Dipl.-Ing. Manuel Reithofer Ph.D. is a researcher at the Institute of Molecular Biotechnology within the Department of Biotechnology and Food Science at the University of Natural Resources and Life Sciences, Vienna . His work focuses on molecular biology, cell biology, and microbiology, with a strong emphasis on recombinant protein production and immune response mechanisms. Education: Ph.D. in Immunology (2014-2018), Medical University of Vienna. Master in Medical Biotechnology (2012-2014), University of Natural Resources and Life Sciences, Vienna. Bachelor in Food Science and Biotechnology (2009-2012), University of Natural Resources and Life Sciences, Vienna. Dr. Reithofer's research explores baculovirus-mediated gene delivery (BacMam platform), SARS-CoV-2 spike protein interactions, and allergen-specific immunotherapy. He leads the REMBAC project (2025-2026, funded by FFG) and contributes to SARS-CoV-2 biosensor development (2021-2023, FWF). His work spans collaborations with institutions like the Medical University of Vienna. He has presented at international conferences (e.g., Protein Expression in Animal Cells (PEACe), Sitges 2023 ) and maintains affiliations with multiple BOKU research teams.
Dr. Andreas Zedrosser is a senior researcher at the Institute of Wildlife Biology and Game Management , University of Natural Resources and Life Sciences, Vienna (BOKU). He holds a PhD in Wildlife Biology and has held postdoctoral and research positions at institutions including the Norwegian University of Life Sciences and University of Alberta. His work focuses on brown bear ecology, conservation, and human-wildlife interactions. PhD in Scandinavian brown bear life history (2006) MSc in Wildlife Biology (2001) Postdoc at Norwegian University of Life Sciences (2007-2011) His research spans wildlife ecology , conservation biology , and nutritional ecology , with recent publications analyzing brown bear space use, reproductive performance, and behavioral responses to anthropogenic threats. Articles highlight climate change impacts , foraging optimization , and social dynamics in solitary carnivores. Scientific accolades include the Granser Research Prize (2011) and Kurir Foundation Prize (2008) . He supervises theses on bear ecology and has contributed to international conservation programs for large carnivores in Europe. His team collaborates with institutions like the Scandinavian Brown Bear Research Project and Norwegian Red List committees.
Nikolaus Virgolini is a researcher at the Institute of Bioprocess Science and Engineering within the Department of Biotechnology and Food Science at the University of Natural Resources and Life Sciences, Vienna (BOKU) . He holds a Dipl.-Ing. and Ph.D., with expertise in mammalian cell biotechnology and bioprocess optimization. His research focuses on Cellular response to evolutionary pressures in HEK293 cells Characterization of genetic/epigenetic states for biopharmaceutical applications Advanced analytics for gene therapy vectors (AAVs) Metabolic engineering for sustainable polymer production Recent publications highlight methodological advances in bioprocess engineering and molecular biotechnology , particularly in AAV vector separation techniques HEK293 cell line optimization Protein glycosylation and clearance mechanisms He participates in international conferences like ESGCT and PEACe , contributing to knowledge transfer in bioprocessing. Currently involved in the Christian Doppler Laboratory for Knowledge-based Production of Gene Therapy Vectors (2023-2029).
Dr. Gerlinde Wiesenberger is a senior researcher at the Institute of Bioanalytics and Agro-Metabolomics , part of the Department of Agricultural Sciences at the University of Natural Resources and Life Sciences, Vienna (BOKU) . With over 15 years of experience in mycotoxin research, she specializes in Fusarium toxins , plant resistance mechanisms , and mycotoxin detoxification . Current projects: BIOTOXDoc (2023-2027), Toxicological significance of modified fumonisins (2020-2023) Key research areas: Mycotoxin chemistry , Metabolomics , Fungal-plant interactions Her work focuses on biochemical characterization of mycotoxin-modifying enzymes , mechanisms of fungal self-resistance , and toxin degradation in food processing . Recent articles highlight discoveries in UDP-glucosyltransferase function , novel Fusarium metabolites , and masked mycotoxin dynamics . She has supervised 6 university theses and collaborated with institutions like the Institute of Meteorology and Climatology and Institute of Microbial Genetics . Her research contributes to food safety strategies under climate change scenarios.
