Dominik Brunmeir is a Researcher in the Data Science department at TU Wien's Faculty of Informatics. His work focuses on agent-based modeling, machine learning applications, and epidemiological simulation for public health policy analysis. He is involved in projects such as DynOptTestControl (2022–2026) and KLIPHA-COVID19 (2020–2021), contributing to pandemic response strategies and vaccination optimization algorithms. His research integrates computational methods with real-world challenges, including estimating herd immunity thresholds, evaluating contact-tracing policies, and modeling undetected infections during the SARS-CoV-2 outbreak. He has published extensively in journals like Scientific Reports , Medical Decision Making , and PLoS Computational Biology , emphasizing interdisciplinary approaches to public health and decision support systems. Key technical contributions include the development of agent-based templates for simulation efficiency, GANs for agent decision modeling, and transformer tools for medical decision-support knowledge systems. His work bridges theoretical modeling with practical applications in healthcare logistics and pandemic management.
Marvin Burges is a PreDoc Researcher at the Department of Computer Vision within the Faculty of Informatics at TU Wien. His research focuses on applying computer vision and machine learning techniques to historical aerial imagery, with a particular emphasis on object detection, semantic classification, and interactive analysis. He is actively involved in the DoRIAH project (2020–2024), exploring applications such as bomb crater detection and semi-automated object recognition in archival materials. Burges teaches courses including 3D Vision and Introduction to Visual Computing . His work bridges historical preservation, geospatial analysis, and modern AI methods, with publications in venues like GeoSearch, IEEE WACV, and OAGM workshops. His methodologies include self-supervised learning, vision-language models, and human-in-the-loop systems to enhance the interpretability of legacy datasets. Key technical contributions include developing algorithms for historical aerial image classification, crater detection, and novel class identification in remotely sensed imagery. His research addresses challenges in digitizing and analyzing large-scale historical archives through interdisciplinary approaches.
Ingo Feinerer serves as an Associate Professor at Vienna University of Technology's Faculty of Informatics, specifically within the Institute of Information Systems Engineering (E192-02). His research bridges theoretical computer science and practical applications in database systems, artificial intelligence, and text mining, with significant contributions to configuration management and formal methods. His educational background includes: PhD Dissertation (2007): A formal treatment of UML class diagrams as an efficient method for configuration management Diploma Thesis (2005): Formal program verification: a comparison of selected tools and their theoretical foundations Feinerer's research focuses on database theory (particularly schema mapping and dependencies), AI-driven configuration systems using integer linear programming, and text mining infrastructure development in R. His work combines theoretical rigor with practical tool development, notably through the textcat and tm packages. The integration of formal methods in software engineering remains a consistent thread throughout his publications. Analysis of his 15 most recent publications reveals strong specialization in database constraints (40%), text mining applications (30%), and software configuration systems (30%), with increasing interdisciplinary work connecting computer science to digital humanities. His notable recognition includes: INiTS Award (2007) for technology commercialization potential Feinerer has supervised doctoral research including F. I. Chertes' work on schema mapping languages and diploma theses on UML semantics and probabilistic databases. He led major research projects HINT (2012-2017) and SEE (2012-2016) focusing on database technologies and information systems. His work demonstrates consistent funding through Austrian national research programs. As a core member of the Databases and Artificial Intelligence research group, he collaborates extensively on R package development for text analysis and contributes to international workshops on theoretical aspects of software engineering.
Günther Haring serves as a Full Professor at TU Wien's Faculty of Informatics, specifically within the Institute of Information Systems Engineering (E194), where he leads research in distributed systems and mobile computing architectures. His core research spans: Distributed Systems infrastructure design Mobile context-aware frameworks Wireless sensor network integration Shared data space computation models Location-based distributed services Professor Haring maintains active supervision of graduate researchers, with documented mentorship of diploma and doctoral candidates in mobile distributed systems. His work demonstrates consistent focus on mobility challenges within distributed environments over the past two decades. He operates within the Distributed Systems research group (E194-02), contributing to TU Wien's informatics infrastructure through both theoretical frameworks and practical implementations of context-aware computing systems.
