@phdthesis{21854,
  abstract     = {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.

First, 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.

},
  author       = {Iofinova, Eugenia B},
  issn         = {2663-337X},
  pages        = {237},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{On the utility and effects of efficiency in artificial neural networks}},
  doi          = {10.15479/AT-ISTA-21854},
  year         = {2026},
}

@unpublished{21859,
  abstract     = {As artificial neural networks, and specifically large language models, have improved rapidly in capabilities and quality, they have increasingly been deployed in real-world applications, from customer service to Google search, despite the fact that they frequently make factually incorrect or undesirable statements. This trend has inspired practical and academic interest in model editing, that is, in adjusting the weights of the model to modify its likely outputs for queries relating to a specific fact or set of facts. This may be done either to amend a fact or set of facts, for instance, to fix a frequent error in the training data, or to suppress a fact or set of facts entirely, for instance, in case of dangerous knowledge. Multiple methods have been proposed to do such edits. However, at the same time, it has been shown that such model editing can be brittle and incomplete. Moreover the effectiveness of any model editing method necessarily depends on the data on which the model is trained, and, therefore, a good understanding of the interaction of the training data distribution and the way it is stored in the network is necessary and helpful to reliably perform model editing. However, working with large language models trained on real-world data does not allow us to understand this relationship or fully measure the effects of model editing. We therefore propose Behemoth, a fully synthetic data generation framework. To demonstrate the practical insights from the framework, we explore model editing in the context of simple tabular data, demonstrating surprising findings that, in some cases, echo real-world results, for instance, that in some cases restricting the update rank results in a more effective update.},
  author       = {Iofinova, Eugenia B and Alistarh, Dan-Adrian},
  booktitle    = {arXiv},
  title        = {{Behemoth: Benchmarking unlearning in LLMs using fully synthetic data}},
  doi          = {10.48550/arXiv.2601.23153},
  year         = {2026},
}

@article{20847,
  abstract     = {We report on an experimental active matter system with motion restricted to four cardinal directions. Our particles are magnetite-doped colloidal spheres driven by the Quincke electrorotational instability. The absence of a magnetic field (|𝑩|=0) leads to circular trajectories interspersed with short spontaneous runs. Intermediate fields (|𝑩|≲20mT) linearize the motion along the axis perpendicular to 𝑩. At high magnetic fields, we observe the surprising emergence of a second, distinct linearization along the axis parallel to 𝑩. With numerical simulations, we show that this behavior can be explained by anisotropic magnetic susceptibility.},
  author       = {Fitzgerald, Eavan and Clavaud, Cécile and Das, Debasish and Lenton, Isaac C and Waitukaitis, Scott R},
  issn         = {2470-0053},
  journal      = {Physical Review E},
  number       = {6},
  publisher    = {American Physical Society},
  title        = {{Rolling at right angles: Magnetic anisotropy enables dual-anisotropic active matter}},
  doi          = {10.1103/1ss8-31rb},
  volume       = {112},
  year         = {2025},
}

@inproceedings{21327,
  abstract     = {Proteins exist as a dynamic ensemble of multiple conformations, and these motions are often crucial for their functions. However, current structure prediction methods predominantly yield a single conformation, overlooking the conformational heterogeneity revealed by diverse experimental modalities. Here, we present a framework for building experiment-grounded protein structure generative models that infer conformational ensembles consistent with measured experimental data. The key idea is to treat stateof-the-art protein structure predictors (e.g., AlphaFold3) as sequence-conditioned structural priors, and cast ensemble modeling as posterior inference of protein structures given experimental measurements. Through extensive real-data experiments, we demonstrate the generality of our method to incorporate a variety of experimental measurements. In particular, our framework uncovers previously unmodeled conformational heterogeneity from crystallographic densities, and generates high-accuracy NMR ensembles orders of magnitude faster than the status quo. Notably, we demonstrate that our ensembles outperform AlphaFold3 (Abramson et al., 2024) and sometimes better fit experimental data than publicly deposited structures to the Protein Data Bank (PDB, Burley et al. (2017)). We believe that this approach will unlock building predictive models that fully embrace experimentally observed conformational diversity.},
  author       = {Maddipatla, Sai A and Sellam, Nadav E and Bojan, Meital I and Vedula, Sanketh and Schanda, Paul and Marx, Ailie and Bronstein, Alexander},
  booktitle    = {Proceedings of the 42nd International Conference on Machine Learning},
  issn         = {2640-3498},
  location     = {Vancouver, Canada},
  pages        = {42366 -- 42393},
  publisher    = {ML Research Press},
  title        = {{Inverse problems with experiment-guided AlphaFold}},
  volume       = {267},
  year         = {2025},
}

