Find Academic Supervisors

• Real-Time Systems
• System Architectures
• Communication Protocols
• +3 more

Roman Obermaisser is a Professor at the Vienna University of Technology (TU Wien), affiliated with the Cyber-Physical Systems department. His research focuses on real-time systems, system architectures, communication protocols, safety-critical systems, distributed algorithms, and fault-tolerance. He holds a PhD in Computer Science from TU Wien, awarded in 2003 for his work on integrated architectures for control paradigms. His academic contributions span over two decades, with publications in top-tier conferences and journals. Key research themes include time-triggered architectures (TTA), fault containment in embedded systems, and integration of heterogeneous communication protocols like CAN and Ethernet. He has supervised numerous graduate students, contributing to advancements in system-on-chip (SoC) design, transient-resilient architectures, and diagnostic frameworks for real-time systems. Obermaisser’s work emphasizes practical applications in automotive and industrial systems, addressing challenges such as scalability, reliability, and composability. His involvement in projects like GENESYS and DECOS highlights his role in developing cross-domain reference architectures for embedded systems. Recent efforts include evaluating ontology-based reconfiguration and COTS-based Ethernet solutions for safety-critical networks. His articles reflect a focus on real-time communication protocols, fault-tolerant design, and system integration, with applications ranging from automotive networks to smart transducers. Advising over 20 students underscores his commitment to nurturing the next generation of embedded systems researchers.

Victor VianuView profile

Professor

• Computational Logic
• Database Systems
• Database Theory
• +4 more

Victor Vianu is a Professor of Computer Science and Engineering at the University of California, San Diego and holds the INRIA International Chair at INRIA-Saclay in Paris. He has maintained continuous faculty status at UC San Diego since 1983 while developing extensive international collaborations, particularly with French research institutions including INRIA, ENST-Paris, ENS-Paris, and the University of Paris. His academic credentials include a Ph.D. in Computer Science from the University of Southern California (1983) and undergraduate studies in Mathematics and Informatics at the University of Bucharest (1974-1977). Professor Vianu's research spans computational logic, database systems and theory, and automatic verification. His work uniquely bridges theoretical foundations with practical applications in XML processing, workflow systems, and data-driven applications. He has made seminal contributions to understanding the theoretical underpinnings of database query languages and their expressive power, particularly in the context of XML technologies and workflow systems. His research demonstrates a consistent trajectory from theoretical computer science to practical database systems applications. His publication record reveals significant contributions to database theory spanning over three decades, with particular emphasis on XML technologies, workflow systems, and formal methods for data-driven applications. His work shows a clear evolution from foundational theoretical work to practical applications in business processes and web technologies. INRIA International Chair (2013) Fellow of the American Association for the Advancement of Science (AAAS) (2013) ACM PODS Alberto O. Mendelzon Test-of-Time Award (2010) Fellow of the Association for Computing Machinery (ACM) (2006) Professor Vianu has held significant leadership roles including Editor-in-Chief of the prestigious Journal of the ACM, numerous program committee chair positions for major database conferences (PODS, ICDT, ASIAN), and General Chair for ACM SIGMOD conferences. He has served on the executive committees of SIGMOD (1998-2000) and PODS (1993-2004), and was a member of the ICDT Council (1997-2007), demonstrating sustained influence in the theoretical database community. His extensive invited talks at major conferences including College de France, ACM PODS, and International Conference on Database Theory highlight his international recognition.