Florian Ferdinand Huemer is a PostDoc Researcher at the Embedded Computing Systems department (E191-02 Faculty Council Substitute Member) within the Faculty of Informatics at Vienna University of Technology. His work focuses on fault-tolerant asynchronous circuits, delay-insensitive communication protocols, and FPGA reliability analysis. BSc , Vienna University of Technology Dipl.-Ing. , Vienna University of Technology Dr.techn. , Vienna University of Technology Key research areas include: Fault-Tolerant Computing : Designing systems resilient to transient faults and radiation effects. Asynchronous Circuits : Developing quasi-delay-insensitive logic and Muller pipelines. Embedded Metrology : Applying polarization cameras and time-to-digital converters for industrial measurements. Recent publications address: 2024 : Polarization camera-based inline thickness measurement and FPGA ring oscillator synchronization. 2023 : Mitigating single-event transients in QDI logic. 2021 : Automated fault-injection frameworks and QDI pipeline sensitivity analysis. Projects funded by the Austrian Science Fund (FWF) during 2013-2018 explored self-stabilizing Byzantine fault-tolerant algorithms. Supervisions include: Haschke (2024): QDI adder comparison Spitzer (2024): Automated fault-injection framework Schwendinger (2022): Asynchronous circuit testing tools Pircher (2022): Smart SoC testing via IJTAG Behal (2021): QDI design template fault sensitivity
Bernhard Kerbl is a Post-doctoral Researcher at the Computer Graphics Group (E193-02) within the Faculty of Informatics at Vienna University of Technology (TU Wien). He actively contributes to research in real-time rendering, GPU optimization, and 3D visualization. His work focuses on point cloud rendering, Gaussian splatting, and low-level graphics API development (particularly Vulkan). Core Research Areas: Real-time rendering, GPU programming, point cloud processing, 3D Gaussian splatting, task-based parallelism Projects: IVILPC (2023–2026), ACD (2020–2028), EVOCATION (2018–2022) Key Contributions: Developed real-time rendering techniques for massive datasets, pioneered GPU-based scene streaming architectures, and created novel methods for visual error prediction using machine learning. His work on Vulkan transition in academia received recognition, and he maintains active collaborations in GPU education. Scientific Achievements: Best Paper Award at EGPGV 2024 for "Fast Rendering of Parametric Objects on Modern GPUs" Recipient of Vienna Science and Technology Fund (WWTF) support for graphics research Technical Expertise: Specializes in CUDA, OpenGL/Vulkan APIs, and real-time systems. His work bridges academic research with practical implementations in virtual reality, augmented reality, and GPU education.
Raimund Kirner is an academic at the Institute of Computer Engineering (E191-01) at Technische Universität Wien , specializing in real-time and embedded systems. His career spans research in Worst-Case Execution Time (WCET) Analysis , Time-Triggered Communication , and Automated Testing for safety-critical systems. He has contributed to projects such as ALL-TIMES, COSTA, and HINT, focusing on timing predictability and composability in real-time systems. Key Research Areas : WCET Analysis, Real-Time Systems, Embedded Testing, Time-Predictable Computing Notable Collaborations : Peter Puschner, Andreas Prantl, Martina Zolda Recent Publications analyze cybersecurity in automotive networks, quantitative interface evaluation for time-triggered systems, and synchronization trade-offs. His work bridges theoretical timing models with practical compiler and hardware solutions for deterministic execution. Awards : Recipient of the Mobilitätsstipendium der Creditanstalt AG (2003) for outstanding dissertation. Advising includes supervising 11 theses from 2002–2014 on topics like Automated Load Balancing , WCET Estimation , and Compiler Timing Models .
Dr. Robert Keil is a Research Fellow at the Department of Experimental Physics, University of Innsbruck, Austria. His research focuses on quantum optics, many-particle interference, and hybrid quantum networks. He teaches courses in photonics and electromagnetism, including 'Photonik' and 'Physik2 - Elektromagnetismus und Optik'. Academic Role: Senior Scientist (Research Fellow) Affiliation: University of Innsbruck, Department of Experimental Physics Research Interests: Quantum Optics: Investigating non-interacting particles and photon interference phenomena Hybrid Quantum Networks: Developing photonic interfaces for quantum communication Quantum Mechanics Tests: Precision multi-path interferometry experiments Funding: Current projects include FWF-funded research on single-photon spectra and hybrid photonic circuits. Previous grants include studies on many-particle interference and foundational quantum tests.
Rolf Apweiler serves as Director of the European Bioinformatics Institute (EMBL-EBI), part of the European Molecular Biology Laboratory, a position he has held since 2015. Previously, he was Associate Director (2012-2015) and led multiple critical protein resources including UniProt and InterPro. His leadership extends to directing Open Targets since 2018 and spearheading EMBL-EBI's contribution to the European COVID-19 Data Platform. Apweiler's research spans Bioinformatics, Proteomics, and Genomics , with significant contributions to protein annotation methods, proteomics data standards, and major biological databases. His work enables comprehensive analysis of proteome sets across entire organisms and has established foundational resources for the global scientific community. His publication portfolio demonstrates consistent leadership in developing critical bioinformatics infrastructure, with major contributions including UniProt, PRIDE, IntAct, and InterPro. These resources form the backbone of modern proteomics research and have been widely adopted across the life sciences. HUPO Distinguished Achievement Award in Proteomics (2004) EMBO Member (2011) ISCB Fellow (2015) President of Human Proteomics Organisation (2007-2008) As Director of EMBL-EBI, Apweiler oversees one of the world's leading bioinformatics institutions, managing extensive research programs, international collaborations, and major data infrastructure projects. His leadership in Open Targets demonstrates significant engagement with translational research connecting basic science to drug discovery. Apweiler's teams maintain several critical global resources including PRIDE (proteomics identifications), IntAct (molecular interactions), and UniProt (protein knowledgebase), forming an integrated ecosystem for biological data analysis.