@article{18605,
  abstract     = {The response of clouds and moist-convective processes to heat loss to space by long-wave radiative cooling is an important feedback in the Earth's atmosphere. It is known that moist convection increases roughly in equilibrium with radiative cooling, an assumption often made in simplified models of the tropical atmosphere. In this study, we use an idealised two-dimensional model of the atmosphere introduced by Vallis et. al. and incorporate a bulk-cooling term, which is an idealisation of radiative cooling in the atmosphere. We comment briefly on the static stability of the system to dry and moist convection and characteris its moist convective response to changes in the bulk cooling. We find that, while the clear-sky regions of the model respond directly to the change in the cooling term, the regions dominated by moist convective plumes are insensitive to changes in cooling. Similar to previous findings from cloud-resolving models, we too find in our idealised setting that the majority of the increase in convection occurs via an increase in the areal coverage of convection, rather than its intensity. We argue that these small-scale convective processes are an upper bound on how quickly convective intensity can change to stay in equilibrium with radiative cooling.},
  author       = {Agasthya, Lokahith N and Muller, Caroline J and Cheve, Mathis},
  issn         = {1477-870X},
  journal      = {Quarterly Journal of the Royal Meteorological Society},
  number       = {766},
  publisher    = {Wiley},
  title        = {{Moist convective scaling: Insights from an idealised model}},
  doi          = {10.1002/qj.4902},
  volume       = {151},
  year         = {2025},
}

@misc{18697,
  abstract     = {The information-processing capability of the brain’s cellular network depends on the physical wiring pattern between neurons and their molecular and functional characteristics. Mapping neurons and resolving their individual synaptic connections can be achieved by volumetric imaging at nanoscale resolution with dense cellular labelling. Light microscopy is uniquely positioned to visualize specific molecules but dense, synapse-level circuit reconstruction by light microscopy has been out of reach due to limitations in resolution, contrast, and volumetric imaging capability. Here we developed light-microscopy based connectomics (LICONN). We integrated specifically engineered hydrogel embedding and expansion with comprehensive deep-learning based segmentation and analysis of connectivity, thus directly incorporating molecular information in synapse-level brain tissue reconstructions. LICONN will allow synapse-level brain tissue phenotyping in biological experiments in a readily adoptable manner.},
  author       = {Danzl, Johann G and Lyudchik, Julia and Kreuzinger, Caroline},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Light-microscopy based connectomic reconstruction of mammalian brain tissue}},
  doi          = {10.15479/AT:ISTA:18697},
  year         = {2025},
}

@misc{18712,
  abstract     = {This file contains the code associated with the manuscript 'Effect of assortative mating and sexual selection on polygenic barriers to gene flow'. },
  author       = {Surendranadh, Parvathy and Sachdeva, Himani},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Mathematica notebook and Fortran code for 'Effect of assortative mating and sexual selection on polygenic barriers to gene flow'}},
  doi          = {10.15479/AT:ISTA:17344},
  year         = {2025},
}

