@article{17219,
  abstract     = {We introduce a multi-material non-manifold mesh-based surface tracking algorithm that converts self-intersections 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 with thousands of interacting bubbles, and boolean unions of non-manifold meshes consisting of millions of triangles.},
  author       = {Synak, Peter and Kalinov, Aleksei and Strugaru, Irina-Malina and Etemadihaghighi, Arian and Yang, Huidong and Wojtan, Christopher J},
  issn         = {1557-7368},
  journal      = {ACM Transactions on Graphics},
  keywords     = {surface tracking, topology change, non- manifold meshes, multi-material flows, solid modeling},
  number       = {4},
  publisher    = {Association for Computing Machinery},
  title        = {{Multi-material mesh-based surface tracking with implicit topology changes}},
  doi          = {10.1145/3658223},
  volume       = {43},
  year         = {2024},
}

@phdthesis{18301,
  abstract     = {Physics simulation in computer graphics can bring triangle meshes into topologically invalid states. The method in this thesis contributed to Heiss-Synak* and Kalinov* et al. [2024] who devised a non-manifold hybrid surface tracker—a surface tracker that repairs explicit non-manifold triangle meshes with the help of the implicit domain. Specifically, this thesis provides an algorithm for filling the holes that are left after removing problematic parts of the mesh.},
  author       = {Etemadihaghighi, Arian},
  issn         = {2791-4585},
  keywords     = {surface tracking, non-manifold, hole-filling, topology change, multi-material, solid-modeling},
  pages        = {39},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Filling the holes of non-manifold self-intersecting meshes for implicit topology changes in surface tracking}},
  doi          = {10.15479/at:ista:18301},
  year         = {2024},
}

@phdthesis{17368,
  abstract     = {Recent advancements in molecular diagnostic techniques have enabled the collection of
multiple types of omics data from patients, including genomics, epigenomics, proteomics,
and transcriptomics. However, we lack effective methods for integrating all these different
data types and combining them with clinical outcomes to study the molecular mechanisms
that govern pathological phenotypes. We present multi-omics BayesW, a penalized Bayesian
regression method that can handle general omics data for survival analysis of time-to-event
phenotypes. Our method can: (1) accommodate incomplete data by allowing censored
individuals, (2) use continuous time-to-event data to test associations of markers with a
phenotype and (3) estimate effects jointly while allowing for independent groups of biological
markers. Extensive simulations using planted signals on real data demonstrate that our model
accurately retrieves the true parameters of the model while controlling for false discoveries
and maintaining the expected prediction accuracy. We address data correlations by estimating
the effects jointly, even between omic groups, while also estimating the individual variance
explained by each group. We apply our model to two datasets. Using 18,000 individuals from
the Generation Scotland study we model the association of time at onset of Type 2 Diabetes,
Stroke, Ischemic Disease, and Osteoarthritis from baseline study entry, with 831,724 CpG
methylation probes. We find that large proportions of variation in disease onset times can
be attributed to methylation as measured in whole blood at baseline in individuals without
disease symptoms. We then apply our model to The Cancer Genome Atlas (TCGA) pan-cancer
dataset, in which we use 5 types of omics: copy number variation, epigenetics, somatic
mutations, miRNA, and gene expression. For cancer survival age-at-onset we find that, when
fitting the 5 groups together, almost all variation attributable to "omics" data is explained by
DNA methylation. When considering progression times, both methylation and gene expression
explain a large part of the variance. We found 2 genes that are significantly associated (95%
posterior inclusion probability) with cancer survival time, conditional on all other genome-wide
omics data variation. Owing to the vast variability of mechanisms characterizing different
cancers, there are likely few specific genes with a strong signal in a pan-cancer setting. Taken
together, we showed the applicability of our multi-omics BayesW model to a wide-range of
biological questions in multi-omics data.
},
  author       = {Villanueva Marijuan, Ariadna},
  issn         = {2791-4585},
  keywords     = {Epigenetics, Multi-omics, Bayesian regression},
  pages        = {60},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Bayesian linear regression for analyzing general omics data with time-to-event phenotypes}},
  doi          = {10.15479/at:ista:17368},
  year         = {2024},
}

@inproceedings{12976,
  abstract     = {3D printing based on continuous deposition of materials, such as filament-based 3D printing, has seen widespread adoption thanks to its versatility in working with a wide range of materials. An important shortcoming of this type of technology is its limited multi-material capabilities. While there are simple hardware designs that enable multi-material printing in principle, the required software is heavily underdeveloped. A typical hardware design fuses together individual materials fed into a single chamber from multiple inlets before they are deposited. This design, however, introduces a time delay between the intended material mixture and its actual deposition. In this work, inspired by diverse path planning research in robotics, we show that this mechanical challenge can be addressed via improved printer control. We propose to formulate the search for optimal multi-material printing policies in a reinforcement
learning setup. We put forward a simple numerical deposition model that takes into account the non-linear material mixing and delayed material deposition. To validate our system we focus on color fabrication, a problem known for its strict requirements for varying material mixtures at a high spatial frequency. We demonstrate that our learned control policy outperforms state-of-the-art hand-crafted algorithms.},
  author       = {Liao, Kang and Tricard, Thibault and Piovarci, Michael and Seidel, Hans-Peter and Babaei, Vahid},
  booktitle    = {2023 IEEE International Conference on Robotics and Automation},
  issn         = {1050-4729},
  keywords     = {reinforcement learning, deposition, control, color, multi-filament},
  location     = {London, United Kingdom},
  pages        = {12345--12352},
  publisher    = {IEEE},
  title        = {{Learning deposition policies for fused multi-material 3D printing}},
  doi          = {10.1109/ICRA48891.2023.10160465},
  volume       = {2023},
  year         = {2023},
}