Francesco Paolo Battaglia is a Full Professor at the Donders Centre for Neuroscience, Radboud University Nijmegen, Netherlands. He has held previous academic positions including Associate Professor (2013-2020) and Assistant Professor (2006-2012), with ongoing contributions to computational neuroscience and memory research. Education: PhD in Cognitive Neuroscience (1998) from SISSA, Italy Master in Physics (1994) from University of Rome La Sapienza His research focuses on neuronal networks of memory, hippocampal function, neurophysiology, and computational modeling of neural systems. He has pioneered work on grid cells and spatial cognition frameworks. Scientific Awards: ERC Advanced Grant (2019) Neuron Top 30 Paper Recognition (2018) Neurotech-NL Plan Recognition (2015) Nobel Prize 2014 Citation Contribution Prix la Recherche (2010) He has secured over €6 million in funding through grants including ERC REPLAY-DMN (€2.38M), NWO TOP Exact Sciences (€750K), and EU-MSCA Postdoctoral Fellowship (€180K). Supervised 6 postdocs, 9 PhD students, and 10 Master students at Donders Institute.
René Bernards serves as Professor of Molecular Carcinogenesis at Utrecht University (part-time since 1994) and Head of the Division of Molecular Carcinogenesis at the Netherlands Cancer Institute (since 1992). He co-founded Agendia BV in 2003, a genomics diagnostics company that launched the first microarray-based breast cancer diagnostic test in 2004. His research focuses on genome-wide loss-of-function genetic screens to identify novel cancer drug targets and resistance mechanisms. Key areas include senescence induction therapy and MAP kinase pathway drug combinations , with his 2012 discovery of BRAF/EGFR inhibition efficacy leading to regulatory approval for BRAF-mutant colon cancer treatment. His publication portfolio demonstrates strong translational impact, with recent work spanning computational oncology (2018) and immunotherapy response prediction (2025). These studies reflect his laboratory's evolution from fundamental cancer genetics toward clinically applicable diagnostic and therapeutic strategies. Pezcoller Foundation-FECS Recognition for Contribution to Oncology (2005) Spinoza award, Netherlands Organization for Scientific Research (2005) ESMO Lifetime Achievement Award in Translational Research (2007) Foreign member, Royal Society (2023) Bernards leads a 17-member research team including PhD students and postdoctoral fellows, maintaining close clinical collaborations with affiliated hospitals. His group's work on senescent cancer cell elimination (2024) continues to generate significant research interest. The laboratory operates within the Netherlands Cancer Institute's infrastructure, leveraging specialized facilities for functional genomics and drug screening.
Berry Gérard is a distinguished Professor at Collège de France, holding the Chair in Algorithms, Machines, and Languages since 2012. He previously served as Director of Research at INRIA Sophia Antipolis and Chief Scientist at Esterel Technologies. His academic journey includes roles at École des Mines de Paris and École Polytechnique. Gérard specializes in models of computation, programming language design, and synchronous systems. He has contributed significantly to the development of the Esterel language for embedded systems and formal verification techniques. Education: Docteur d’Etat in Mathematics, Université Paris VII (Computer Science option), 1979 Ingénieur des Mines, Corps National des Ingénieurs des Mines, 1970 École Polytechnique, 1967 Research Interests: Focuses on computational models (e.g., lambda-calculus, synchronous concurrency), programming languages (Esterel, Hop/HipHop), circuit synthesis, and formal verification. His recent work explores diffuse programming and web orchestration. Key Awards: 2014: Médaille d'or du CNRS 2005: Member, Académie des technologies 1993: Member, Academia Europaea 1979: Bronze Medal of CNRS Professional Roles: President of the Council of Education and Research at École Polytechnique Member of the Scientific Council of IRCAM Former President of the INRIA Evaluation Committee Labs/Teams: Active in INRIA’s Indes project on diffuse programming and collaborates with IRCAM on real-time music systems.