Benedikt WarthView profile

Professor

• Exposomics
• Metabolomics
• Analytical Chemistry
• +4 more

Benedikt Warth is a Full Professor for Food Chemistry and Exposome Research at the Department of Food Chemistry and Toxicology, Faculty of Chemistry, University of Vienna (since 2022). He coordinates the Austrian node of the ESFRI research infrastructure EIRENE and leads the 'Global Exposomics and Biomonitoring Laboratory' since 2017. His work bridges chemistry and toxicology, focusing on exposomics and metabolomics to assess chemical exposure and its health impacts. Education: PhD in Analytical Chemistry (2012), Master’s in Biotechnology (2009), Bachelor’s in Food Science and Biotechnology (2007) Research interests center on exposomics , metabolomics , and analytical chemistry , particularly for environmental and food-related toxicants. Recent articles highlight advancements in mass spectrometry for exposome-scale analysis, combining targeted and non-targeted approaches, and exploring chemical interactions (e.g., xenoestrogens, mycotoxins, flame retardants) in biological systems. Key trends in his publications include: Development of hybrid LC-MS methods (targeted/untargeted) for sensitive exposomics Integration of AI and cognitive computing for pathway analysis Global biomonitoring of mycotoxins and xenobiotics in vulnerable populations Standardization frameworks for non-targeted analysis (SRT) Notable awards include the 2025 Chemical Research in Toxicology Young Investigator Award , Brigitte Gedek-Science Award , and multiple grants (ERC Consolidator, Erwin-Schrödinger Fellowship). He has delivered over 20 invited talks on exposomics, including sessions at ACS Fall Meetings and international conferences. His laboratory's projects span: Breast cancer exposomics (linking environmental exposures to disease onset) High-throughput sample preparation for exposome-wide studies Systems toxicology of chemical mixtures (e.g., flame retardants, mycotoxins) Development of global metabolomic assays for toxicity prediction

Giovanni De MicheliView profile

Professor

• Computer Architecture
• Electrical Engineering
• Integrated Systems
• +5 more

Giovanni De Micheli is a Professor of Electrical Engineering and Computer Science at EPF Lausanne, Switzerland. He also serves as Director of the Integrated Systems Centre and the Institute of Electrical Engineering at EPFL, and chairs the Scientific Committee of CSEM in Neuchatel. Previously, he held academic roles at Stanford University for 18 years, including Full Professor, Associate Professor, and Assistant Professor in the Department of Electrical Engineering. His research spans synthesis of digital circuits, hardware/software co-design, low-power design, and Networks on Chip (NoC) technology. 2003: IEEE Emanuel Piore Award 2000: Golden Jubilee Medal of the IEEE CAS Society 2000: ACM Fellow 1994: IEEE Fellow 1990: IEEE/CS Distinguished Service Award 1988: NSF Presidential Young Investigator Award His seminal contributions include pioneering C-based synthesis and Boolean matching algorithms for digital circuits, foundational work in dynamic power management using stochastic control, and the development of Network-on-Chip (NoC) technology. His publications, such as "Networks on Chips: A New SoC Paradigm" and "Dynamic Power Management for Portable Systems" , have shaped modern SoC design practices. With over 400 technical articles, 9 books, and an H-index of 56, his work remains highly influential.

Lloyd Nicholas TrefethenView profile

Professor

• Numerical analysis
• Applied mathematics
• Approximation theory
• +6 more

Lloyd Nicholas Trefethen is Professor of Numerical Analysis and Fellow of Balliol College at the University of Oxford, a position he has held since 1997. He also has concurrent appointments as Global Distinguished Professor of Mathematics and Computer Science at New York University (2013–2019) and has served as Von Neumann Professor at TU Munich and Matheon Professor at TU Berlin in 2010. Education: PhD (Computer Science/Numerical Analysis), Stanford University, 1982 MS (Computer Science/Numerical Analysis), Stanford University, 1980 AB summa cum laude (Applied Mathematics), Harvard College, 1977 Research Interests: Trefethen’s work centers on numerical mathematics, with particular emphasis on spectral methods , numerical linear algebra , approximation theory , numerical conformal mapping , quadrature , and pseudospectra . His research often bridges rigorous mathematical theory and practical algorithms, most notably through the widely used Chebfun software system. Recent publications illustrate a trend toward developing fast, high-accuracy algorithms for solving classical problems such as the Laplace and Helmholtz equations, rational approximation via the AAA algorithm, and stability analysis in fluid mechanics without traditional eigenvalue techniques. Scientific Awards: Pólya Prize for Mathematical Exposition (SIAM, 2017) Naylor Prize (London Mathematical Society, 2013) Gold Medal (Institute of Mathematics and its Applications, 2011) Fellow of the Royal Society (2005) Member of the US National Academy of Engineering (2007) ERC Advanced Grant (2012–2017) Honorary doctorates from Stellenbosch University and University of Fribourg (2019) Advising & Grants: Trefethen has supervised 24 PhD/DPhil students at MIT, Cornell, and Oxford; twelve have launched academic careers. He has held major grants including an ERC Advanced Grant on “Computing with functions instead of numbers” (€2.4 M, 2012–2017) and EPSRC funding for the Chebfun System (2006–2010). Labs & Teams: He leads the Chebfun Team at Oxford, an interdisciplinary group developing open-source software for numerical computing with functions. The team collaborates globally with researchers in mathematics, computer science, and engineering.