@article{18778,
  abstract     = {Transcription by RNA polymerase II (Pol II) can be repressed by noncoding RNA, including the human RNA Alu. However, the mechanism by which endogenous RNAs repress transcription remains unclear. Here we present cryogenic-electron microscopy structures of Pol II bound to Alu RNA, which reveal that Alu RNA mimics how DNA and RNA bind to Pol II during transcription elongation. Further, we show how distinct domains of the general transcription factor TFIIF control repressive activity. Together, we reveal how a noncoding RNA can regulate mammalian gene expression.},
  author       = {Tluckova, Katarina and Kaczmarek, Beata M and Testa Salmazo, Anita P and Bernecky, Carrie A},
  issn         = {1545-9985},
  journal      = {Nature Structural & Molecular Biology},
  pages        = {607--612},
  publisher    = {Springer Nature},
  title        = {{Mechanism of mammalian transcriptional repression by noncoding RNA}},
  doi          = {10.1038/s41594-024-01448-7},
  volume       = {32},
  year         = {2025},
}

@article{18879,
  abstract     = {Our brain has remarkable computational power, generating sophisticated behaviors, storing memories over an individual’s lifetime, and producing higher cognitive functions. However, little of our neuroscience knowledge covers the human brain. Is this organ truly unique, or is it a scaled version of the extensively studied rodent brain? Combining multicellular patch-clamp recording with expansion-based superresolution microscopy and full-scale modeling, we determined the cellular and microcircuit properties of the human hippocampal CA3 region, a fundamental circuit for memory storage. In contrast to neocortical networks, human hippocampal CA3 displayed sparse connectivity, providing a circuit architecture that maximizes associational power. Human synapses showed unique reliability, high precision, and long integration times, exhibiting both species- and circuit-specific properties. Together with expanded neuronal numbers, these circuit characteristics greatly enhanced the memory storage capacity of CA3. Our results reveal distinct microcircuit properties of the human hippocampus and begin to unravel the inner workings of our most complex organ. },
  author       = {Watson, Jake and Vargas Barroso, Victor M and Morse, Rebecca and Navas Olivé, Andrea C and Tavakoli, Mojtaba and Danzl, Johann G and Tomschik, Matthias and Rössler, Karl and Jonas, Peter M},
  issn         = {1097-4172},
  journal      = {Cell},
  number       = {2},
  pages        = {501--514.e18},
  publisher    = {Elsevier},
  title        = {{Human hippocampal CA3 uses specific functional connectivity rules for efficient associative memory}},
  doi          = {10.1016/j.cell.2024.11.022},
  volume       = {188},
  year         = {2025},
}

@article{19076,
  abstract     = {For accurate perception and motor control, an animal must distinguish between sensory experiences elicited by external stimuli and those elicited by its own actions. The diversity of behaviors and their complex influences on the senses make this distinction challenging. Here, we uncover an action–cue hub that coordinates motor commands with visual processing in the brain’s first visual relay. We show that the ventral lateral geniculate nucleus (vLGN) acts as a corollary discharge center, integrating visual translational optic flow signals with motor copies from saccades, locomotion and pupil dynamics. The vLGN relays these signals to correct action-specific visual distortions and to refine perception, as shown for the superior colliculus and in a depth-estimation task. Simultaneously, brain-wide vLGN projections drive corrective actions necessary for accurate visuomotor control. Our results reveal an extended corollary discharge architecture that refines early visual transformations and coordinates actions via a distributed hub-and-spoke network to enable visual perception during action.},
  author       = {Vega Zuniga, Tomas A and Sumser, Anton L and Symonova, Olga and Koppensteiner, Peter and Schmidt, Florian and Jösch, Maximilian A},
  issn         = {1546-1726},
  journal      = {Nature Neuroscience},
  publisher    = {Springer Nature},
  title        = {{A thalamic hub-and-spoke network enables visual perception during action by coordinating visuomotor dynamics}},
  doi          = {10.1038/s41593-025-01874-w},
  volume       = {28},
  year         = {2025},
}