Dr. Ernö Robert Csetnek is a researcher affiliated with the Faculty of Mathematics , Department of Mathematics . His work spans optimization, dynamical systems, and non-smooth mathematical analysis. Faculty of Mathematics, Department of Mathematics Active in convex and non-convex optimization, variational inequalities, and dynamical systems His recent publications focus on Tikhonov regularization , inertial dynamics , and minimax algorithms for non-smooth and non-convex problems. Key themes include convergence guarantees, differential equations modeling, and operator splitting techniques. Scientific awards: No awards explicitly mentioned in the provided data.
Soumya Dutta is an Assistant Professor in the Department of Computer Science and Engineering (CSE) at the Indian Institute of Technology Kanpur (IITK) since 2022. He previously held positions at Los Alamos National Laboratory as a Postdoctoral Researcher (2018-2019) and Scientist II (2019-2022). Dr. Dutta earned his Ph.D. and M.S. in Computer Science from The Ohio State University (2011-2018) and a B.Tech in Electronics and Communication Engineering from the West Bengal University of Technology (2005-2009). His research lies at the intersection of Machine Learning , Visual Computing , Big Data Analytics , and High-Performance Computing (HPC) . He focuses on developing scalable solutions for extreme-scale data, such as exascale simulations, social media, IoT, and healthcare. His work emphasizes uncertainty quantification in AI models and interactive visualization techniques. Dr. Dutta’s recent publications highlight his expertise in in situ visualization for climate modeling, implicit neural representations for uncertainty-aware rendering, and statistical sampling for exascale systems. His funded projects include AI-driven data analytics frameworks and deepfake defense mechanisms supported by ISRO, SERB, and C3iHub. Scientific Awards include Best Reviewer (TVCG), Best Paper (ISAV, TopoInVis), and LAAP Award (LANL).
Daniel Große serves as a full Professor at Johannes Kepler University Linz, holding primary affiliation with the Institute for Symbolic Artificial Intelligence and secondary appointments at the Institute of Complex Systems and LIT Secure and Correct Systems Lab. He currently leads 3 major research projects including Modular Real-Time Control (2023-2026) and the ENGEL Austria GmbH industry collaboration (2019-2027), while maintaining active roles in 113 professional activities through 2025. His research integrates Computer Security , Hardware Design , and Artificial Intelligence to address critical challenges in embedded systems. Key focus areas include cryptographic instruction chaining for control flow protection, RISC-V vector workload simulation, and LLM-assisted metamorphic testing of graphics libraries, with strong emphasis on practical applications for safety-critical systems. Recent publications (2025) reveal a cohesive research trajectory toward secure computing foundations, combining formal verification techniques with AI-driven development tools. His work consistently bridges hardware security primitives and software engineering innovations, particularly targeting vulnerabilities in instruction set architectures and embedded graphics pipelines. Prof. Große has supervised 4 graduate students and secured significant funding through both public grants (VerA project) and industry partnerships. His project portfolio demonstrates strategic balance between theoretical advances in arithmetic circuit verification and applied industrial solutions for real-time control systems. As a core member of the LIT Secure and Correct Systems Lab, he contributes to interdisciplinary research initiatives developing formally verified secure computing platforms, with active collaborations spanning hardware security validation, virtual prototyping frameworks, and AI-enhanced software testing methodologies.
Thomas Gärtner is a Full Professor of Machine Learning at TU Wien (Technical University of Vienna), leading the Machine Learning Research Unit (E 194-06). He previously held professorships at the University of Nottingham and the University of Bonn. His research focuses on efficient and effective machine learning algorithms, particularly in structured data domains like graphs and chemical compounds. Key areas include kernel methods, active learning, and graph neural networks. He is involved in projects such as NanoX (Austrian Science Fund) and StruDL (Vienna Science Fund), addressing challenges in structured data learning and trustworthy AI. Education: PhD from University of Bonn (2005), MSc from University of Bristol (2000), Diplom from University of Cooperative Education (1999). Research Interests: Machine Learning, Data Mining, Kernel Methods, Chemoinformatics, Graph Neural Networks, Active Learning, and Constructive Machine Learning. His work emphasizes real-world applications in chemistry and computer games. Grants & Awards: Emmy Noether Grant (2010), Best Paper Award (2016), ICLR Area Chair (2021), and recognition for contributions to EPSRC peer review (2020). Teaching: Offers courses like 'Introduction to Machine Learning' and 'Theoretical Foundations of Machine Learning.' Supervises PhD and diploma students in advanced topics such as graph algorithms and neural network distillation. Lab/Teams: Heads the Machine Learning Research Unit and collaborates with the competence center ML2R (Rhine-Ruhr region). Active in organizing ECML PKDD conferences and workshops on constructive machine learning.