• Cybersecurity
• Cyber-Physical Systems
• Industrial Control Systems
• +4 more

Andreas Ekelhart is a Researcher at TU Wien's Department of Information and Software Engineering. His work focuses on cybersecurity, cyber-physical systems, and industrial control systems. He specializes in developing frameworks like SLOGERT for automated log analysis and Kyrstal for attack discovery using knowledge graphs. His research also explores digital twin technology for threat detection and semantic web applications in machine learning systems. Key contributions include the VloGraph framework for distributed security log analysis and the QualSec approach for automated security risk identification in production systems. He collaborates on standards like AutomationML and emphasizes privacy-preserving data analysis through semantic architectures.

• Communication Studies
• Journalism
• Media Framing
• +6 more

Fabienne Lind is a researcher at the Faculty of Social Sciences, Institute of Journalism and Communication Studies , focusing on communication studies, media framing, and political discourse. Her work spans migration, climate change, and social media analysis. Research interests include Comparative communication research Computational text analysis Media framing of climate justice and migration Digital political communication Multilingual text analysis Recent publications analyze social media dynamics , climate change coverage , and migration discourse across Brazil, India, and South Africa. Her 2025 work on longitudinal disparities in communication research highlights global trends. Scientific awards include PhD Award (2023) ICA Journalism Studies Division Top Student Paper Award (2019) Article of the Year by 'Communication Methods and Measures' (2018) She contributes to collaborative projects like CIDAPE (2024–2027) on climate, inequality, and democratic action, and engages in computational text analysis tools development for communication studies.

Torsten SchwedeView profile

Professor

• Structural Bioinformatics
• Protein Structure Prediction
• Computational Structural Biology
• +3 more

Torsten Schwede is a Professor for Structural Bioinformatics at the Biozentrum, University of Basel, and serves as Vice President for Research at the same institution. He leads the SPHN Data Coordination Center at SIB Swiss Institute of Bioinformatics. His research focuses on computational structural biology, protein structure prediction, and structural bioinformatics, with contributions to tools like SWISS-MODEL. He has been honored as a Highly Cited Researcher in Biology and Biochemistry (2019–2021). Education: PhD in Protein X-ray Crystallography from Albert-Ludwigs-Universität Freiburg (Germany). Positions include leadership roles in academia and industry (e.g., GlaxoSmithKline). His work emphasizes protein modeling, data management, and integrative structural methods. Collaborations span computational drug design, benchmarking initiatives (CASP), and open-source software development. Scientific contributions include advancements in protein-ligand interactions, homology modeling, and the development of ModelCIF and QMEANDisCo frameworks. He actively participates in global initiatives like the Swiss Personalized Health Network (SPHN) and precision medicine.

