[{"ddc":["000"],"quality_controlled":"1","doi":"10.4230/LIPIcs.CONCUR.2026.12","year":"2026","ec_funded":1,"researchdata_availability":"no","corr_author":"1","publication_status":"published","citation":{"ama":"Asadi A, Chatterjee K, Kebis P. PAC learning in turn-based stochastic games with reachability objectives: A decentralized private approach via expected conditional distance. In: <i>37th International Conference on Concurrency Theory</i>. Vol 391. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2026. doi:<a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2026.12\">10.4230/LIPIcs.CONCUR.2026.12</a>","short":"A. Asadi, K. Chatterjee, P. Kebis, in:, 37th International Conference on Concurrency Theory, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2026.","ista":"Asadi A, Chatterjee K, Kebis P. 2026. PAC learning in turn-based stochastic games with reachability objectives: A decentralized private approach via expected conditional distance. 37th International Conference on Concurrency Theory. CONCUR: Conference on Concurrency Theory, LIPIcs, vol. 391, 12:1-12:23.","apa":"Asadi, A., Chatterjee, K., &#38; Kebis, P. (2026). PAC learning in turn-based stochastic games with reachability objectives: A decentralized private approach via expected conditional distance. In <i>37th International Conference on Concurrency Theory</i> (Vol. 391). Liverpool, United Kingdom: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. <a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2026.12\">https://doi.org/10.4230/LIPIcs.CONCUR.2026.12</a>","ieee":"A. Asadi, K. Chatterjee, and P. Kebis, “PAC learning in turn-based stochastic games with reachability objectives: A decentralized private approach via expected conditional distance,” in <i>37th International Conference on Concurrency Theory</i>, Liverpool, United Kingdom, 2026, vol. 391.","chicago":"Asadi, Ali, Krishnendu Chatterjee, and Pavol Kebis. “PAC Learning in Turn-Based Stochastic Games with Reachability Objectives: A Decentralized Private Approach via Expected Conditional Distance.” In <i>37th International Conference on Concurrency Theory</i>, Vol. 391. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2026. <a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2026.12\">https://doi.org/10.4230/LIPIcs.CONCUR.2026.12</a>.","mla":"Asadi, Ali, et al. “PAC Learning in Turn-Based Stochastic Games with Reachability Objectives: A Decentralized Private Approach via Expected Conditional Distance.” <i>37th International Conference on Concurrency Theory</i>, vol. 391, 12:1-12:23, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2026, doi:<a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2026.12\">10.4230/LIPIcs.CONCUR.2026.12</a>."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"project":[{"name":"Bilateral Artificial Intelligence (Chatterjee)","_id":"4029cfc7-b034-11f1-9e55-88ab2ff3b6ee","grant_number":"COE12"},{"call_identifier":"H2020","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","grant_number":"863818","name":"Formal Methods for Stochastic Models: Algorithms and Applications"},{"name":"Interface Theory for Security and Privacy","_id":"34a1b658-11ca-11ed-8bc3-c75229f0241e","grant_number":"F8502"},{"name":"Vigilant Algorithmic Monitoring of Software","grant_number":"101020093","_id":"62781420-2b32-11ec-9570-8d9b63373d4d","call_identifier":"H2020"}],"das_tickbox":"0","OA_place":"publisher","supplementarymaterial":"yes","article_number":"12:1-12:23","alternative_title":["LIPIcs"],"file":[{"date_updated":"2026-09-17T09:50:00Z","file_name":"2026_LIPIcsCONCUR_Asadi2.pdf","success":1,"creator":"dernst","access_level":"open_access","checksum":"2e6c55b65d9d7ce436a6f59e81d7ba17","file_id":"22947","file_size":959234,"relation":"main_file","content_type":"application/pdf","date_created":"2026-09-17T09:50:00Z"}],"keyword":["formal methods","games and logic","logical aspects of AI","model checking"],"OA_type":"gold","intvolume":"       391","publisher":"Schloss Dagstuhl - Leibniz-Zentrum für Informatik","article_processing_charge":"Yes","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"type":"conference","license":"https://creativecommons.org/licenses/by/4.0/","date_created":"2026-09-13T22:01:53Z","volume":391,"day":"24","date_updated":"2026-09-17T09:51:25Z","abstract":[{"text":"Reachability is the most fundamental logical objective, yet it is notoriously difficult to learn in reinforcement learning settings: even for Markov decision processes, PAC learning of reachability is impossible without additional assumptions. This difficulty also holds in turn-based stochastic games (TBSGs), where two adversarial players interact on a finite state space. In this work, we consider turn-based stochastic games with reachability objectives. For such settings, adversarial learning, in which players are adversarial even in the learning phase, is impossible. Therefore, the goal is to consider learning, in which both players learn the unknown model together. In this spirit, previous literature on PAC learning in TBSGs considers (a) public information shared by both players; and (b) centralized learning, which means that players share the same learning algorithm. In this work, our contribution is two-fold. First, we relax these strong assumptions and ensure learning: (i) with private information not shared with the other player; and (ii) decentralized learning where the players do not share the same learning algorithm. To the best of our knowledge, this work is the first positive result for decentralized and private information learning of TBSGs with reachability objectives. Second, we introduce a game-theoretic generalization of the Expected Conditional Distance (ECD) parameter, which measures the expected length of reaching the target set. We establish a polynomial-sample complexity bound with respect to the number of states, actions, ECD parameter, and inverses of error tolerance and failure probability.","lang":"eng"}],"fulldoi":"https://doi.org/10.4230/LIPIcs.CONCUR.2026.12","month":"08","language":[{"iso":"eng"}],"has_accepted_license":"1","department":[{"_id":"GradSch"},{"_id":"KrCh"},{"_id":"ToHe"}],"status":"public","oa_version":"Published Version","conference":{"end_date":"2026-09-04","start_date":"2026-09-01","location":"Liverpool, United Kingdom","name":"CONCUR: Conference on Concurrency Theory"},"acknowledgement":"The research was partially supported by Austrian Science Fund (FWF) 10.55776/COE12,\r\nERC CoG 863818 (ForM-SMArt), FWF-2022-SFB F8502 (SPyCoDe), and ERC-2020-AdG 101020093\r\n(VAMOS) grants.","_id":"22919","external_id":{"arxiv":["2607.14877"]},"publication":"37th International Conference on Concurrency Theory","scopus_import":"1","author":[{"id":"02d96aae-000e-11ec-b801-cadd0a5eefbb","first_name":"Ali","last_name":"Asadi","full_name":"Asadi, Ali"},{"orcid":"0000-0002-4561-241X","first_name":"Krishnendu","last_name":"Chatterjee","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","full_name":"Chatterjee, Krishnendu"},{"last_name":"Kebis","full_name":"Kebis, Pavol","first_name":"Pavol","id":"2e0132b3-4e98-11ef-b275-cf7281c2802a"}],"file_date_updated":"2026-09-17T09:50:00Z","arxiv":1,"date_published":"2026-08-24T00:00:00Z","title":"PAC learning in turn-based stochastic games with reachability objectives: A decentralized private approach via expected conditional distance","publication_identifier":{"eissn":["1868-8969"],"isbn":["9783959774475"]}},{"ddc":["530"],"quality_controlled":"1","year":"2026","doi":"10.1038/s41467-026-75598-1","ec_funded":1,"publication_status":"published","citation":{"short":"A. Kerschbaumer, J.-Y.M. Desaules, M. Ljubotina, M. Serbyn, Nature Communications 17 (2026).","ama":"Kerschbaumer A, Desaules J-YM, Ljubotina M, Serbyn M. Quasi-solitons in Rydberg atom chains. <i>Nature Communications</i>. 2026;17. doi:<a href=\"https://doi.org/10.1038/s41467-026-75598-1\">10.1038/s41467-026-75598-1</a>","ista":"Kerschbaumer A, Desaules J-YM, Ljubotina M, Serbyn M. 2026. Quasi-solitons in Rydberg atom chains. Nature Communications. 17, 8783.","apa":"Kerschbaumer, A., Desaules, J.-Y. M., Ljubotina, M., &#38; Serbyn, M. (2026). Quasi-solitons in Rydberg atom chains. <i>Nature Communications</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41467-026-75598-1\">https://doi.org/10.1038/s41467-026-75598-1</a>","ieee":"A. Kerschbaumer, J.-Y. M. Desaules, M. Ljubotina, and M. Serbyn, “Quasi-solitons in Rydberg atom chains,” <i>Nature Communications</i>, vol. 17. Springer Nature, 2026.","chicago":"Kerschbaumer, Aron, Jean-Yves Marc Desaules, Marko Ljubotina, and Maksym Serbyn. “Quasi-Solitons in Rydberg Atom Chains.” <i>Nature Communications</i>. Springer Nature, 2026. <a href=\"https://doi.org/10.1038/s41467-026-75598-1\">https://doi.org/10.1038/s41467-026-75598-1</a>.","mla":"Kerschbaumer, Aron, et al. “Quasi-Solitons in Rydberg Atom Chains.” <i>Nature Communications</i>, vol. 17, 8783, Springer Nature, 2026, doi:<a href=\"https://doi.org/10.1038/s41467-026-75598-1\">10.1038/s41467-026-75598-1</a>."},"researchdata_availability":"yes","corr_author":"1","PlanS_conform":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","OA_place":"publisher","project":[{"call_identifier":"H2020","_id":"fc2ed2f7-9c52-11eb-aca3-c01059dda49c","grant_number":"101034413","name":"IST-BRIDGE: International postdoctoral program"},{"grant_number":"COE01","_id":"92c64506-16d5-11f0-9cad-87ce313ee832","name":"Quantum Science Austria (Serbyn)"}],"related_material":{"record":[{"status":"public","id":"21960","relation":"research_data"}]},"oa":1,"das_tickbox":"1","pmid":1,"article_type":"original","supplementarymaterial":"yes","article_number":"8783","file":[{"file_name":"2026_NatureComm_Kerschbaumer.pdf","date_updated":"2026-09-09T07:04:48Z","checksum":"2e12ade81e19b7eea099a2196217edff","file_id":"22863","success":1,"access_level":"open_access","creator":"dernst","content_type":"application/pdf","relation":"main_file","file_size":1337815,"date_created":"2026-09-09T07:04:48Z"}],"intvolume":"        17","OA_type":"gold","publisher":"Springer Nature","DOAJ_listed":"1","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"article_processing_charge":"Yes","type":"journal_article","date_created":"2026-07-27T07:26:27Z","volume":17,"abstract":[{"text":"Solitons—localized wave packets that travel without spreading—play a central role in understanding transport and properties of nonlinear systems. In quantum many-body systems, however, such robust excitations are typically destroyed by thermalization. Here, we theoretically demonstrate the existence of solitonic excitations in high-energy states of Rydberg atom chains in the regime of strong nearest-neighbor Rydberg blockade. These localized wave packets propagate directionally atop a special class of reviving initial states related to quantum many-body scars and are capable of carrying energy. Exhibiting long coherence times, these states constitute a form of non-ergodic quantum dynamics and can be efficiently implemented on Rydberg atom simulators. In this work, in addition to a phenomenological description of solitons, we identify their counterpart in a classical nonlinear dynamical system, demonstrate their potential use in quantum information transfer, and conjecture their relevance for anomalous energy transport reported in numerical studies of Rydberg atom arrays.","lang":"eng"}],"fulldoi":"https://doi.org/10.1038/s41467-026-75598-1","day":"21","date_updated":"2026-09-17T10:54:09Z","department":[{"_id":"MaSe"},{"_id":"GradSch"}],"status":"public","language":[{"iso":"eng"}],"month":"08","has_accepted_license":"1","acknowledgement":"We acknowledge useful discussions with J.