Benjamin Roth is a Professor at Saarland University holding dual affiliations in the Faculty of Computer Science (Research Group Data Mining and Machine Learning) and the Faculty of Philological and Cultural Studies (Department of European and Comparative Literature and Language Studies). His research focuses on natural language processing, large language models, machine learning, and computational linguistics. He leads multiple active research projects including 'Understanding Language in Context' (2025–2033) and 'Linguistic Methods for the Detection of Implicit Abuse' (2024–2027). Notable collaborations span cross-functional studies on LLM behavior, clinical text analysis, and knowledge graph integration. He actively participates in conference organization and has presented at venues like the Konferenz zur Verarbeitung natürlicher Sprache (2024). His work emphasizes methodological innovation in weak supervision, model calibration, and multimodal reasoning. Recent contributions include studies on persona effects in LLMs, specification overfitting mitigation, and zero-shot temporal relation extraction. He has co-authored over 20 peer-reviewed publications since 2020, with a focus on advancing ethical AI, model interpretability, and NLP education.
Peter Jonas is a Professor and the Magdalena Walz Professor for Life Sciences at the Institute of Science and Technology Austria (ISTA). His research focuses on synaptic physiology, cellular neuroscience, and neural circuit dynamics, particularly in the hippocampus and cortex. He leads the Jonas Group, which investigates how synaptic properties shape higher network functions through advanced techniques like patch-clamp recording, two-photon imaging, optogenetics, and electron microscopy. MD, University of Giessen, Germany (1987) His research interests include synaptic transmission, plasticity, biophysics of ion channels, neural coding, and network modeling. The lab combines experimental and computational approaches to understand how synaptic mechanisms support memory and cognition. Recent work emphasizes nanoscale synaptic architecture, presynaptic function, and multiscale brain imaging. Recent publications highlight innovations in synaptic physiology, including mechanisms of vesicle release, synaptic nanotopography, and functional connectivity in memory networks. Trends include the integration of molecular, cellular, and systems-level analyses, with a strong emphasis on quantitative and interdisciplinary neuroscience. Magdalena Walz Professor for Life Sciences Peter Seeburg Integrative Neuroscience Prize of the Society of Neuroscience (100,000 $) Member, EMBO Erwin Schrödinger Prize, Austrian Academy of Sciences (ÖAW) FWF Wittgenstein Award ERC Advanced Grant GIANTSYN Elected Member Editorial Board, Neuron Member, Academia Europaea ERC Advanced Grant NANOPHYS Adolf Fick Award, Physical-Medical Society, Würzburg, Germany Member, Academy of Sciences, Heidelberg, Germany Member of the Board of Reviewing Editors, Science Tsungming Tu Award, National Science Council Taiwan DFG Gottfried Wilhelm Leibniz Award Member, German Academy of Sciences Leopoldina Max Planck Research Award Medinfar European Prize in Physiology, President of Portugal BMBF Heinz Maier Leibnitz Award DFG Heisenberg Fellowship Peter Jonas has advised several PhD students, including Silvia Jamrichova, Peipeng Lin, Rebecca Morse Mora, and Priyansha Verma. His research has been supported by major grants, including two ERC Advanced Grants (NANOPHYS and GIANTSYN), reflecting sustained excellence and innovation in fundamental neuroscience research. The Jonas Group is an active interdisciplinary team comprising postdocs, PhD students, research technicians, and software developers, working on synaptic mechanisms, neural coding, and brain-wide imaging technologies.