@article{19278,
  abstract     = {When two insulating, neutral materials are contacted and separated, they exchange electrical charge1. Experiments have long suggested that this ‘contact electrification’ is transitive, with different materials ordering into ‘triboelectric series’ based on the sign of charge acquired2. At the same time, the effect is plagued by unpredictability, preventing consensus on the mechanism and casting doubt on the rhyme and reason that series imply3. Here we expose an unanticipated connection between the unpredictability and order in contact electrification: nominally identical materials initially exchange charge randomly and intransitively, but—over repeated experiments—order into triboelectric series. We find that this evolution is driven by the act of contact itself—samples with more contacts in their history charge negatively to ones with fewer contacts. Capturing this ‘contact bias’ in a minimal model, we recreate both the initial randomness and ultimate order in numerical simulations and use it experimentally to force the appearance of a triboelectric series of our choosing. With a set of surface-sensitive techniques to search for the underlying alterations contact creates, we only find evidence of nanoscale morphological changes, pointing to a mechanism strongly coupled with mechanics. Our results highlight the centrality of contact history in contact electrification and suggest that focusing on the unpredictability that has long plagued the effect may hold the key to understanding it.},
  author       = {Sobarzo Ponce, Juan Carlos A and Pertl, Felix and Balazs, Daniel and Costanzo, Tommaso and Sauer, Markus and Foelske, Annette and Ostermann, Markus and Pichler, Christian M. and Wang, Yongkang and Nagata, Yuki and Bonn, Mischa and Waitukaitis, Scott R},
  issn         = {1476-4687},
  journal      = {Nature},
  number       = {8051},
  publisher    = {Springer Nature},
  title        = {{Spontaneous ordering of identical materials into a triboelectric series}},
  doi          = {10.1038/s41586-024-08530-6},
  volume       = {638},
  year         = {2025},
}

@article{19404,
  abstract     = {Cell migration is a fundamental process during embryonic development. Most studies in vivo have focused on the migration of cells using the extracellular matrix (ECM) as their substrate for migration. In contrast, much less is known about how cells migrate on other cells, as found in early embryos when the ECM has not yet formed. Here, we show that lateral mesendoderm (LME) cells in the early zebrafish gastrula use the ectoderm as their substrate for migration. We show that the lateral ectoderm is permissive for the animal-pole-directed migration of LME cells, while the ectoderm at the animal pole halts it. These differences in permissiveness depend on the lateral ectoderm being more cohesive than the animal ectoderm, a property controlled by bone morphogenetic protein (BMP) signaling within the ectoderm. Collectively, these findings identify ectoderm tissue cohesion as one critical factor in regulating LME migration during zebrafish gastrulation.},
  author       = {Tavano, Ste and Brückner, David and Tasciyan, Saren and Tong, Xin and Kardos, Roland and Schauer, Alexandra and Hauschild, Robert and Heisenberg, Carl-Philipp J},
  issn         = {2211-1247},
  journal      = {Cell Reports},
  number       = {3},
  publisher    = {Elsevier},
  title        = {{BMP-dependent patterning of ectoderm tissue material properties modulates lateral mesendoderm cell migration during early zebrafish gastrulation}},
  doi          = {10.1016/j.celrep.2025.115387},
  volume       = {44},
  year         = {2025},
}

@phdthesis{19557,
  author       = {Schwarz, Lena A},
  issn         = {2663-337X},
  pages        = {124},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Mapping developmental dynamics of autism spectrum disorder mouse models at single-cell resolution}},
  doi          = {10.15479/AT-ISTA-19557},
  year         = {2025},
}

@article{19602,
  abstract     = {N4-methylcytosine (4mC) is an important DNA modification in prokaryotes, but its relevance and even its presence in eukaryotes have been mysterious. Here we show that spermatogenesis in the liverwort Marchantia polymorpha involves two waves of extensive DNA methylation reprogramming. First, 5-methylcytosine (5mC) expands from transposons to the entire genome. Notably, the second wave installs 4mC throughout genic regions, covering over 50% of CG sites in sperm. 4mC requires a methyltransferase (MpDN4MT1a) that is specifically expressed during late spermiogenesis. Deletion of MpDN4MT1a alters the sperm transcriptome, causes sperm swimming and fertility defects, and impairs post-fertilization development. Our results reveal extensive 4mC in a eukaryote, identify a family of eukaryotic methyltransferases, and elucidate the biological functions of 4mC in reproductive development, thereby expanding the repertoire of functional eukaryotic DNA modifications.},
  author       = {Walker, James and Zhang, Jingyi and Liu, Yalin and Xu, Shujuan and Yu, Yiming and Vickers, Martin and Ouyang, Weizhi and Tálas, Judit and Dolan, Liam and Nakajima, Keiji and Feng, Xiaoqi},
  issn         = {1097-4172},
  journal      = {Cell},
  number       = {11},
  pages        = {2890--2906.e14},
  publisher    = {Elsevier},
  title        = {{Extensive N4 cytosine methylation is essential for Marchantia sperm function}},
  doi          = {10.1016/j.cell.2025.03.014},
  volume       = {188},
  year         = {2025},
}