@phdthesis{6435,
  abstract     = {Social insect colonies tend to have numerous members which function together like a single organism in such harmony that the term ``super-organism'' is often used. In this analogy the reproductive caste is analogous to the primordial germ
cells of a metazoan, while the sterile worker caste corresponds to somatic cells. The worker castes, like tissues, are
in charge of all functions of a living being, besides reproduction. The establishment of new super-organismal units
(i.e. new colonies) is accomplished by the co-dependent castes. The term oftentimes goes beyond a metaphor. We invoke it when we speak about the metabolic rate, thermoregulation, nutrient regulation and gas exchange of a social insect colony. Furthermore, we assert that the super-organism has an immune system, and benefits from ``social immunity''.

Social immunity was first summoned by evolutionary biologists to resolve the apparent discrepancy between the expected high frequency of disease outbreak amongst numerous, closely related tightly-interacting hosts, living in stable and microbially-rich environments, against the exceptionally scarce epidemic accounts in natural populations. Social
immunity comprises a multi-layer assembly of behaviours which have evolved to effectively keep the pathogenic enemies of a colony at bay. The field of social immunity has drawn interest, as it becomes increasingly urgent to stop
the collapse of pollinator species and curb the growth of invasive pests. In the past decade, several mechanisms of
social immune responses have been dissected, but many more questions remain open.

I present my work in two experimental chapters. In the first, I use invasive garden ants (*Lasius neglectus*) to study how pathogen load and its distribution among nestmates affect the grooming response of the group. Any given group of ants will carry out the same total grooming work, but will direct their grooming effort towards individuals
carrying a relatively higher spore load. Contrary to expectation, the highest risk of transmission does not stem from grooming highly contaminated ants, but instead, we suggest that the grooming response likely minimizes spore loss to the environment, reducing contamination from inadvertent pickup from the substrate.

The second is a comparative developmental approach. I follow black garden ant queens (*Lasius niger*) and their colonies from mating flight, through hibernation for a year. Colonies which grow fast from the start, have a lower chance of survival through hibernation, and those which survive grow at a lower pace later. This is true for colonies of naive
and challenged queens. Early pathogen exposure of the queens changes colony dynamics in an unexpected way: colonies from exposed queens are more likely to grow slowly and recover in numbers only after they survive hibernation.

In addition to the two experimental chapters, this thesis includes a co-authored published review on organisational
immunity, where we enlist the experimental evidence and theoretical framework on which this hypothesis is built,
identify the caveats and underline how the field is ripe to overcome them. In a final chapter, I describe my part in
two collaborative efforts, one to develop an image-based tracker, and the second to develop a classifier for ant
behaviour.},
  author       = {Casillas Perez, Barbara E},
  issn         = {2663-337X},
  keywords     = {Social Immunity, Sanitary care, Social Insects, Organisational Immunity, Colony development, Multi-target tracking},
  pages        = {183},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Collective defenses of garden ants against a fungal pathogen}},
  doi          = {10.15479/AT:ISTA:6435},
  year         = {2019},
}

@misc{5560,
  abstract     = {This repository contains the data collected for the manuscript "Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity".
The data is compressed into a single archive. Within the archive, different folders correspond to figures of the main text and the SI of the related publication.
Data is saved as plain text, with each folder containing a separate readme file describing the format. Typically, the data is from fluorescence microscopy measurements of single cells growing in a microfluidic "mother machine" device, and consists of relevant values (primarily arbitrary unit or normalized fluorescence measurements, and division times / growth rates) after raw microscopy images have been processed, segmented, and their features extracted, as described in the methods section of the related publication.},
  author       = {Bergmiller, Tobias and Andersson, Anna M and Tomasek, Kathrin and Balleza, Enrique and Kiviet, Daniel and Hauschild, Robert and Tkacik, Gasper and Guet, Calin C},
  keywords     = {single cell microscopy, mother machine microfluidic device, AcrAB-TolC pump, multi-drug efflux, Escherichia coli},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity}},
  doi          = {10.15479/AT:ISTA:53},
  year         = {2017},
}

@misc{5562,
  abstract     = {This data was collected as part of the study [1]. It consists of preprocessed multi-electrode array recording from 160 salamander retinal ganglion cells responding to 297 repeats of a 19 s natural movie. The data is available in two formats: (1) a .mat file containing an array with dimensions “number of repeats” x “number of neurons” x “time in a repeat”; (2) a zipped .txt file containing the same data represented as an array with dimensions “number of neurons” x “number of samples”, where the number of samples is equal to the product of the number of repeats and timebins within a repeat. The time dimension is divided into 20 ms time windows, and the array is binary indicating whether a given cell elicited at least one spike in a given time window during a particular repeat. See the reference below for details regarding collection and preprocessing:

[1] Tkačik G, Marre O, Amodei D, Schneidman E, Bialek W, Berry MJ II. Searching for Collective Behavior in a Large Network of Sensory Neurons. PLoS Comput Biol. 2014;10(1):e1003408.},
  author       = {Marre, Olivier and Tkacik, Gasper and Amodei, Dario and Schneidman, Elad and Bialek, William and Berry, Michael},
  keywords     = {multi-electrode recording, retinal ganglion cells},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Multi-electrode array recording from salamander retinal ganglion cells}},
  doi          = {10.15479/AT:ISTA:61},
  year         = {2017},
}