Michael Kuhn is a Research Professor and co-leader of the Economic Demography research group at the Wittgenstein Centre (IIASA, VID/OEAW, WU) and Vienna Institute of Demography (VID) under the Austrian Academy of Sciences. He holds a PhD in Economics from the University of Rostock, Germany (2001), with prior roles including a Junior Professorship at the Max Planck Institute for Demographic Research (2005–2008) and a lectureship at the University of York, UK (1999–2004). His research focuses on health economics, population dynamics, and the macroeconomic implications of aging populations. Key projects include FWF-funded studies on medical progress and health expenditure (2014–2017) and lifecycle behavior under health shocks (2018–present). He serves on the German Economic Association’s committees for Health and Population Economics, co-edits the Journal of the Economics of Ageing , and organizes the European Workshop on Labour, Health, and Education under Demographic Change since 2006. His work addresses global health challenges, climate adaptation, and the interplay between demographic shifts and economic systems. Recent research spans healthcare access disparities, aging’s economic impacts, and resilience modeling against health and environmental crises.
Peter Auer is a Professor affiliated with the Institute of Machine Learning and Neural Computation . His research spans Computer Science , focusing on Machine Learning , Pattern Recognition , and Artificial Intelligence . Key contributions include work on boosting algorithms, feature extraction, and visual information systems. Projects : Learning for Adaptable Visual Assistants (LAVA) (2002-2005) Research Trends : Publications emphasize object recognition , feature vectors , and hierarchical document repositories , with applications in computer vision and information retrieval.
Hannes Leeb is a full-time Professor at the University of Vienna , leading the Department of Statistics and Operations Research within the Faculty of Business, Economics, and Statistics . He is also affiliated with the Research Network Data Science and co-organizes the ISOR Colloquium . Research Interests : Inference Post Model Selection, Shrinkage-Type Estimators, High-Dimensional Data Analysis, Machine Learning, Random Matrices, Asymptotic Statistics, Linear/Non-Linear Time Series. Recent Research Trends : His 15 most recent articles focus on valid statistical inference in high-dimensional settings, including F-statistics , conformal prediction , and adaptive methods for deep learning. Key subfields include post-model selection uncertainty , conditional coverage , and shrinkage estimator properties . Teaching & Leadership : He teaches core courses like 'Basic Principles of Statistics' and 'Probability Theory', and supervises PhD research privatissimum in econometrics/statistics. As department head, he emphasizes data science integration and methodological rigor .
Michael Drauch is a Researcher in the Department of Mathematics at the Faculty of Mathematics. His research focuses on optimization theory, variational inequalities, and their applications in machine learning, particularly in generative adversarial networks (GANs). He has published extensively in top-tier conferences and journals since 2020, with notable contributions to monotone operators, convergence analysis, and algorithm design. Education: Holds BSc, MSc, and Dr. degrees (specific institutions not detailed). Research Interests: Optimization algorithms, convex-concave problems, minimax theory, and numerical methods with applications in machine learning. Recent publications highlight advancements in accelerated minimax algorithms and inertial forward-backward-forward methods. His work has garnered 7 citations and 8 Mendeley readers, indicating academic impact. Collaborations span international conferences like ICML. Drauch actively participates in academic activities, including talks on monotone variational inequalities at multiple institutions.
Prof. Klaus Roppert is a researcher at the Institute for Fundamentals and Theory of Electrical Engineering, Technische Universität Graz. His work focuses on electromagnetism, hysteresis modeling, and computational methods in electrical engineering. He holds degrees including Dipl.-Ing., Dr.techn., and BSc. Research Interests: Electromagnetic field theory and hysteresis modeling Finite element analysis for nonlinear systems Aeroacoustic simulations and fluid-structure interactions Material characterization and parameter identification Development of open-source simulation tools (e.g., openCFS) Recent work emphasizes transient analysis of transformers, rotational loss calculations, and energy-based vector hysteresis frameworks. He has contributed to modeling MEMS devices and EMI filters, with a focus on DC-biased components. Teaching and supervision: Involvement in courses and final theses supervision at TU Graz. Labs/Tools: Core contributor to openCFS, an open-source platform for coupled field simulations in acoustics and electromagnetics.