@misc{19623,
  abstract     = {Persistent revivals recently observed in Rydberg atom simulators have challenged our understanding of thermalization and attracted much interest to the concept of quantum many-body scars (QMBSs). QMBSs are non-thermal highly excited eigenstates that coexist with typical eigenstates in the spectrum of many-body Hamiltonians, and have since been reported in multiple theoretical models, including the so-called PXP model, approximately realized by Rydberg simulators. At the same time, questions of how common QMBSs are and in what models they are physically realized remain open. In this Letter, we demonstrate that QMBSs exist in a broader family of models that includes and generalizes PXP to longer-range constraints and states with different periodicity. We show that in each model, multiple QMBS families can be found. Each of them relies on a different approximate 𝔰𝔲⁡(2) algebra, leading to oscillatory dynamics in all cases. However, in contrast to the PXP model, their observation requires launching dynamics from weakly entangled initial states rather than from a product state. QMBSs reported here may be experimentally probed using Rydberg atom simulator in the regime of longer-range Rydberg blockades.},
  author       = {Desaules, Jean-Yves Marc},
  keywords     = {quantum many-body scars, non-equilibrium physics, Rydberg atoms},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Research Data for "Quantum Many-Body Scars beyond the PXP Model in Rydberg Simulators"}},
  doi          = {10.15479/AT:ISTA:19623},
  year         = {2025},
}

@phdthesis{19630,
  abstract     = {This thesis consists of three chapters, each corresponding to one publication. While each of these projects tackles a topic in a different area of research, they all share a common thread in the type of topological structure they handle - a partition of space into volumes separated by interfaces that meet in non-manifold junctions.

In Chapter 2, we study clusters of soap bubbles from a simulation perspective. In particular, we develop a surface-only algorithm that couples large scale motion and shape deformation of soap bubble clusters with the small scale evolution of the thin film's thickness, which is responsible for visual phenomena like surface vortices, Newton's interference patterns, capillary waves, and deformation-dependent rupturing of films in a foam. We model film thickness as a reduced degree of freedom in the Navier-Stokes equations and from them derive three sets of equations governing normal and tangential motion of the soap film surface, as well as the evolution of the thin film thickness. We discretize these equations on a non-manifold triangle mesh, extending and adapting operators to handle complex topology. We also present an incompressible fluid solver for 2.5D films and an advection algorithm for convecting fields across non-manifold surface junctions. Our simulations enhance bubble solvers with additional effects caused by convection, rippling, draining, and evaporation of the thin film.

In Chapter 3, we introduce a multi-material non-manifold mesh-based surface tracking algorithm that converts mesh defects, such as overlaps, self-intersections, and inversions into topological changes. Our algorithm generalizes prior work on manifold surface tracking with topological changes: it preserves surface features like mesh-based methods, and it robustly handles topological changes like level set methods. Our method also offers improved efficiency and robustness over the state of the art. We demonstrate the effectiveness of the approach on a range of examples, including complex soap film simulations, such as those presented in Chapter 2, but with an order of magnitude more interacting bubbles than what we could achieve before, and Boolean unions of non-manifold meshes consisting of millions of triangles.