-S. Caux, E. Demler, J. Dubail, F. Essler, J. Feldmeier, S. Garratt, W. W. Ho, M. Lukin, Z. Papic, S. Rotter, F. Surace, and R. Vasseur. J.-Y.D. acknowledges funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 101034413. M. L. acknowledges support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy—EXC-2111—390814868. We acknowledge support by the Erwin Schrödinger International Institute for Mathematics and Physics (ESI). This research was funded in part by the Austrian Science Fund (FWF) https://doi.org/10.55776/COE1 and the European Union—NextGenerationEU. This research was supported in part by grant NSF PHY2309135 to the Kavli Institute for Theoretical Physics (KITP).","_id":"22408","dataavailabilitystatement":"The raw data used to generate the figures are available at ref54.The TEBD algorithm used in this work was implemented using the ITensor library48,49 and the integration of the classical differential equations was performed via SciPy’s Runge-Kutta RK45 integrator52,53. The code used in this study to produce the plots from the shared data is available at ref.54.","oa_version":"Published Version","external_id":{"pmid":["42469244"]},"author":[{"orcid":"0009-0002-2370-8661","first_name":"Aron","id":"ade85a9c-3200-11ee-973b-91c1eb240410","last_name":"Kerschbaumer","full_name":"Kerschbaumer, Aron"},{"id":"6c292945-a610-11ed-9eec-c3be1ad62a80","first_name":"Jean-Yves Marc","full_name":"Desaules, Jean-Yves Marc","last_name":"Desaules","orcid":"0000-0002-3749-6375"},{"last_name":"Ljubotina","id":"F75EE9BE-5C90-11EA-905D-16643DDC885E","full_name":"Ljubotina, Marko","first_name":"Marko","orcid":"0000-0003-0038-7068"},{"first_name":"Maksym","id":"47809E7E-F248-11E8-B48F-1D18A9856A87","full_name":"Serbyn, Maksym","last_name":"Serbyn","orcid":"0000-0002-2399-5827"}],"scopus_import":"1","publication":"Nature Communications","file_date_updated":"2026-09-09T07:04:48Z","date_published":"2026-08-21T00:00:00Z","title":"Quasi-solitons in Rydberg atom chains","publication_identifier":{"eissn":["2041-1723"]}},{"tmp":{"short":"CC BY-NC (4.0)","image":"/images/cc_by_nc.png","legal_code_url":"https://creativecommons.org/licenses/by-nc/4.0/legalcode","name":"Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)"},"type":"research_data","article_processing_charge":"No","license":"https://creativecommons.org/licenses/by-nc/4.0/","date_created":"2026-06-09T07:17:50Z","date_updated":"2026-09-17T10:54:08Z","day":"16","abstract":[{"lang":"eng","text":"Solitons - localized wave packets that travel without spreading - play a central role in understanding transport and properties of nonlinear systems. In quantum many-body systems, however, such robust excitations are typically destroyed by thermalization. Here, we theoretically demonstrate the existence of solitonic excitations in high-energy states of Rydberg atom chains in the regime of strong nearest-neighbor Rydberg blockade. \r\nThese localized wave packets propagate directionally atop a special class of reviving initial states related to quantum many-body scars and are capable of carrying energy. Exhibiting long coherence times, these states constitute a form of non-ergodic quantum dynamics and can be efficiently implemented on Rydberg atom simulators. In this work, in addition to a phenomenological description of solitons, we identify their counterpart in a classical nonlinear dynamical system, demonstrate their potential use in quantum information transfer, and conjecture their relevance for anomalous energy transport reported in numerical studies of Rydberg atom arrays."}],"fulldoi":"https://doi.org/10.15479/AT-ISTA-21960","month":"06","has_accepted_license":"1","status":"public","department":[{"_id":"GradSch"},{"_id":"MaSe"}],"oa_version":"Published Version","_id":"21960","author":[{"orcid":"0009-0002-2370-8661","first_name":"Aron","full_name":"Kerschbaumer, Aron","id":"ade85a9c-3200-11ee-973b-91c1eb240410","last_name":"Kerschbaumer"}],"file_date_updated":"2026-06-15T22:02:07Z","date_published":"2026-06-16T00:00:00Z","title":"Research Data: \"Quasi-solitons in Rydberg atom chains\"","year":"2026","doi":"10.15479/AT-ISTA-21960","ec_funded":1,"corr_author":"1","citation":{"ama":"Kerschbaumer A. Research Data: “Quasi-solitons in Rydberg atom chains.” 2026. doi:<a href=\"https://doi.org/10.15479/AT-ISTA-21960\">10.15479/AT-ISTA-21960</a>","short":"A. Kerschbaumer, (2026).","apa":"Kerschbaumer, A. (2026). Research Data: “Quasi-solitons in Rydberg atom chains.” Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT-ISTA-21960\">https://doi.org/10.15479/AT-ISTA-21960</a>","ieee":"A. Kerschbaumer, “Research Data: ‘Quasi-solitons in Rydberg atom chains.’” Institute of Science and Technology Austria, 2026.","ista":"Kerschbaumer A. 2026. Research Data: ‘Quasi-solitons in Rydberg atom chains’, Institute of Science and Technology Austria, <a href=\"https://doi.org/10.15479/AT-ISTA-21960\">10.15479/AT-ISTA-21960</a>.","mla":"Kerschbaumer, Aron. <i>Research Data: “Quasi-Solitons in Rydberg Atom Chains.”</i> Institute of Science and Technology Austria, 2026, doi:<a href=\"https://doi.org/10.15479/AT-ISTA-21960\">10.15479/AT-ISTA-21960</a>.","chicago":"Kerschbaumer, Aron. “Research Data: ‘Quasi-Solitons in Rydberg Atom Chains.’” Institute of Science and Technology Austria, 2026. <a href=\"https://doi.org/10.15479/AT-ISTA-21960\">https://doi.org/10.15479/AT-ISTA-21960</a>."},"user_id":"68b8ca59-c5b3-11ee-8790-cd641c68093d","project":[{"call_identifier":"H2020","name":"IST-BRIDGE: International postdoctoral program","_id":"fc2ed2f7-9c52-11eb-aca3-c01059dda49c","grant_number":"101034413"}],"related_material":{"record":[{"id":"22408","relation":"used_in_publication","status":"public"}]},"oa":1,"OA_place":"repository","file":[{"date_updated":"2026-06-15T22:01:57Z","file_name":"README.txt","creator":"akerschb","access_level":"open_access","success":1,"file_id":"22010","checksum":"133269a105e996c6c44fdd56128259c7","file_size":1940,"relation":"main_file","content_type":"text/plain","date_created":"2026-06-15T22:01:57Z"},{"file_name":"Soliton_Data.zip","date_updated":"2026-06-15T22:02:07Z","file_id":"22011","checksum":"759f9649c3919f4c4ad37a1d104ea32a","access_level":"open_access","creator":"akerschb","success":1,"content_type":"application/zip","file_size":13259747,"relation":"main_file","date_created":"2026-06-15T22:02:07Z"}],"contributor":[{"contributor_type":"contact_person","orcid":"0009-0002-2370-8661","first_name":"Aron","id":"ade85a9c-3200-11ee-973b-91c1eb240410","last_name":"Kerschbaumer"},{"contributor_type":"supervisor","orcid":"0000-0002-2399-5827","first_name":"Maksym","id":"47809E7E-F248-11E8-B48F-1D18A9856A87","last_name":"Serbyn"},{"first_name":"Jean-Yves Marc","last_name":"Desaules","id":"6c292945-a610-11ed-9eec-c3be1ad62a80","orcid":"0000-0002-3749-6375","contributor_type":"researcher"},{"contributor_type":"researcher","last_name":"Ljubotina","first_name":"Marko"}],"publisher":"Institute of Science and Technology Austria"},{"date_published":"2026-09-07T00:00:00Z","file_date_updated":"2026-09-11T07:32:17Z","publication_identifier":{"isbn":["978-3-99078-089-3"],"issn":["2663-337X"]},"title":"Monitoring algorithmic fairness in sequential decision making","_id":"22808","acknowledgement":"This work was supported in part by the ERC-2020-AdG 101020093 (VAMOS).\r\n","oa_version":"Published Version","author":[{"orcid":"0000-0001-8974-2542","id":"8121a2d0-dc85-11ea-9058-af578f3b4515","full_name":"Kueffner, Konstantin","last_name":"Kueffner","first_name":"Konstantin"}],"fulldoi":"https://doi.org/10.15479/AT-ISTA-22808","doi_confirm":"1","abstract":[{"lang":"eng","text":"As automated decision-makers have become ubiquitous in many domains of life,\r\ntheir decisions have become increasingly consequential. Recent years have shown\r\nthat such systems can exhibit discriminatory behaviour against individuals and\r\nsocial groups alike, thereby amplifying existing biases and entrenching\r\nsocio-economic disparities over time. Algorithmic fairness addresses this\r\nproblem by developing methods to quantify and mitigate unfair behaviour.\r\nHowever, much of the existing literature studies fairness in a static\r\npre-deployment setting and, therefore, neglects that automated decision-makers are\r\noften deployed in dynamic environments, where their behaviour and the\r\npopulations they affect may change over time.\r\n\r\nThis thesis addresses this gap through the lens of runtime verification.\r\nInstead of treating fairness as a property of a classifier together with a fixed\r\ninput distribution, it reframes fairness as a property of the interaction trace\r\nbetween the decision-maker and its deployment environment. To evaluate such\r\nsequential fairness properties, the thesis develops runtime monitors that\r\nobserve the evolving interaction between the system and the environment and\r\nissue verdicts after each new observation. Because, these monitors are designed to detect\r\nunfair behaviour during deployment, they complement fair training,\r\nauditing, verification, and enforcement by providing an additional layer of mathematically rigorous fairness assurance.\r\n\r\nIn summary, the thesis develops quantitative, trace-based analogues of\r\nclassical group and individual fairness measures and constructs monitors for\r\nthem. This includes monitors for long-run group fairness over Markovian traces,\r\nfor the time-varying welfare of a changing population in a dynamical system, and\r\nfor the individual fairness of an arbitrary system generating a trace of inputs\r\nand outputs. To achieve this, the monitors combine ideas from runtime\r\nverification, sequential statistics, and nearest-neighbour search. In the\r\ngroup-fairness settings, monitoring is primarily a sequential statistical\r\nestimation problem: the monitor must construct statistically sound interval\r\nestimates of fairness values from dependent and partially observed interactions.\r\nIn the individual-fairness setting, the main challenge is computational\r\nefficiency: the monitor must detect individual fairness violations by efficiently comparing the\r\ncurrent decision with all previously observed decisions.