Michael Bronstein is a Professor & Chair in Machine Learning and Pattern Recognition at the Department of Computing, Imperial College London (since 2018), with a concurrent professorship at the Institute for Computational Science, University of Lugano, Switzerland (since 2010, currently on leave). His academic career includes visiting positions at Stanford University (Visiting Lecturer, 2008-2009), Tel Aviv University (Visiting Associate Professor, 2015-2017), Harvard University (Visiting Scholar, 2017-2018), and MIT (Research Affiliate, 2017-2018). Dr. Bronstein's research focuses on theoretical and computational geometric methods for data analysis, with applications spanning machine learning, computer vision, graphics, geometry processing, biology, and social networks. His work in geometric deep learning has established foundational frameworks for processing non-Euclidean data such as graphs and manifolds, bridging the gap between traditional Euclidean deep learning and complex structured data. His publication record demonstrates a clear trajectory from fundamental geometric methods to their application in diverse domains. Early work focused on 3D shape analysis and non-rigid shape recognition, while more recent publications showcase the application of geometric deep learning to protein structure analysis, point cloud processing, and graph-based machine learning. The consistent thread throughout his research is the development of mathematical frameworks that respect the intrinsic geometry of data. Royal Academy of Engineering Silver Medal (2020) Fellow of IEEE, IAPR, and ELLIS Five ERC grants (Starting 2012, Consolidator 2016, and Proof of Concept 2016, 2018, 2019) Royal Society Wolfson Research Merit Award Young Scientist, World Economic Forum (2014) Bronstein has successfully translated academic research into practical applications through multiple entrepreneurial ventures. As ML Lead for Project CETI and Head of Graph Learning Research at Twitter (since 2019), he bridges academic research with industrial applications. His previous startups include Fabula AI (acquired by Twitter in 2019) and Invision (acquired by Intel in 2012), where he contributed to the development of Intel RealSense 3D camera technology. His research has been supported by significant funding including ERC grants and industry awards from Google, Amazon, and Facebook.
Guido Caldarelli is a Full Professor of Theoretical Physics at Ca' Foscari University of Venice , with affiliations at CNR-ISC, IMT Lucca, and the London Institute for Mathematical Sciences (LIMS). His career spans roles including President of the Complex Systems Society (2018-2020), co-founder of the Network Science Society, and director of CNR-ISC. Active in interdisciplinary research, he bridges statistical physics, network science, and applications in finance, urban planning, and biomedicine. PhD in Condensed Matter Physics, SISSA Trieste (1996) MPhil in Physics, SISSA (1994) Physics Degree, Sapienza Rome (1992) Guido's research focuses on complex systems and network theory , particularly in financial networks, urban dynamics, and biological systems. His work explores scale-free networks, systemic risk, and entropy-based models, with applications in digital twins for cities, microbiome analysis, and misinformation spread on social media. Recent publications highlight trends in network analysis for urban planning (green infrastructure), machine learning in NMR spectroscopy, and social media dynamics during political events. His interdisciplinary approach connects theoretical physics to practical challenges in healthcare, finance, and climate resilience. Scientific Awards Honorary ISI Fellow APS Fellow (2020) Member of Academia Europaea (2020) Fellow of the Network Science Society Outstanding Service Prize, Network Science Society (2020) Guido leads the Complex Networks group at CNR-ISC, co-founded Catchy s.r.l. (data-driven innovation), and serves on the Scientific Committee for Italian Police Force training . His work integrates theoretical rigor with real-world impact across disciplines.
Federico Capasso is the Robert Wallace Professor of Applied Physics at Harvard University, where he has been a faculty member since 2003. He is renowned for inventing the quantum cascade laser at Bell Laboratories and pioneering bandstructure engineering in semiconductor devices. His research spans plasmonics, metasurfaces, nanophotonics, and Casimir forces , with applications in light sources, optical antennas, and MEMS technology. PhD in Physics, summa cum laude, University of Rome (1973) Leadership roles at Bell Labs: Head of multiple departments (1987–2000), Vice President (2000–2002) Research Interests: Quantum electronics, terahertz radiation generation, plasmonic interfaces, and flat optics. His group at Harvard demonstrated optical antennas, plasmonic collimators , and generalized laws of reflection/refraction via metasurfaces. Article Trends: Recent work focuses on metasurface optimization , integrated solitons , optical rotatum , and active mid-infrared ring resonators , reflecting advancements in flat optics and quantum electronics. Scientific Awards: 2016 Balzan Prize 2013 SPIE Gold Medal 2005 King Faisal Prize 2004 Edison Medal 1995–1998: National Academy memberships and fellowships Labs/Teams: Leads the Capasso Group at Harvard, which co-founded the startup Metalenz for metasurface commercialization.