Lastly, in Chapter 4, we utilize developments in the theory of random geometric complexes facilitated by observations from Discrete Morse theory. We survey the methods and results obtained with this new approach, and discuss some of its shortcomings. We use simulations to illustrate the results and to form conjectures, getting numerical estimates for combinatorial, topological, and geometric properties of weighted and unweighted Delaunay mosaics, their dual Voronoi tessellations, and the Alpha and Wrap complexes contained in the mosaics.},
  author       = {Synak, Peter},
  issn         = {2663-337X},
  pages        = {106},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Methods for fluid simulation, surface tracking, and statistics of non-manifold structures}},
  doi          = {10.15479/AT-ISTA-19630},
  year         = {2025},
}

@phdthesis{19684,
  abstract     = {The overarching goal of this thesis is to break down the complexity of turbulent flows in terms of enumerable, coherent structures and patterns. In a five-paper series, we adopt a variety of perspectives and techniques to relate the properties of systems of increasing complexity to their underlying coherent structures. 

Initially, we take a dynamical systems point of view, seeing turbulent flow as a chaotic trajectory bouncing between exact unstable solutions of the underlying equations of motion. Using persistent homology, the main tool of topological data analysis capturing the persistence across scales of topological features in a point cloud, we introduce a method that quantifies visits of turbulent trajectories to unstable time-periodic solutions, also called periodic orbits. We demonstrate this method first in the Rössler and Kuramoto–Sivashinsky systems. Using this method in 3D Kolmogorov flow, we extract a Markov chain from turbulent data, where each node corresponds to the neighbourhood of a periodic orbit. The invariant distribution of this Markov chain reproduces expectation values on turbulent data when it is used to weight averages on the respective periodic orbits.

In more realistic, wall-bounded settings, such as plane-Couette flow (pcf) driven by the relative motion of the walls, or plane-Poiseuille flow (ppf) driven by a pressure gradient, finding exact solutions is difficult. We use dynamic mode decomposition (DMD), a dimensionality reduction method for sequential data, to identify and approximate low-dimensional dynamics without knowing any exact solutions. Most spatially-extended systems are equivariant under translations, and in such cases spatial drifts dominate DMD, hindering its use in the search for and modelling of low-dimensional dynamics. We augment DMD with a symmetry reduction method trained on turbulent data to stop it from seeing translations as a feature, improving its ability to extract dynamical information in translation-equivariant systems. We find segments of turbulent trajectories that linearize well with their symmetry-reduced DMD spectra, akin to dynamics near exact solutions. Searching for harmonics in the spectra gives leads for periodic orbits with spatial drifts, one of which converges to a new solution.

In larger domains, turbulence can localize and coexist with surrounding laminar flow. Our preceding approaches are global, taking all of a domain into account at once, and cannot readily treat each localized patch individually. Working first in a minimal oblique domain that can host a single 1D-localized turbulent patch, we find that turbulence in ppf is connected to a stable periodic orbit at a flow velocity much lower than when turbulence is first onset. We show that, well in advance of sustained turbulence, chaos sets in explosively, and for long time horizons, time series are consistent with that of a random process.

Finally, in much larger domains, we study and compare 2D-localized turbulence that appears as large-scale inclined structures, called stripes, in ppf and pcf. While appearing similar, we find that stripes in these two settings differ significantly in terms of how they sustain themselves, and in higher velocities, how they proliferate.},
  author       = {Yalniz, Gökhan},
  issn         = {2663-337X},
  pages        = {155},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Transition to turbulence : Data-, solution-, and pattern-driven approaches}},
  doi          = {10.15479/AT-ISTA-19684},
  year         = {2025},
}