\r\n"}],"day":"07","date_updated":"2026-09-18T07:41:29Z","status":"public","department":[{"_id":"GradSch"},{"_id":"ToHe"}],"has_accepted_license":"1","language":[{"iso":"eng"}],"month":"09","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"article_processing_charge":"No","type":"dissertation","date_created":"2026-09-05T15:59:19Z","file":[{"creator":"kkueffne","access_level":"closed","file_id":"22903","checksum":"716ce44a6ed9a727f231bdebdeecc741","date_updated":"2026-09-11T07:32:13Z","file_name":"Thesis_Konstantin_Kueffner-3.zip","date_created":"2026-09-11T07:32:13Z","relation":"source_file","file_size":26356903,"content_type":"application/zip"},{"relation":"main_file","file_size":10051715,"content_type":"application/pdf","date_created":"2026-09-11T07:32:17Z","date_updated":"2026-09-11T07:32:17Z","file_name":"Thesis_Konstantin_Kueffner-2.pdf","creator":"kkueffne","access_level":"open_access","checksum":"77082e90b8330fb46f585843840c5d5c","file_id":"22904"}],"alternative_title":["ISTA Thesis"],"publisher":"Institute of Science and Technology Austria","OA_place":"publisher","project":[{"name":"Vigilant Algorithmic Monitoring of Software","grant_number":"101020093","_id":"62781420-2b32-11ec-9570-8d9b63373d4d","call_identifier":"H2020"}],"related_material":{"record":[{"status":"public","id":"13310","relation":"part_of_dissertation"},{"relation":"part_of_dissertation","id":"14454","status":"public"},{"status":"public","relation":"part_of_dissertation","id":"20292"},{"id":"21090","relation":"part_of_dissertation","status":"public"},{"relation":"part_of_dissertation","id":"13228","status":"public"}]},"oa":1,"supervisor":[{"orcid":"0000-0002-2985-7724","first_name":"Thomas A","full_name":"Henzinger, Thomas A","last_name":"Henzinger","id":"40876CD8-F248-11E8-B48F-1D18A9856A87"}],"citation":{"mla":"Kueffner, Konstantin. <i>Monitoring Algorithmic Fairness in Sequential Decision Making</i>. Institute of Science and Technology Austria, 2026, doi:<a href=\"https://doi.org/10.15479/AT-ISTA-22808\">10.15479/AT-ISTA-22808</a>.","chicago":"Kueffner, Konstantin. “Monitoring Algorithmic Fairness in Sequential Decision Making.” Institute of Science and Technology Austria, 2026. <a href=\"https://doi.org/10.15479/AT-ISTA-22808\">https://doi.org/10.15479/AT-ISTA-22808</a>.","ieee":"K. Kueffner, “Monitoring algorithmic fairness in sequential decision making,” Institute of Science and Technology Austria, 2026.","apa":"Kueffner, K. (2026). <i>Monitoring algorithmic fairness in sequential decision making</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT-ISTA-22808\">https://doi.org/10.15479/AT-ISTA-22808</a>","ista":"Kueffner K. 2026. Monitoring algorithmic fairness in sequential decision making. Institute of Science and Technology Austria.","short":"K. Kueffner, Monitoring Algorithmic Fairness in Sequential Decision Making, Institute of Science and Technology Austria, 2026.","ama":"Kueffner K. Monitoring algorithmic fairness in sequential decision making. 2026. doi:<a href=\"https://doi.org/10.15479/AT-ISTA-22808\">10.15479/AT-ISTA-22808</a>"},"publication_status":"published","corr_author":"1","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","degree_awarded":"PhD","ddc":["000"],"ec_funded":1,"page":"183","doi":"10.15479/AT-ISTA-22808","year":"2026"},{"file":[{"file_id":"22901","checksum":"a5e3d79e0e5f3f4fb3c414e48116dc9e","creator":"aehrmann","access_level":"closed","file_name":"2026_Ehrmann_Andreas_Thesis.pdf","date_updated":"2026-09-17T08:59:39Z","embargo_to":"open_access","date_created":"2026-09-11T07:23:57Z","content_type":"application/pdf","embargo":"2027-01-15","relation":"main_file","file_size":14782662},{"description":"All LaTeX files to compile my PhD Thesis.","date_created":"2026-09-11T07:24:14Z","content_type":"application/zip","file_size":155228,"relation":"source_file","checksum":"0235b9c52fee0c97f402f1c3d4efc1eb","file_id":"22902","creator":"aehrmann","access_level":"closed","file_name":"thesis_latex_files.zip","date_updated":"2026-09-11T07:24:14Z"}],"alternative_title":["ISTA Thesis"],"publisher":"Institute of Science and Technology Austria","keyword":["PhD Thesis","functional nanomachines","biological functionality","nanotechnology","energy delivery","target behavior","dynamics","design principles","optimization","differentiable statistical physics","machine learning"],"OA_place":"publisher","das_tickbox":"0","project":[{"grant_number":"PAT 8537123","_id":"90a98bb5-16d5-11f0-9cad-9675f3f8015d","name":"Functional bio-inspired nanomachines from sticky colloids"}],"related_material":{"record":[{"status":"public","relation":"part_of_dissertation","id":"22893"},{"relation":"part_of_dissertation","id":"22892","status":"public"}]},"supervisor":[{"orcid":"0000-0002-1307-5074","first_name":"Carl Peter","full_name":"Goodrich, Carl Peter","last_name":"Goodrich","id":"EB352CD2-F68A-11E9-89C5-A432E6697425"},{"last_name":"Hannezo","first_name":"Edouard B","full_name":"Hannezo, Edouard B","id":"3A9DB764-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6005-1561"}],"supplementarymaterial":"not applicable","citation":{"ama":"Ehrmann A. Biological functionality without biochemistry: Designing nanomachines for target behavior. 2026. doi:<a href=\"https://doi.org/10.15479/AT-ISTA-22873\">10.15479/AT-ISTA-22873</a>","short":"A. Ehrmann, Biological Functionality without Biochemistry: Designing Nanomachines for Target Behavior, Institute of Science and Technology Austria, 2026.","mla":"Ehrmann, Andreas. <i>Biological Functionality without Biochemistry: Designing Nanomachines for Target Behavior</i>. Institute of Science and Technology Austria, 2026, doi:<a href=\"https://doi.org/10.15479/AT-ISTA-22873\">10.15479/AT-ISTA-22873</a>.","chicago":"Ehrmann, Andreas. “Biological Functionality without Biochemistry: Designing Nanomachines for Target Behavior.” Institute of Science and Technology Austria, 2026. <a href=\"https://doi.org/10.15479/AT-ISTA-22873\">https://doi.org/10.15479/AT-ISTA-22873</a>.","ieee":"A. Ehrmann, “Biological functionality without biochemistry: Designing nanomachines for target behavior,” Institute of Science and Technology Austria, 2026.","apa":"Ehrmann, A. (2026). <i>Biological functionality without biochemistry: Designing nanomachines for target behavior</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT-ISTA-22873\">https://doi.org/10.15479/AT-ISTA-22873</a>","ista":"Ehrmann A. 2026. Biological functionality without biochemistry: Designing nanomachines for target behavior. Institute of Science and Technology Austria."},"publication_status":"published","corr_author":"1","researchdata_availability":"upon request","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","degree_awarded":"PhD","ddc":["530","600","621","004","005"],"page":"168","year":"2026","doi":"10.15479/AT-ISTA-22873","date_published":"2026-09-04T00:00:00Z","file_date_updated":"2026-09-17T08:59:39Z","publication_identifier":{"issn":["2663-337X"],"isbn":["978-3-99078-092-3"]},"title":"Biological functionality without biochemistry: Designing nanomachines for target behavior","_id":"22873","acknowledgement":"I acknowledge funding by the Austrian Science Fund (FWF) [10.55776/PAT8537123].","oa_version":"Published Version","author":[{"orcid":"0000-0002-0997-5678","first_name":"Andreas","last_name":"Ehrmann","id":"eaa689ed-f6e0-11ea-865d-bd98cbcf83c2","full_name":"Ehrmann, Andreas"}],"doi_confirm":"1","fulldoi":"https://doi.org/10.15479/AT-ISTA-22873","day":"04","date_updated":"2026-09-18T11:28:29Z","department":[{"_id":"GradSch"},{"_id":"CaGo"},{"_id":"EdHa"}],"status":"public","has_accepted_license":"1","acknowledged_ssus":[{"_id":"ScienComp"},{"_id":"CampIT"}],"language":[{"iso":"eng"}],"month":"09","license":"https://creativecommons.org/licenses/by-nc-sa/4.0/","tmp":{"image":"/images/cc_by_nc_sa.png","legal_code_url":"https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode","name":"Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)","short":"CC BY-NC-SA (4.0)"},"type":"dissertation","article_processing_charge":"No","date_created":"2026-09-09T12:18:24Z"},{"doi_confirm":"1","fulldoi":"https://doi.org/10.15479/AT-ISTA-22857","abstract":[{"text":"Artificial intelligence and machine learning have undergone an unprecedented evolution in the past decade, motivating a research effort toward a theory able to capture the qualitative behavior of large-scale neural systems. A central puzzle has been the clear benefit of scaling architecture size and overfitting the training set in supervised learning tasks. This evidence, in apparent contradiction with classical statistical learning theory, pushed researchers to develop a new theory capturing the interplay between the algorithmic and architectural bias of training and the specific target function, differently from previous methods rooted in uniform stability.\r\nThis approach has enabled a grounded understanding of novel learning regimes, typically through formal limits where the number of training samples $n$, data dimensions $d$, and model parameters $p$ grow to infinity at different rates. \\\\\r\nIn this thesis, we follow this approach, focusing on the trustworthiness of high-dimensional models: properties that are difficult to control during training or deployment and often emerge under unpredictable or adversarial conditions. In such settings, it is crucial to formally ensure a priori the reliability of machine learning systems.\r\nFirst, we study data memorization, both as label fitting and as the storage of private information about training samples in trained parameters. We prove that $p = \\Omega(n)$ parameters are sufficient for a deep neural network to memorize a generic set of labels, and for a model to memorize spurious features across training data. We then give evidence that $p = \\Omega(dn)$ parameters are instead necessary for an adversary to reconstruct the full training set from the trained parameters.\r\nSecond, we study robustness, both to adversarial perturbations and to distribution shift. We first prove that $p = \\Omega(dn)$ parameters can be sufficient for a class of neural networks to overfit the training data while guaranteeing robustness to adversarial perturbations. Then, we focus on spurious correlations learning in high-dimensional regression, studying the effect of the ridge regularization parameter in the proportional regime $n = \\Theta(d)$, and connecting it via an equivalence argument to the role of over-parameterization $p = \\Omega(n)$ in neural networks. We also investigate the architectural bias of attention-based networks, showing that they are sensitive to the replacement of individual words in an embedded sentence, allowing them to generalize on sentences where the contextual meaning depends on one or few words.\r\nFinally, we study differentially private optimization in high-dimensional regimes. We prove that standard private gradient methods do not suffer in the over-parameterized regime $p = \\Omega(n)$, challenging the current wisdom based on stability-derived generalization bounds. We then consider linear regression in the proportional regime $n = \\Theta(d)$, showing that standard private gradient descent can achieve optimal rates under appropriate hyper-parameter scaling, such as sufficiently small gradient clipping constants, whose role is still debated in practice.","lang":"eng"}],"date_updated":"2026-09-21T13:07:01Z","day":"08","status":"public","department":[{"_id":"GradSch"},{"_id":"MaMo"}],"has_accepted_license":"1","acknowledged_ssus":[{"_id":"ScienComp"}],"month":"09","language":[{"iso":"eng"}],"type":"dissertation","article_processing_charge":"No","date_created":"2026-09-08T13:40:08Z","date_published":"2026-09-08T00:00:00Z","file_date_updated":"2026-09-10T10:03:48Z","publication_identifier":{"issn":["2663-337X"],"isbn":["978-3-99078-091-6"]},"title":"Trustworthy machine learning in high dimensions","_id":"22857","acknowledgement":"This project was partially supported by the 2019 Lopez-Loreta prize,\r\nthe European Union (ERC, INF2\r\n, project number 101161364), the Austrian Science Fund\r\n(FWF) 10.55776/COE12, and a Google PhD fellowship in machine intelligence. Furthermore,\r\nthe candidate acknowledges the support from the Scientific Service Units of the Institute of\r\nScience and Technology Austria through resources provided by Scientific Computing.","oa_version":"Published Version","author":[{"last_name":"Bombari","first_name":"Simone","full_name":"Bombari, Simone","id":"ca726dda-de17-11ea-bc14-f9da834f63aa"}],"citation":{"apa":"Bombari, S. (2026). <i>Trustworthy machine learning in high dimensions</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT-ISTA-22857\">https://doi.org/10.15479/AT-ISTA-22857</a>","ieee":"S. Bombari, “Trustworthy machine learning in high dimensions,” Institute of Science and Technology Austria, 2026.","ista":"Bombari S. 2026. Trustworthy machine learning in high dimensions. Institute of Science and Technology Austria.","mla":"Bombari, Simone. <i>Trustworthy Machine Learning in High Dimensions</i>. Institute of Science and Technology Austria, 2026, doi:<a href=\"https://doi.org/10.15479/AT-ISTA-22857\">10.15479/AT-ISTA-22857</a>.","chicago":"Bombari, Simone. “Trustworthy Machine Learning in High Dimensions.” Institute of Science and Technology Austria, 2026. <a href=\"https://doi.org/10.15479/AT-ISTA-22857\">https://doi.org/10.15479/AT-ISTA-22857</a>.","short":"S. Bombari, Trustworthy Machine Learning in High Dimensions, Institute of Science and Technology Austria, 2026.","ama":"Bombari S. Trustworthy machine learning in high dimensions. 2026. doi:<a href=\"https://doi.org/10.15479/AT-ISTA-22857\">10.15479/AT-ISTA-22857</a>"},"publication_status":"published","corr_author":"1","researchdata_availability":"no","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","degree_awarded":"PhD","ddc":["519"],"page":"446","year":"2026","doi":"10.15479/AT-ISTA-22857","file":[{"relation":"source_file","file_size":99154325,"content_type":"application/zip","date_created":"2026-09-08T13:28:38Z","date_updated":"2026-09-08T13:28:38Z","file_name":"Thesis copy.zip","creator":"sbombari","access_level":"closed","file_id":"22859","checksum":"8eab99d6dc6e4476826bdfc7c00fdebb"},{"date_created":"2026-09-10T10:03:48Z","content_type":"application/pdf","file_size":12856211,"relation":"main_file","checksum":"007033bafe4622ff4c2e758301354df1","file_id":"22898","success":1,"creator":"sbombari","access_level":"open_access","file_name":"2026_Bombari_Simone_Thesis.pdf","date_updated":"2026-09-10T10:03:48Z"}],"alternative_title":["ISTA Thesis"],"publisher":"Institute of Science and Technology Austria","keyword":["machine learning","high-dimensional statistics","deep learning theory","privacy","memorization","robustness"],"OA_place":"publisher","related_material":{"record":[{"status":"public","id":"12537","relation":"part_of_dissertation"},{"relation":"part_of_dissertation","id":"18972","status":"public"},{"id":"18973","relation":"part_of_dissertation","status":"public"},{"relation":"part_of_dissertation","id":"21324","status":"public"},{"id":"22894","relation":"part_of_dissertation","status":"public"},{"relation":"part_of_dissertation","id":"19627","status":"public"},{"id":"12859","relation":"part_of_dissertation","status":"public"}]},"project":[{"name":"Trustworthy Deep Learning Theory: Private Over-Parameterized Models and Robust LLMs","_id":"92099302-16d5-11f0-9cad-f9a785f54fbd"},{"grant_number":"101161364","_id":"911e6d1f-16d5-11f0-9cad-c5c68c6a1cdf","name":"Inference in High Dimensions: Light-speed Algorithms and Information Limits"},{"name":"Bilateral Artificial Intelligence (Mondelli)","grant_number":"COE12","_id":"74caaef7-b034-11f1-8f2d-e0e993bb422e"}],"oa":1,"das_tickbox":"0","supervisor":[{"orcid":"0000-0002-3242-7020","last_name":"Mondelli","first_name":"Marco","id":"27EB676C-8706-11E9-9510-7717E6697425","full_name":"Mondelli, Marco"}],"supplementarymaterial":"no"},{"date_published":"2026-01-26T00:00:00Z","arxiv":1,"file_date_updated":"2026-09-11T12:07:48Z","publication_identifier":{"isbn":["9798331339678"]},"title":"A law of data reconstruction for random features (and beyond)","_id":"22894","acknowledgement":"M.M. is funded by the European Union (ERC, INF2\r\n, project number 101161364). S.B. was supported\r\nby a Google PhD fellowship. L.I. acknowledges the grant received from the European Union NextGenerationEU (Piano Nazionale di Ripresa E Resilienza (PNRR)) DM 351 on Trustworthy AI. T.T. &\r\nL.I. acknowledge the EU project ELSA - European Lighthouse on Secure and Safe AI. This study was\r\ncarried out within the FAIR - Future Artificial Intelligence Research and received funding from the\r\nEuropean Union Next-GenerationEU (PIANO NAZIONALE DI RIPRESA E RESILIENZA (PNRR)\r\n– MISSIONE 4 COMPONENTE 2, INVESTIMENTO 1.3 – D.D. 1555 11/10/2022, PE00000013).\r\nThis manuscript reflects only the authors’ views and opinions, neither the European Union nor the\r\nEuropean Commission can be considered responsible for them. The authors would like to thank\r\nYizhe Zhu for helpful discussions.","conference":{"name":"ICLR: International Conference on Learning Representations ","location":"Rio de Janeiro, Brazil","start_date":"2026-04-23","end_date":"2026-04-27"},"oa_version":"Published Version","publication":"14th International Conference on Learning Representations","author":[{"first_name":"Leonardo","full_name":"Iurada, Leonardo","last_name":"Iurada"},{"full_name":"Bombari, Simone","id":"ca726dda-de17-11ea-bc14-f9da834f63aa","last_name":"Bombari","first_name":"Simone"},{"last_name":"Tommasi","full_name":"Tommasi, Tatiana","first_name":"Tatiana"},{"orcid":"0000-0002-3242-7020","first_name":"Marco","last_name":"Mondelli","id":"27EB676C-8706-11E9-9510-7717E6697425","full_name":"Mondelli, Marco"}],"external_id":{"arxiv":["2509.22214"]},"abstract":[{"text":"Large-scale deep learning models are known to memorize parts of the training\r\nset. In machine learning theory, memorization is often framed as interpolation or\r\nlabel fitting, and classical results show that this can be achieved when the number\r\nof parameters p in the model is larger than the number of training samples n. In\r\nthis work, we consider memorization from the perspective of data reconstruction,\r\ndemonstrating that this can be achieved when p is larger than dn, where d is\r\nthe dimensionality of the data. More specifically, we show that, in the random\r\nfeatures model, when p ≫ dn, the subspace spanned by the training samples in\r\nfeature space gives sufficient information to identify the individual samples in input\r\nspace. Our analysis suggests an optimization method to reconstruct the dataset\r\nfrom the model parameters, and we demonstrate that this method performs well on\r\nvarious architectures (random features, two-layer fully-connected and deep residual\r\nnetworks). Our results reveal a law of data reconstruction, according to which the\r\nentire training dataset can be recovered as p exceeds the threshold dn.\r\n","lang":"eng"}],"date_updated":"2026-09-21T13:07:01Z","day":"26","status":"public","department":[{"_id":"GradSch"},{"_id":"MaMo"}],"has_accepted_license":"1","language":[{"iso":"eng"}],"month":"01","type":"conference","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"article_processing_charge":"No","volume":2026,"date_created":"2026-09-09T13:31:46Z","file":[{"date_created":"2026-09-11T12:07:48Z","content_type":"application/pdf","relation":"main_file","file_size":7869510,"file_id":"22907","checksum":"a3dcba6649b7496124fa0ae68bf2c4cb","access_level":"open_access","creator":"cchlebak","success":1,"file_name":"2026_ICLR_Iurada.pdf","date_updated":"2026-09-11T12:07:48Z"}],"publisher":"OpenReview","intvolume":"      2026","OA_type":"gold","OA_place":"publisher","das_tickbox":"0","related_material":{"record":[{"status":"public","id":"22857","relation":"dissertation_contains"}]},"project":[{"name":"Inference in High Dimensions: Light-speed Algorithms and Information Limits","grant_number":"101161364","_id":"911e6d1f-16d5-11f0-9cad-c5c68c6a1cdf"},{"_id":"92099302-16d5-11f0-9cad-f9a785f54fbd","name":"Trustworthy Deep Learning Theory: Private Over-Parameterized Models and Robust LLMs"}],"oa":1,"citation":{"ama":"Iurada L, Bombari S, Tommasi T, Mondelli M. A law of data reconstruction for random features (and beyond). In: <i>14th International Conference on Learning Representations</i>. Vol 2026. OpenReview; 2026:145275-145314.","short":"L. Iurada, S. Bombari, T. Tommasi, M. Mondelli, in:, 14th International Conference on Learning Representations, OpenReview, 2026, pp. 145275–145314.","ista":"Iurada L, Bombari S, Tommasi T, Mondelli M. 2026. A law of data reconstruction for random features (and beyond). 14th International Conference on Learning Representations. ICLR: International Conference on Learning Representations  vol. 2026, 145275–145314.","apa":"Iurada, L., Bombari, S., Tommasi, T., &#38; Mondelli, M. (2026). A law of data reconstruction for random features (and beyond). In <i>14th International Conference on Learning Representations</i> (Vol. 2026, pp. 145275–145314). Rio de Janeiro, Brazil: OpenReview.","ieee":"L. Iurada, S. Bombari, T. Tommasi, and M. Mondelli, “A law of data reconstruction for random features (and beyond),” in <i>14th International Conference on Learning Representations</i>, Rio de Janeiro, Brazil, 2026, vol. 2026, pp. 145275–145314.","chicago":"Iurada, Leonardo, Simone Bombari, Tatiana Tommasi, and Marco Mondelli. “A Law of Data Reconstruction for Random Features (and Beyond).” In <i>14th International Conference on Learning Representations</i>, 2026:145275–314. OpenReview, 2026.","mla":"Iurada, Leonardo, et al. “A Law of Data Reconstruction for Random Features (and Beyond).” <i>14th International Conference on Learning Representations</i>, vol. 2026, OpenReview, 2026, pp. 145275–314."},"publication_status":"published","corr_author":"1","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","quality_controlled":"1","ddc":["000"],"page":"145275-145314","year":"2026"},{"language":[{"iso":"eng"}],"month":"08","has_accepted_license":"1","department":[{"_id":"ToHe"},{"_id":"GradSch"}],"status":"public","date_updated":"2026-09-22T06:02:06Z","day":"24","abstract":[{"text":"Runtime monitoring of quantitative signals faces a fundamental trade-off between volatility and over-aggregation: instantaneous observations are noisy, while long-run averages obscure local structure. Localisation measures such as discounted averages offer a principled middle ground, yet remain poorly understood in runtime verification. This paper studies discounted sums from a monitoring perspective, in both deterministic and stochastic settings. We formalize the discounted monitoring problem and show that exact, sound monitoring of discounted sums cannot be achieved with finite memory. To overcome this impossibility, we introduce ε-approximately sound monitoring, deriving explicit bounds on memory and observation requirements. We then extend the framework to stochastic processes via expected discounted sums, defining pointwise and uniform (ε,δ)-soundness notions, establishing statistical optimality, and proving impossibility beyond a precision threshold. We also formalize the resource complexity of deterministic discounted monitoring via affine register machines and prove a tight worst-case lower bound. Finally, we present a specification language for arithmetic expressions over multiple discounted sums with synchronous and asynchronous semantics, and evaluate our approach on practical scenarios including algorithmic fairness.","lang":"eng"}],"fulldoi":"https://doi.org/10.4230/LIPIcs.CONCUR.2026.22","volume":391,"date_created":"2026-09-13T22:01:54Z","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"article_processing_charge":"Yes","type":"conference","title":"Monitoring discounted sum properties","publication_identifier":{"isbn":["9783959774475"],"issn":["1868-8969"]},"file_date_updated":"2026-09-22T05:59:03Z","date_published":"2026-08-24T00:00:00Z","arxiv":1,"external_id":{"arxiv":["2606.25979"]},"publication":"37th International Conference on Concurrency Theory","author":[{"orcid":"0000-0002-0783-904X","first_name":"Filip","full_name":"Cano Cordoba, Filip","id":"708cad98-e86a-11ef-8098-bdae2d7c6af1","last_name":"Cano Cordoba"},{"orcid":"0000-0002-2985-7724","last_name":"Henzinger","full_name":"Henzinger, Thomas A","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","first_name":"Thomas A"},{"last_name":"Kueffner","full_name":"Kueffner, Konstantin","first_name":"Konstantin","id":"8121a2d0-dc85-11ea-9058-af578f3b4515","orcid":"0000-0001-8974-2542"},{"last_name":"Sarac","full_name":"Sarac, Naci E","first_name":"Naci E","id":"8C6B42F8-C8E6-11E9-A03A-F2DCE5697425"}],"scopus_import":"1","oa_version":"Published Version","conference":{"location":"Liverpool, United Kingdom","name":"CONCUR: Conference on Concurrency Theory","end_date":"2026-09-04","start_date":"2026-09-01"},"acknowledgement":"This work has been supported by the European Research Council under Grant No.: ERC2020-AdG 101020093 and ERC-2021-AdG 101055412.