@article{19704,
  abstract     = {The information-processing capability of the brain’s cellular network depends on the physical wiring pattern between neurons and their molecular and functional characteristics. Mapping neurons and resolving their individual synaptic connections can be achieved by volumetric imaging at nanoscale resolution1,2 with dense cellular labelling. Light microscopy is uniquely positioned to visualize specific molecules, but dense, synapse-level circuit reconstruction by light microscopy has been out of reach, owing to limitations in resolution, contrast and volumetric imaging capability. Here we describe light-microscopy-based connectomics (LICONN). We integrated specifically engineered hydrogel embedding and expansion with comprehensive deep-learning-based segmentation and analysis of connectivity, thereby directly incorporating molecular information into synapse-level reconstructions of brain tissue. LICONN will allow synapse-level phenotyping of brain tissue in biological experiments in a readily adoptable manner.},
  author       = {Tavakoli, Mojtaba and Lyudchik, Julia and Januszewski, Michał and Vistunou, Vitali and Agudelo Duenas, Nathalie and Vorlaufer, Jakob and Sommer, Christoph M and Kreuzinger, Caroline and Oliveira, Bárbara and Cenameri, Alban and Novarino, Gaia and Jain, Viren and Danzl, Johann G},
  issn         = {1476-4687},
  journal      = {Nature},
  pages        = {398--410},
  publisher    = {Springer Nature},
  title        = {{Light-microscopy-based connectomic reconstruction of mammalian brain tissue}},
  doi          = {10.1038/s41586-025-08985-1},
  volume       = {642},
  year         = {2025},
}

@article{19876,
  abstract     = {Assortative mating and sexual selection are widespread in nature and can play an important role in speciation by facilitating the buildup and maintenance of reproductive isolation (RI). However, their contribution to genome-wide suppression of gene flow during RI is rarely quantified.
Here, we consider a polygenic “magic” trait that is divergently selected across two populations connected by migration, while also serving as the basis of assortative mating, thus generating sexual selection on one or both sexes. We obtain theoretical predictions for divergence at
individual trait loci by assuming that the effect of all other loci on any locus can be encapsulated via an effective migration rate, which bears a simple relationship to measurable fitness components of migrants and various early-generation hybrids. Our analysis clarifies how “tipping
points” (characterized by an abrupt collapse of adaptive divergence) arise, and when assortative mating can shift the critical level of migration beyond which divergence collapses. We quantify the relative contributions of viability and sexual selection to genome-wide barriers to gene
flow and discuss how these depend on existing divergence levels. Our results suggest that effective migration rates provide a useful way of understanding genomic divergence, even in scenarios involving multiple, interacting mechanisms of RI. },
  author       = {Surendranadh, Parvathy and Sachdeva, Himani},
  issn         = {1558-5646},
  journal      = {Evolution},
  number       = {7},
  pages        = {1185--1198},
  publisher    = {Oxford University Press},
  title        = {{Effect of assortative mating and sexual selection on polygenic barriers to gene flow}},
  doi          = {10.1093/evolut/qpaf047},
  volume       = {79},
  year         = {2025},
}

@article{20011,
  abstract     = {Heat transport in glasses over a wide temperature range is critical for applications in gate dielectrics and thermal insulators but remains poorly understood due to the challenges in modeling vibrational anharmonicity and configurational dynamics across the glass transition. Recent predictions show an unusual decrease in thermal conductivity (κ) with temperature in amorphous hafnia (a-HfO2), contrasting with the typical trend in glasses. Using molecular dynamics with a machine-learning-based neuroevolution potential, we compute κ of a-HfO2 from 50 K to 2000 K. At low temperatures, the Wigner transport equation captures both anharmonicity and quantum statistics. Above 1200 K, atomic diffusion invalidates the quasiparticle picture, and we resort to the Green–Kubo method to capture convective transport. We further extend the Wigner transport equation to supercooled a-HfO2, revealing the crucial role of low-frequency modes in facilitating heat transport. The computed κ, based on both Green–Kubo and Wigner transport theories, increases continuously with temperature up to 2000 K.},
  author       = {Zeng, Zezhu and Liang, Xia and Fan, Zheyong and Chen, Yue and Simoncelli, Michele and Cheng, Bingqing},
  issn         = {2639-4979},
  journal      = {ACS Materials Letters},
  pages        = {2695--2701},
  publisher    = {American Chemical Society},
  title        = {{Thermal transport of amorphous hafnia across the glass transition}},
  doi          = {10.1021/acsmaterialslett.5c00263},
  year         = {2025},
}