\r\nFilip Cano: ERC-2020-AdG 101020093\r\nThomas A. Henzinger: ERC-2020-AdG 101020093\r\nKonstantin Kueffner: ERC-2020-AdG 101020093\r\nN. Ege Saraç: ERC-2021-AdG 101055412","dataavailabilitystatement":"Software (Source Code): https://github.com/filipcano/monitoringdiscounted-sum-properties [10]\r\narchived at swh:1:dir:cb99396415f279c985cd05206b44320227f64245\r\n","_id":"22921","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","corr_author":"1","researchdata_availability":"no","publication_status":"published","citation":{"ama":"Cano Cordoba F, Henzinger TA, Kueffner K, Sarac NE. Monitoring discounted sum properties. In: <i>37th International Conference on Concurrency Theory</i>. Vol 391. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2026. doi:<a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2026.22\">10.4230/LIPIcs.CONCUR.2026.22</a>","short":"F. Cano Cordoba, T.A. Henzinger, K. Kueffner, N.E. Sarac, in:, 37th International Conference on Concurrency Theory, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2026.","mla":"Cano Cordoba, Filip, et al. “Monitoring Discounted Sum Properties.” <i>37th International Conference on Concurrency Theory</i>, vol. 391, 22:1-22:19, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2026, doi:<a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2026.22\">10.4230/LIPIcs.CONCUR.2026.22</a>.","chicago":"Cano Cordoba, Filip, Thomas A Henzinger, Konstantin Kueffner, and Naci E Sarac. “Monitoring Discounted Sum Properties.” In <i>37th International Conference on Concurrency Theory</i>, Vol. 391. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2026. <a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2026.22\">https://doi.org/10.4230/LIPIcs.CONCUR.2026.22</a>.","ieee":"F. Cano Cordoba, T. A. Henzinger, K. Kueffner, and N. E. Sarac, “Monitoring discounted sum properties,” in <i>37th International Conference on Concurrency Theory</i>, Liverpool, United Kingdom, 2026, vol. 391.","apa":"Cano Cordoba, F., Henzinger, T. A., Kueffner, K., &#38; Sarac, N. E. (2026). Monitoring discounted sum properties. In <i>37th International Conference on Concurrency Theory</i> (Vol. 391). Liverpool, United Kingdom: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. <a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2026.22\">https://doi.org/10.4230/LIPIcs.CONCUR.2026.22</a>","ista":"Cano Cordoba F, Henzinger TA, Kueffner K, Sarac NE. 2026. Monitoring discounted sum properties. 37th International Conference on Concurrency Theory. CONCUR: Conference on Concurrency Theory, LIPIcs, vol. 391, 22:1-22:19."},"year":"2026","doi":"10.4230/LIPIcs.CONCUR.2026.22","ec_funded":1,"ddc":["000"],"quality_controlled":"1","keyword":["Runtime Verification","Probabilistic Systems","Quantitative Verification","Approximate Monitoring"],"intvolume":"       391","OA_type":"gold","publisher":"Schloss Dagstuhl - Leibniz-Zentrum für Informatik","alternative_title":["LIPIcs"],"file":[{"relation":"main_file","file_size":997156,"content_type":"application/pdf","date_created":"2026-09-22T05:59:03Z","date_updated":"2026-09-22T05:59:03Z","file_name":"2026_LIPIcsCONCUR_Cano.pdf","success":1,"access_level":"open_access","creator":"dernst","checksum":"f7b2e22428344fd7972c54f099df6aba","file_id":"22978"}],"supplementarymaterial":"no","article_number":"22:1-22:19","oa":1,"project":[{"call_identifier":"H2020","name":"Vigilant Algorithmic Monitoring of Software","grant_number":"101020093","_id":"62781420-2b32-11ec-9570-8d9b63373d4d"}],"das_tickbox":"1","OA_place":"publisher"},{"day":"06","date_updated":"2026-10-01T08:59:32Z","fulldoi":"https://doi.org/10.1093/bioadv/vbag182","abstract":[{"lang":"eng","text":"Linguistic inequality remains a silent barrier in contemporary science, particularly in rapidly evolving and interdisciplinary fields such as bioinformatics. This article examines how the Spanish-speaking community has responded to this gap through the creation of the Simposio de Estudiantes Hispanohablantes de Bioinformática y Biología Computacional (SEH2Bioinfo), a collective initiative that transforms language into a tool for inclusion and collaboration. Drawing on a historical review of the use of Spanish in scientific communication and an analysis of the two editions of SEH2Bioinfo (2022 and 2025), complemented by surveys of more than 1500 participants, we explore the effects of language on confidence, participation, and academic visibility. The findings show that Spanish can serve as a space for training and mentorship without compromising rigor, while simultaneously strengthening international networks and promoting open science. The growth of SEH2Bioinfo, its collaborative approach, and its intercontinental reach establish the symposium as a model for linguistic equity in scientific practice. Its experience demonstrates that expanding linguistic diversity in bioinformatics is not only possible but essential to building a global scientific community that is fairer, more connected, and representative."}],"has_accepted_license":"1","language":[{"iso":"eng"}],"month":"08","status":"public","department":[{"_id":"PaSc"},{"_id":"GradSch"}],"type":"journal_article","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"article_processing_charge":"Yes","DOAJ_listed":"1","date_created":"2026-09-17T11:06:17Z","volume":6,"date_published":"2026-08-06T00:00:00Z","file_date_updated":"2026-10-01T08:55:00Z","publication_identifier":{"eissn":["2635-0041"]},"title":"Bioinformatics in Español: Expanding open, diverse, and collaborative science through SEH2Bioinfo","oa_version":"Published Version","dataavailabilitystatement":"The data underlying this article, including the abstract books for\r\nthe first and second editions of the SEH2Bioinfo symposia, are\r\navailable in Zenodo at https://doi.org/10.5281/zenodo.6603621\r\nand https://doi.org/10.5281/zenodo.1,54,46,570, respectively.","_id":"22957","acknowledgement":"We acknowledge the sponsors who made the SEH2Bioinfo possible, the organizers from the various Spanish-speaking RSGs, and\r\nthe collaborators who contributed to dissemination, logistics,\r\nand other essential tasks for its execution. G.J.O.-O. thanks the\r\nFONDECYT Postdoctoral Project No. 3250793 for financial support. G.J.O.-O. also expresses gratitude to Valentina Luza: “May\r\nher passion for science communication keep inspiring new generations, myself included, to infinity and beyond!” R.G.P.\r\nthanks the Argentinian public university education system as an\r\nelement of social ascendance and democratization of professional opportunities.","scopus_import":"1","publication":"Bioinformatics Advances","author":[{"full_name":"Padilla Franzotti, Carla L","first_name":"Carla L","last_name":"Padilla Franzotti"},{"last_name":"Olguín-Orellana","first_name":"Gabriel J","full_name":"Olguín-Orellana, Gabriel J"},{"first_name":"Nicolas","full_name":"Palopoli, Nicolas","last_name":"Palopoli"},{"first_name":"Sebastián","full_name":"Urquiza-Zurich, Sebastián","last_name":"Urquiza-Zurich"},{"first_name":"Adrian","full_name":"Garcia-Moreno, Adrian","last_name":"Garcia-Moreno"},{"full_name":"Monzón, Sara","first_name":"Sara","last_name":"Monzón"},{"full_name":"Cabrera-Pasadas, Mónica","first_name":"Mónica","last_name":"Cabrera-Pasadas"},{"last_name":"Soler Sáez","full_name":"Soler Sáez, Irene","first_name":"Irene"},{"first_name":"Carla","full_name":"Perpiñá-Clérigues, Carla","last_name":"Perpiñá-Clérigues"},{"full_name":"Puche Quiñonez, Rafael J","last_name":"Puche Quiñonez","first_name":"Rafael J"},{"last_name":"Vélez Segura","full_name":"Vélez Segura, Jennifer","first_name":"Jennifer"},{"last_name":"Lovaco-Flores","full_name":"Lovaco-Flores, Jose Abel","first_name":"Jose Abel"},{"first_name":"Cleidy M","full_name":"Osorio Mogollón, Cleidy M","last_name":"Osorio Mogollón"},{"first_name":"Eva M","full_name":"Esquinas-Román, Eva M","last_name":"Esquinas-Román"},{"full_name":"Miserendino, Maria C","last_name":"Miserendino","first_name":"Maria C","id":"273e0cbd-72f0-11ef-b75a-f9f932e292fa"},{"last_name":"Eranti","first_name":"Pradeep","full_name":"Eranti, Pradeep"},{"full_name":"Castillo-Orozco, Ana","first_name":"Ana","last_name":"Castillo-Orozco"},{"first_name":"Yesid","full_name":"Cuesta-Astroz, Yesid","last_name":"Cuesta-Astroz"},{"full_name":"Parra, R Gonzalo","first_name":"R Gonzalo","last_name":"Parra"}],"external_id":{"pmid":["42577783"]},"researchdata_availability":"yes","citation":{"apa":"Padilla Franzotti, C. L., Olguín-Orellana, G. J., Palopoli, N., Urquiza-Zurich, S., Garcia-Moreno, A., Monzón, S., … Parra, R. G. (2026). Bioinformatics in Español: Expanding open, diverse, and collaborative science through SEH2Bioinfo. <i>Bioinformatics Advances</i>. Oxford University Press. <a href=\"https://doi.org/10.1093/bioadv/vbag182\">https://doi.org/10.1093/bioadv/vbag182</a>","ieee":"C. L. Padilla Franzotti <i>et al.</i>, “Bioinformatics in Español: Expanding open, diverse, and collaborative science through SEH2Bioinfo,” <i>Bioinformatics Advances</i>, vol. 6, no. 1. Oxford University Press, 2026.","ista":"Padilla Franzotti CL, Olguín-Orellana GJ, Palopoli N, Urquiza-Zurich S, Garcia-Moreno A, Monzón S, Cabrera-Pasadas M, Soler Sáez I, Perpiñá-Clérigues C, Puche Quiñonez RJ, Vélez Segura J, Lovaco-Flores JA, Osorio Mogollón CM, Esquinas-Román EM, Miserendino MC, Eranti P, Castillo-Orozco A, Cuesta-Astroz Y, Parra RG. 2026. Bioinformatics in Español: Expanding open, diverse, and collaborative science through SEH2Bioinfo. Bioinformatics Advances. 6(1), vbag182.","mla":"Padilla Franzotti, Carla L., et al. “Bioinformatics in Español: Expanding Open, Diverse, and Collaborative Science through SEH2Bioinfo.” <i>Bioinformatics Advances</i>, vol. 6, no. 1, vbag182, Oxford University Press, 2026, doi:<a href=\"https://doi.org/10.1093/bioadv/vbag182\">10.1093/bioadv/vbag182</a>.","chicago":"Padilla Franzotti, Carla L, Gabriel J Olguín-Orellana, Nicolas Palopoli, Sebastián Urquiza-Zurich, Adrian Garcia-Moreno, Sara Monzón, Mónica Cabrera-Pasadas, et al. “Bioinformatics in Español: Expanding Open, Diverse, and Collaborative Science through SEH2Bioinfo.” <i>Bioinformatics Advances</i>. Oxford University Press, 2026. <a href=\"https://doi.org/10.1093/bioadv/vbag182\">https://doi.org/10.1093/bioadv/vbag182</a>.","short":"C.L. Padilla Franzotti, G.J. Olguín-Orellana, N. Palopoli, S. Urquiza-Zurich, A. Garcia-Moreno, S. Monzón, M. Cabrera-Pasadas, I. Soler Sáez, C. Perpiñá-Clérigues, R.J. Puche Quiñonez, J. Vélez Segura, J.A. Lovaco-Flores, C.M. Osorio Mogollón, E.M. Esquinas-Román, M.C. Miserendino, P. Eranti, A. Castillo-Orozco, Y. Cuesta-Astroz, R.G. Parra, Bioinformatics Advances 6 (2026).","ama":"Padilla Franzotti CL, Olguín-Orellana GJ, Palopoli N, et al. Bioinformatics in Español: Expanding open, diverse, and collaborative science through SEH2Bioinfo. <i>Bioinformatics Advances</i>. 2026;6(1). doi:<a href=\"https://doi.org/10.1093/bioadv/vbag182\">10.1093/bioadv/vbag182</a>"},"publication_status":"published","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","quality_controlled":"1","ddc":["570"],"year":"2026","doi":"10.1093/bioadv/vbag182","file":[{"date_created":"2026-10-01T08:55:00Z","content_type":"application/pdf","file_size":1359968,"relation":"main_file","file_id":"23016","checksum":"8885b0531a655103c46899b2f935b0db","creator":"dernst","access_level":"open_access","success":1,"file_name":"2026_BioinformaticsAdvances_Franzotti.pdf","date_updated":"2026-10-01T08:55:00Z"}],"publisher":"Oxford University Press","issue":"1","OA_type":"gold","intvolume":"         6","related_material":{"link":[{"relation":"erratum","url":"https://doi.org/10.1093/bioadv/vbag271"}]},"oa":1,"das_tickbox":"1","OA_place":"publisher","article_number":"vbag182","supplementarymaterial":"no","article_type":"original","pmid":1},{"supervisor":[{"first_name":"Christoph","id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","full_name":"Lampert, Christoph","last_name":"Lampert","orcid":"0000-0001-8622-7887"}],"oa":1,"project":[{"name":"Bilateral Artificial Intelligence (Lampert)","grant_number":"COE12","_id":"d8f03aaa-b035-11f1-8588-d5147fa879e0"}],"related_material":{"record":[{"status":"public","id":"21207","relation":"part_of_dissertation"},{"relation":"part_of_dissertation","id":"20819","status":"public"},{"id":"17411","relation":"part_of_dissertation","status":"public"},{"relation":"part_of_dissertation","id":"18120","status":"public"}]},"OA_place":"publisher","publisher":"Institute of Science and Technology Austria","alternative_title":["ISTA Thesis"],"file":[{"date_created":"2026-02-17T11:46:22Z","content_type":"application/zip","relation":"source_file","file_size":272379252,"file_id":"21298","checksum":"121c1d968bd86f3630aa7e81d5bbbcb0","creator":"jscott","access_level":"closed","file_name":"2026_Scott_Jonathan_Thesis_Source.zip","date_updated":"2026-02-17T11:46:22Z"},{"date_created":"2026-02-27T10:25:41Z","content_type":"application/pdf","relation":"main_file","file_size":15220298,"file_id":"21366","checksum":"6e3e08ba474bbee8511cc8a839ab2077","creator":"jscott","access_level":"open_access","success":1,"file_name":"2026_Jonathan_Scott_Thesis.pdf","date_updated":"2026-02-27T10:25:41Z"}],"year":"2026","doi":"10.15479/AT-ISTA-21198","page":"158","ddc":["005"],"degree_awarded":"PhD","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","corr_author":"1","publication_status":"published","citation":{"short":"J.A. Scott, Data Heterogeneity and Personalization in Federated Learning, Institute of Science and Technology Austria, 2026.","ama":"Scott JA. Data heterogeneity and personalization in federated learning. 2026. doi:<a href=\"https://doi.org/10.15479/AT-ISTA-21198\">10.15479/AT-ISTA-21198</a>","chicago":"Scott, Jonathan A. “Data Heterogeneity and Personalization in Federated Learning.” Institute of Science and Technology Austria, 2026. <a href=\"https://doi.org/10.15479/AT-ISTA-21198\">https://doi.org/10.15479/AT-ISTA-21198</a>.","mla":"Scott, Jonathan A. <i>Data Heterogeneity and Personalization in Federated Learning</i>. Institute of Science and Technology Austria, 2026, doi:<a href=\"https://doi.org/10.15479/AT-ISTA-21198\">10.15479/AT-ISTA-21198</a>.","ista":"Scott JA. 2026. Data heterogeneity and personalization in federated learning. Institute of Science and Technology Austria.","apa":"Scott, J. A. (2026). <i>Data heterogeneity and personalization in federated learning</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT-ISTA-21198\">https://doi.org/10.15479/AT-ISTA-21198</a>","ieee":"J. A. Scott, “Data heterogeneity and personalization in federated learning,” Institute of Science and Technology Austria, 2026."},"author":[{"full_name":"Scott, Jonathan A","last_name":"Scott","id":"e499926b-f6e0-11ea-865d-9c63db0031e8","first_name":"Jonathan A"}],"oa_version":"Published Version","acknowledgement":"This research was funded in part by the Austrian Science Fund (FWF)\r\n[10.55776/COE12]. Furthermore, the candidate acknowledges the support from the Scientific\r\nService Units (SSU) of ISTA through resources provided by Scientific Computing (SciComp).","_id":"21198","title":"Data heterogeneity and personalization in federated learning","publication_identifier":{"issn":["2663-337X"]},"file_date_updated":"2026-02-27T10:25:41Z","date_published":"2026-02-09T00:00:00Z","date_created":"2026-02-09T14:59:53Z","article_processing_charge":"No","type":"dissertation","acknowledged_ssus":[{"_id":"ScienComp"}],"month":"02","language":[{"iso":"eng"}],"has_accepted_license":"1","status":"public","department":[{"_id":"GradSch"},{"_id":"ChLa"}],"day":"09","date_updated":"2026-10-01T09:29:03Z","abstract":[{"text":"In recent years there has been a massive increase in the amount of data generated in a\r\ndecentralized manner. Ever more powerful edge devices, such as smartphones, have become\r\nubiquitous in most societies on earth. Through text typed, photos taken and apps used,\r\nthese devices, which we refer to as clients, generate enormous amounts of high quality and\r\ncomplex data. Moreover, the nature of these devices means the data they generate is often\r\nsensitive and privacy concerns prevent it being gathered and stored in a central location. This\r\npresents a challenge to the modern machine learning paradigm that requires central access\r\nto large amounts of data. Federated learning (FL) has emerged as one of the answers to\r\nthis problem. Rather than bringing the data to the model, FL sends the model to the data.\r\nModel training takes place on device, with periodically synchronized updates, allowing data to\r\nremain locally stored. While this approach offers significant privacy advantages it comes with\r\nits own set of unique challenges. These include: data heterogeneity, the notion that different\r\ndevices generate data in distinct ways which can negatively impact training dynamics; systems\r\nheterogeneity, meaning that different devices may have differing hardware specifications; high\r\ncommunication costs, which are induced by the repeated transferring of models over the\r\nnetwork and low device computational power, which limits the use of larger models on device.\r\nIn this thesis we present a range of methods for federated learning. We focus primarily on\r\nthe challenge of data heterogeneity, though the methods presented are designed to be well\r\nadapted to the other challenges of a federated setting, such as the constraints of limited\r\ncompute and communication overhead. We first present a method for explicitly modeling client\r\ndata heterogeneity. The approach formulates clients as samples from a certain probability\r\ndistribution and infers the parameters of this distribution from the available training clients.\r\nThis learned distribution then represents the heterogeneity present among the clients and can\r\nbe sampled from in order to create new simulated clients that are similar to the real clients we\r\nhave observed so far. Following this we present two methods for directly dealing with data\r\nheterogeneity through personalization. Highly heterogeneous client data distributions can mean\r\nthat learning a single global model becomes suboptimal, and some form of personalization of\r\nmodels to each individual client is required. Our approaches are based around hypernetworks,\r\nwhich we use to generate personalized model parameters without the need for additional\r\ntraining or finetuning. In the first approach we focus on generating full parameterizations of\r\nclient models using learned embeddings of client data and labels, with a hypernetwork located\r\non the central server. In the second approach we address the more challenging scenario where\r\nwe want to generate a personalized model for a client without any label information. The\r\nhypernetwork is trained to generate a low dimensional representation of a client’s personalized\r\nmodel parameters, allowing it to be transferred to and run on the client devices. In our final\r\npresented method, we change our focus and rather than aim to directly address the challenge\r\nof data heterogeneity, we instead ensure we are unaffected by it. This is done in the context\r\nof k-means clustering and we present a method for federated clustering with a focus on added\r\nprivacy guarantees.","lang":"eng"}],"doi_confirm":"1","fulldoi":"https://doi.org/10.15479/AT-ISTA-21198"},{"oa_version":"Published Version","_id":"21854","acknowledgement":"The research in this Ph.D. was funded in whole\r\nor in part by the Austrian Science Fund (FWF) W1260-N35 (Vienna Graduate School for\r\nComputational Optimization). For open access purposes the author has applied a CC BY\r\npublic copyright license to any author accepted manuscript version arising from this submission\r\nwherever possible. Additionally, I am grateful to Alois Schlögl, Waleed Khalid, and the rest of\r\nthe ISTA Scientific Computing team for building and maintaining the infrastructure I used\r\nto run experiments. I’m also deeply grateful to the Alistarh group’s administrative assistant,\r\nChristine Francois, who always deals with our nonsense with common sense and a smile.\r\n","author":[{"full_name":"Iofinova, Eugenia B","last_name":"Iofinova","first_name":"Eugenia B","id":"f9a17499-f6e0-11ea-865d-fdf9a3f77117","orcid":"0000-0002-7778-3221"}],"date_published":"2026-05-11T00:00:00Z","file_date_updated":"2026-05-13T13:10:48Z","publication_identifier":{"issn":["2663-337X"]},"title":"On the utility and effects of efficiency in artificial neural networks","article_processing_charge":"No","type":"dissertation","date_created":"2026-05-11T08:43:22Z","day":"11","date_updated":"2026-10-01T09:32:47Z","fulldoi":"https://doi.org/10.15479/AT-ISTA-21854","doi_confirm":"1","abstract":[{"lang":"eng","text":"As neural-network-based models grow both in size and popularity, interest has grown in making the models smaller and more efficient to train. To that end, many methods have been proposed to prune models by reducing their number of nonzero parameters. Additionally, parameter-efficient fine-tuning, in which a much smaller number of parameters than the total contained in the model is updated during training, has become very popular, especially in the space of Large Language Models. At the same time, the increasingly routine deployment of machine learning in real-world applications has spurred a drive to make them more trustworthy - in the sense of, among other things, being unbiased, interpretable, and editable. In this thesis, we examine the interplay between efficiency and trustworthiness.\r\n\r\nFirst, we analyze the effects of model pruning on bias in computer vision models, demonstrating that increased sparsity leads to greater bias, largely as a function of increased model uncertainty in marginal cases. Based on this observation, we propose several bias mitigation techniques. Then, we demonstrate that example-specific model pruning can improve model interpretation methods while improving pruning efficiency to make example-specific model pruning feasible in real time. Then, we investigate the effectiveness of parameter-efficient and data-efficient model personalization via fine-tuning, demonstrating that it is highly feasible with very small computational and data resources. Finally, we consider efficiency in editing model knowledge using a custom synthetic data framework, demonstrating that parameter-efficient, low-rank fine-tuning frequently outperforms full-rank fine-tuning, and, additionally, that restricting which model blocks are fine-tuned frequently improves results. Together, the results in this thesis provide new insights and techniques for combining trustworthiness and efficiency during neural network inference and training.\r\n\r\n"}],"has_accepted_license":"1","language":[{"iso":"eng"}],"month":"05","acknowledged_ssus":[{"_id":"ScienComp"}],"department":[{"_id":"GradSch"},{"_id":"DaAl"}],"status":"public","project":[{"_id":"9B9290DE-BA93-11EA-9121-9846C619BF3A","grant_number":"W1260-N35","name":"Vienna Graduate School on Computational Optimization"}],"das_tickbox":"1","related_material":{"record":[{"relation":"part_of_dissertation","id":"14771","status":"public"},{"relation":"part_of_dissertation","id":"21858","status":"public"},{"status":"public","id":"21859","relation":"part_of_dissertation"},{"id":"21857","relation":"part_of_dissertation","status":"public"},{"id":"18121","relation":"part_of_dissertation","status":"public"}]},"oa":1,"supervisor":[{"first_name":"Dan-Adrian","full_name":"Alistarh, Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","last_name":"Alistarh","orcid":"0000-0003-3650-940X"}],"OA_place":"publisher","file":[{"date_updated":"2026-05-11T08:36:01Z","file_name":"EIofinova_thesis_FinalVersion.zip","creator":"eiofinov","access_level":"closed","file_id":"21856","checksum":"2e148dad920e3f9b7c32796e0ba2e5f7","file_size":28479571,"relation":"source_file","content_type":"application/zip","date_created":"2026-05-11T08:36:01Z"},{"date_updated":"2026-05-13T13:10:48Z","file_name":"2026_Iofinova_Eugenia_Thesis.pdf","creator":"eiofinov","access_level":"open_access","success":1,"file_id":"21877","checksum":"b10c2933f386f532b2dbf28b19c5525c","file_size":18137757,"relation":"main_file","content_type":"application/pdf","date_created":"2026-05-13T13:10:48Z"}],"alternative_title":["ISTA Thesis"],"publisher":"Institute of Science and Technology Austria","ddc":["000"],"degree_awarded":"PhD","page":"237","year":"2026","doi":"10.15479/AT-ISTA-21854","corr_author":"1","publisher_comment":"In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of ISTA's products or services. Internal or personal use of this material is permitted. If interested in reprinting/republishing IEEE copyrighted material for advertising or promotional purposes or for creating new collective works for resale or redistribution, please go to http://www.ieee.org/publications_standards/publications/rights/rights_link.html to learn how to obtain a License from RightsLink. If applicable, University Microfilms and/or ProQuest Library, or the Archives of Canada may supply single copies of the dissertation.","citation":{"apa":"Iofinova, E. B. (2026). <i>On the utility and effects of efficiency in artificial neural networks</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT-ISTA-21854\">https://doi.org/10.15479/AT-ISTA-21854</a>","ieee":"E. B. Iofinova, “On the utility and effects of efficiency in artificial neural networks,” Institute of Science and Technology Austria, 2026.","ista":"Iofinova EB. 2026. On the utility and effects of efficiency in artificial neural networks. Institute of Science and Technology Austria.","mla":"Iofinova, Eugenia B. <i>On the Utility and Effects of Efficiency in Artificial Neural Networks</i>. Institute of Science and Technology Austria, 2026, doi:<a href=\"https://doi.org/10.15479/AT-ISTA-21854\">10.15479/AT-ISTA-21854</a>.","chicago":"Iofinova, Eugenia B. “On the Utility and Effects of Efficiency in Artificial Neural Networks.” Institute of Science and Technology Austria, 2026. <a href=\"https://doi.org/10.15479/AT-ISTA-21854\">https://doi.org/10.15479/AT-ISTA-21854</a>.","short":"E.B. Iofinova, On the Utility and Effects of Efficiency in Artificial Neural Networks, Institute of Science and Technology Austria, 2026.","ama":"Iofinova EB. On the utility and effects of efficiency in artificial neural networks. 2026. doi:<a href=\"https://doi.org/10.15479/AT-ISTA-21854\">10.15479/AT-ISTA-21854</a>"},"publication_status":"published","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9"},{"OA_place":"publisher","related_material":{"record":[{"status":"public","relation":"dissertation_contains","id":"23005"}]},"oa":1,"article_number":"L053502","article_type":"letter_note","file":[{"success":1,"creator":"dernst","access_level":"open_access","checksum":"902cc8d177c8d3ae9cfe07c30375c9a9","file_id":"22014","date_updated":"2026-06-16T11:21:53Z","file_name":"2026_PhysicalReviewE_DiazMelian.pdf","date_created":"2026-06-16T11:21:53Z","relation":"main_file","file_size":3173197,"content_type":"application/pdf"}],"issue":"5","publisher":"American Physical Society","intvolume":"       113","OA_type":"hybrid","quality_controlled":"1","ddc":["530"],"year":"2026","doi":"10.1103/m7gr-2t6j","citation":{"ista":"Diaz Melian VL, Lenton IC, Binysh J, Souslov A, Waitukaitis SR. 2026. 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J.B. acknowledges funding from the European Union's Horizon research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 101106500.","oa_version":"Published Version","publication":"Physical Review E","author":[{"id":"b6798902-eea0-11ea-9cbc-a8e14286c631","full_name":"Diaz Melian, Vicente L","last_name":"Diaz Melian","first_name":"Vicente L"},{"orcid":"0000-0002-5010-6984","first_name":"Isaac C","id":"a550210f-223c-11ec-8182-e2d45e817efb","full_name":"Lenton, Isaac C","last_name":"Lenton"},{"first_name":"Jack","last_name":"Binysh","full_name":"Binysh, Jack"},{"first_name":"Anton","full_name":"Souslov, Anton","last_name":"Souslov"},{"first_name":"Scott R","last_name":"Waitukaitis","full_name":"Waitukaitis, Scott R","id":"3A1FFC16-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-2299-3176"}],"scopus_import":"1","external_id":{"arxiv":["2507.04982"]},"date_published":"2026-05-14T00:00:00Z","arxiv":1,"file_date_updated":"2026-06-16T11:21:53Z","publication_identifier":{"eissn":["2470-0053"],"issn":["2470-0045"]},"title":"Geometry of the vapor layer under a Leidenfrost hydrogel sphere","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"type":"journal_article","article_processing_charge":"Yes (via OA deal)","date_created":"2026-06-10T07:36:41Z","volume":113,"fulldoi":"https://doi.org/10.1103/m7gr-2t6j","abstract":[{"text":"A floating Leidenfrost droplet exhibits curvature inversion of its underside, due to the balance of vapor pressure and surface tension. Using interferometric imaging, we find different behavior for a levitated hydrogel sphere. Curvature inversion is observed briefly just after deposition, but quickly gives way to a steady state with no inversion. We show the essential role of vaporization in shaping the underbelly of the hydrogel, where changes due to direct mass loss are more significant than the balance of vapor pressure and elastic forces.","lang":"eng"}],"day":"14","date_updated":"2026-10-02T08:44:47Z","department":[{"_id":"ScWa"},{"_id":"GradSch"}],"status":"public","has_accepted_license":"1","acknowledged_ssus":[{"_id":"M-Shop"},{"_id":"ScienComp"}],"language":[{"iso":"eng"}],"month":"05"},{"date_created":"2026-09-28T17:40:23Z","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"type":"dissertation","article_processing_charge":"No","acknowledged_ssus":[{"_id":"M-Shop"}],"month":"09","language":[{"iso":"eng"}],"has_accepted_license":"1","department":[{"_id":"GradSch"},{"_id":"ScWa"}],"status":"public","day":"29","date_updated":"2026-10-02T08:44:47Z","abstract":[{"text":"When a Leidenfrost droplet floats on its own vapor layer, the interplay between vapor pressure, surface tension, and gravity determines its shape, and in the stable regime the underside of the droplet exhibits curvature inversion. Using interferometric imaging, we observe a different behavior for a levitated hydrogel sphere. Curvature inversion appears briefly after deposition, but the continuous vaporization process removes this feature, leading first to an oscillatory regime and eventually to a steady state without curvature inversion. We demonstrate the essential role of vaporization in shaping the hydrogel underbelly, where direct mass loss has a stronger influence than the balance between vapor pressure and elastic forces.","lang":"eng"}],"fulldoi":"https://doi.org/10.15479/AT-ISTA-23005","doi_confirm":"1","author":[{"id":"b6798902-eea0-11ea-9cbc-a8e14286c631","first_name":"Vicente L","last_name":"Diaz Melian","full_name":"Diaz Melian, Vicente L"}],"oa_version":"Published Version","_id":"23005","title":"The morphology underneath a levitated hydrogel sphere","publication_identifier":{"issn":["2663-337X"]},"file_date_updated":"2026-09-29T09:56:46Z","date_published":"2026-09-29T00:00:00Z","doi":"10.15479/AT-ISTA-23005","year":"2026","page":"114","ddc":["530","530","530"],"degree_awarded":"PhD","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","researchdata_availability":"yes","corr_author":"1","publication_status":"published","citation":{"mla":"Diaz Melian, Vicente L. <i>The Morphology underneath a Levitated Hydrogel Sphere</i>. 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","_id":"22981","title":"Genetic strategies enabling bacterial adaptation to selective pressures","publication_identifier":{"issn":["2663-337X"]},"file_date_updated":"2026-10-01T12:34:18Z","date_published":"2026-09-24T00:00:00Z"},{"PlanS_conform":"1","citation":{"apa":"Bauer, M., Ishida, S., &#38; Michor, P. W. (2026). Symplectic structures on the space of space curves. <i>Journal of Nonlinear Science</i>. Springer Nature. <a href=\"https://doi.org/10.1007/s00332-026-10266-8\">https://doi.org/10.1007/s00332-026-10266-8</a>","ieee":"M. Bauer, S. Ishida, and P. W. Michor, “Symplectic structures on the space of space curves,” <i>Journal of Nonlinear Science</i>, vol. 36, no. 2. Springer Nature, 2026.","ista":"Bauer M, Ishida S, Michor PW. 2026. Symplectic structures on the space of space curves. 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Our method integrates the Liouville 1-form of the Marsden–Weinstein structure with Riemannian structures that have been introduced in mathematical shape analysis. We also derive Hamiltonian vector fields for several classical Hamiltonian functions with respect to these new symplectic structures.","lang":"eng"}],"has_accepted_license":"1","month":"04","language":[{"iso":"eng"}],"status":"public","department":[{"_id":"GradSch"},{"_id":"ChWo"}],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"type":"journal_article","article_processing_charge":"Yes (via OA deal)","volume":36,"date_created":"2026-04-16T07:29:17Z","arxiv":1,"date_published":"2026-04-15T00:00:00Z","file_date_updated":"2026-04-28T09:55:32Z","publication_identifier":{"issn":["0938-8974"],"eissn":["1432-1467"]},"title":"Symplectic structures on the space of space curves","oa_version":"Published Version","_id":"21743","acknowledgement":"The authors are grateful to Boris Khesin for valuable comments on the MW symplectic structure and S. Ishida thanks Albert Chern for insightful discussions on space curves and Chris Wojtan for his continuous support. M. Bauer was partially supported by NSF grant DMS-1953244 and by the Binational Science Foundation (BSF). S. Ishida was partially supported by ERC Consolidator Grant 101045083 “CoDiNA” funded by the European Research Council. Some figures were generated by the software Houdini and its education license was provided by SideFX. 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This convergence result does not require any regularity assumption on the measures, though experiments suggest that the rate is not sharp. Via an analysis of the duality gap we also obtain the convergence rates for the gradient of the optimal potentials and the velocity field under mild regularity assumptions. To obtain such rates we discretize the dual formulation of the dynamic optimal transport problem and use the mature literature related to the error due to discretizing the Hamilton-Jacobi equation."}],"has_accepted_license":"1","language":[{"iso":"eng"}],"month":"02","department":[{"_id":"GradSch"},{"_id":"ChWo"}],"status":"public","oa_version":"Published Version","_id":"14703","acknowledgement":"The authors would like to thank Chris Wojtan for his continuous support and several interesting discussions. Part of this research was performed during two visits: one of SI to the BIDSA research center at Bocconi University, and one of HL to the Institute of Science and Technology Austria. Both host institutions are warmly acknowledged for the hospitality. HL is partially supported by the MUR-Prin 2022-202244A7YL “Gradient Flows and Non-Smooth Geometric Structures with Applications to Optimization and Machine Learning”, funded by the European Union - Next Generation EU. SI is supported in part by ERC Consolidator Grant 101045083 “CoDiNA” funded by the European Research Council. Open access funding provided by Institute of Science and Technology (IST Austria).","scopus_import":"1","author":[{"orcid":"0000-0002-3121-3100","last_name":"Ishida","id":"6F7C4B96-A8E9-11E9-A7CA-09ECE5697425","first_name":"Sadashige","full_name":"Ishida, Sadashige"},{"full_name":"Lavenant, Hugo","last_name":"Lavenant","first_name":"Hugo"}],"publication":"Foundations of Computational Mathematics","external_id":{"arxiv":["2312.12213"],"isi":["001352503300001"]},"date_published":"2026-02-01T00:00:00Z","arxiv":1,"file_date_updated":"2026-07-23T05:37:52Z","publication_identifier":{"issn":["1615-3375"],"eissn":["1615-3383"]},"title":"Quantitative convergence of a discretization of dynamic optimal transport using the dual formulation","quality_controlled":"1","ddc":["000"],"page":"349-384","doi":"10.1007/s10208-024-09686-3","year":"2026","PlanS_conform":"1","researchdata_availability":"no","corr_author":"1","citation":{"ama":"Ishida S, Lavenant H. Quantitative convergence of a discretization of dynamic optimal transport using the dual formulation. <i>Foundations of Computational Mathematics</i>. 2026;26:349-384. doi:<a href=\"https://doi.org/10.1007/s10208-024-09686-3\">10.1007/s10208-024-09686-3</a>","short":"S. Ishida, H. Lavenant, Foundations of Computational Mathematics 26 (2026) 349–384.","ista":"Ishida S, Lavenant H. 2026. Quantitative convergence of a discretization of dynamic optimal transport using the dual formulation. Foundations of Computational Mathematics. 26, 349–384.","ieee":"S. Ishida and H. Lavenant, “Quantitative convergence of a discretization of dynamic optimal transport using the dual formulation,” <i>Foundations of Computational Mathematics</i>, vol. 26. Springer Nature, pp. 349–384, 2026.","apa":"Ishida, S., &#38; Lavenant, H. (2026). Quantitative convergence of a discretization of dynamic optimal transport using the dual formulation. <i>Foundations of Computational Mathematics</i>. 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It lays the foundation for subsequent developmental events, including gastrulation, germ layer specification, organogenesis, and the establishment of the overall body plan. Two major modes of cleavage exist in the animal kingdom: holoblastic (complete) and meroblastic (incomplete) cleavage. Because holoblastic cleavage resembles canonical cytokinesis, its biochemical and mechanical basis has been extensively studied — an annular contractile ring forms at the equator and constricts in a purse-string-like manner, leading to the complete separation of two daughter cells. In contrast, although meroblastic cleavage occurs widely across the animal kingdom (e.g. in fish, reptiles, birds, and cephalopod molluscs), its mechanical basis remains largely unclear. During meroblastic cleavage, the cytokinetic furrow forms only at one pole and does not traverse the entire embryo, raising the question of how cytokinesis proceeds in the absence of a closed contractile ring. Moreover, the resulting daughter cells are not fully separated from the underlying yolk compartment, and how these blastomeres are subsequently cellularised remains unknown. This thesis takes the zebrafish as a model organism to address both questions. The first part characterises the biochemical and mechanical mechanisms underlying non-canonical meroblastic cleavage, revealing a two-phase process in which actomyosin cable contraction and cadherin-mediated membrane adhesion act sequentially to drive furrow ingression and invagination. The second part sheds light on the spatiotemporal dynamics by which individual blastomeres become cellularised, and uncovers a previously unrecognised contribution of central blastomeres to the yolk syncytial layer."}],"fulldoi":"https://doi.org/10.15479/AT-ISTA-22804","doi_confirm":"1","day":"12","date_updated":"2026-10-05T08:56:10Z","author":[{"last_name":"Tong","id":"50F65CDC-AA30-11E9-A72B-8A12E6697425","full_name":"Tong, Xin","first_name":"Xin"}],"acknowledgement":"I gratefully acknowledge the NOMIS Stiftung (Project ID 5061.844, Cytoplasmic\r\nself-organization into cell-like compartments as a common guiding principle in\r\nearly animal development) for funding my doctoral studies.","_id":"22804","oa_version":"Published Version","title":"Towards a deeper understanding of meroblastic cleavage","publication_identifier":{"isbn":["978-3-99078-080-0"],"issn":["2663-337X"]},"file_date_updated":"2026-09-14T12:48:53Z","date_published":"2026-07-12T00:00:00Z","doi":"10.15479/AT-ISTA-22804","year":"2026","page":"121","degree_awarded":"PhD","ddc":["596","532","572"],"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","publication_status":"published","citation":{"short":"X. 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The Scientific Service Units (SSU) of ISTA supported this research through resources provided by the Electron Microscopy Facility (EMF), Juan Aguilera Servin from the Nanofabrication facility (NNF). Special acknowledgments to the Ibá\r\nez group for their fruitful discussions and insights. K.M. acknowledges the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 101034413 and PETRAIII at DESY for the synchrotron X-ray measurements under proposal No. I-20241048 EC. JL is a Serra Húnter Fellow and is grateful to the Academia Excellence program (Generalitat de Catalunya), project PID2024-156765OB-C21 funded by MICIU/AEI/10.13039/501100011033 and the European Regional Development Fund (FEDER), and María de Maeztu Units of Excellence Programme CEX2023-001300 M, funded by MCIN/AEI 10.13039/501100011033. VG and SD acknowledge the use of resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. Y.L. acknowledges funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 754411, the National Natural Science Foundation of China (NSFC) (Grants No. 22209034).","has_accepted_license":"1","language":[{"iso":"eng"}],"month":"09","acknowledged_ssus":[{"_id":"EM-Fac"},{"_id":"NanoFab"}],"status":"public","department":[{"_id":"MaIb"},{"_id":"GradSch"},{"_id":"NanoFab"}],"day":"22","date_updated":"2026-10-06T12:16:03Z","fulldoi":"https://doi.org/10.1021/acs.chemmater.6c01284","abstract":[{"text":"Alkali salts are widely used in solution processing, yet the corresponding cations are often assumed to remain in the liquid phase. Here, we show that alkali ions introduced during the solution synthesis of SnSe are retained through particle isolation and continue to influence the material during subsequent thermal processing, where they shape the evolution of the final polycrystalline material. Different SnSe powders were prepared using Li+, Na+, and K+ precursors, as well as tetramethylammonium (TMA+) precursors as a nonalkali reference for comparison, and all samples were consolidated under identical conditions. Although all three alkali ions were found in the matrix, at grain boundaries, and in segregated nanoscale regions, they partitioned differently and resulted in distinct grain sizes, defect distributions, and therefore transport properties. Li induced the strongest grain size heterogeneity and the lowest energy barriers, Na the best overall balance between carrier concentration and mobility, and K the broadest alkali-rich grain boundary regions along with the strongest interfacial penalty to charge carrier transport. These results show that residual alkali ions are not just remnants of solution synthesis but active determinants of microstructure and thermoelectric performance in SnSe.","lang":"eng"}],"date_created":"2026-09-21T10:33:48Z","volume":38,"article_processing_charge":"Yes (via OA deal)","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"type":"journal_article","publisher":"American Chemical Society","issue":"18","intvolume":"        38","OA_type":"hybrid","file":[{"date_updated":"2026-10-06T12:11:04Z","file_name":"2026_ChemistryMaterials_Fiedler.pdf","success":1,"access_level":"open_access","creator":"dernst","checksum":"15e7866ca4fd57f5526737945651a6f2","file_id":"23063","relation":"main_file","file_size":7461570,"content_type":"application/pdf","date_created":"2026-10-06T12:11:04Z"}],"supplementarymaterial":"yes","article_type":"original","pmid":1,"oa":1,"das_tickbox":"0","project":[{"_id":"9B8F7476-BA93-11EA-9121-9846C619BF3A","name":"HighTE: The Werner Siemens Laboratory for the High Throughput Discovery of Semiconductors for Waste Heat Recovery"},{"name":"IST-BRIDGE: International postdoctoral program","_id":"fc2ed2f7-9c52-11eb-aca3-c01059dda49c","grant_number":"101034413","call_identifier":"H2020"},{"call_identifier":"H2020","grant_number":"754411","_id":"260C2330-B435-11E9-9278-68D0E5697425","name":"ISTplus - Postdoctoral Fellowships"}],"OA_place":"publisher","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","PlanS_conform":"1","researchdata_availability":"no","corr_author":"1","citation":{"mla":"Fiedler, Christine, et al. “Alkali Ions Retained from Synthesis Govern Microstructure and Transport in Solution-Processed SnSe.” <i>Chemistry of Materials</i>, vol. 38, no. 18, American Chemical Society, 2026, pp. 9323–9332, doi:<a href=\"https://doi.org/10.1021/acs.chemmater.6c01284\">10.1021/acs.chemmater.6c01284</a>.","chicago":"Fiedler, Christine, Sharona Horta, Navita Jakhar, Krishnendu Maji, Tobias Kleinhanns, Jordi Llorca, Qi Wang, et al. “Alkali Ions Retained from Synthesis Govern Microstructure and Transport in Solution-Processed SnSe.” <i>Chemistry of Materials</i>. American Chemical Society, 2026. <a href=\"https://doi.org/10.1021/acs.chemmater.6c01284\">https://doi.org/10.1021/acs.chemmater.6c01284</a>.","ieee":"C. Fiedler <i>et al.</i>, “Alkali ions retained from synthesis govern microstructure and transport in solution-processed SnSe,” <i>Chemistry of Materials</i>, vol. 38, no. 18. American Chemical Society, pp. 9323–9332, 2026.","apa":"Fiedler, C., Horta, S., Jakhar, N., Maji, K., Kleinhanns, T., Llorca, J., … Ibáñez, M. (2026). Alkali ions retained from synthesis govern microstructure and transport in solution-processed SnSe. <i>Chemistry of Materials</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acs.chemmater.6c01284\">https://doi.org/10.1021/acs.chemmater.6c01284</a>","ista":"Fiedler C, Horta S, Jakhar N, Maji K, Kleinhanns T, Llorca J, Wang Q, Ramon MG, Das S, Gavini V, Liu Y, Ibáñez M. 2026. Alkali ions retained from synthesis govern microstructure and transport in solution-processed SnSe. Chemistry of Materials. 38(18), 9323–9332.","ama":"Fiedler C, Horta S, Jakhar N, et al. Alkali ions retained from synthesis govern microstructure and transport in solution-processed SnSe. <i>Chemistry of Materials</i>. 2026;38(18):9323–9332. doi:<a href=\"https://doi.org/10.1021/acs.chemmater.6c01284\">10.1021/acs.chemmater.6c01284</a>","short":"C. Fiedler, S. Horta, N. Jakhar, K. Maji, T. Kleinhanns, J. Llorca, Q. Wang, M.G. Ramon, S. Das, V. Gavini, Y. Liu, M. Ibáñez, Chemistry of Materials 38 (2026) 9323–9332."},"publication_status":"published","page":"9323–9332","ec_funded":1,"doi":"10.1021/acs.chemmater.6c01284","year":"2026","quality_controlled":"1","ddc":["540"]}]