Martin HollerView profile

Professor

• Mathematics of data science
• Machine learning
• Generative models
• +7 more

Martin Holler is a Professor at the Institute of Mathematics and Scientific Computing at the University of Graz, Austria, where he leads the research group Applied Mathematics and Machine Learning . His work bridges theoretical mathematics with practical applications in imaging and machine learning. Research Focus: His primary research areas include the mathematics of data science, variational methods in imaging, dynamic and multi-modality inverse problems, and biomedical imaging. He has made significant contributions to model-based regularization techniques, particularly with Total Generalized Variation (TGV) approaches for image and video reconstruction. Publication Trends: Over the past decade, Holler's research has evolved from traditional variational methods for image reconstruction toward increasingly sophisticated machine learning approaches. His recent work (2021-2023) focuses on integrating deep learning with variational methods, particularly for motion separation in medical imaging and learning-informed parameter identification in partial differential equations. His publications demonstrate a consistent thread of applying rigorous mathematical frameworks to solve practical problems in medical imaging and computer vision. Mathematics of data science and machine learning Generative models in machine learning Variational methods in imaging Dynamic and multi-modality inverse problems Model-based regularization Biomedical imaging Image and video decompression Technical Leadership: Holler has developed several open-source software packages implementing advanced reconstruction algorithms, particularly for multi-modal imaging problems. His GitHub repositories show active maintenance and development of these tools, which have been cited in the medical imaging community.

Sylvain LefebvreView profile

Researcher

• Computer Graphics
• Texture Synthesis
• Additive Manufacturing
• +4 more

Sylvain Lefebvre is a permanent researcher at INRIA (Institut National de Recherche en Informatique et en Automatique) in France, where he leads the MFX research team since 2018. Previously, he was part of the ALICE group at INRIA Nancy (2009-2018) and the REVES team in Sophia Antipolis (2006-2009). His career includes a postdoctoral position at Microsoft Research Seattle (2005) following his PhD at INRIA Rhones-Alpes under Fabrice Neyret. His educational background includes a PhD in Computer Graphics from Université Joseph Fourier (Grenoble) in 2005, preceded by a Master in Computer Graphics from INP Grenoble in 2001. His habilitation thesis focused on Runtime Texture Synthesis. Lefebvre's research centers on simplifying content creation for highly detailed patterns, structures, and shapes with applications spanning Computer Graphics to additive manufacturing. He develops fast, controllable by-example synthesis approaches that generate content while enforcing user-specified constraints. His work addresses computational challenges through novel data structures and algorithms optimized for GPUs and FPGAs, including his Silice programming language. The ERC-funded ShapeForge project (2012-2017) advanced shape generation for 3D printing, leading to the IceSL software for digital modeling and fabrication. Analysis of his 15 most recent publications reveals a strong focus on additive manufacturing optimization, with recurring themes in structural integrity, material efficiency, and geometric algorithms. His work bridges computer graphics theory with practical fabrication constraints, particularly in microstructure design, slicing techniques, and mechanical metamaterials. The interdisciplinary nature spans computer science, materials engineering, and robotics. EUROGRAPHICS Young Researcher Award (2010) ERC Starting Grant for ShapeForge project (2012) Lefebvre has advised over 25 PhD students and interns including Marco Freire, Thibault Tricard, and Jimmy Etienne. His ShapeForge project received significant ERC funding, supporting research in computational fabrication. He serves on numerous program committees including SIGGRAPH, Eurographics, and SIGGRAPH Asia, reflecting his leadership in the computer graphics community. As leader of the MFX team since 2018, Lefebvre directs research in computational fabrication, focusing on IceSL software development for 3D printing workflows. The team integrates computer graphics techniques with manufacturing constraints, developing tools that simplify complex object design and fabrication while addressing real-world challenges in material usage and structural integrity.

Timon RabczukView profile

Professor

• Integrated computational materials engineering
• 2D materials
• Computational materials design
• +7 more

Timon Rabczuk is a Chaired Professor of Computational Mechanics at the Institute of Structural Mechanics, Bauhaus-Universität Weimar, Germany, since 2009. He previously held positions as Senior Lecturer at the University of Canterbury (2007-2009), Postdoctoral Fellow at Technical University of Munich (2005-2007), and Postdoctoral Fellow at Northwestern University (2002-2005). His research focuses on computational mechanics, materials science, and numerical methods for multi-scale and multi-field problems involving material failure, plasticity, and large deformations. Research Contributions : He develops models for virtual material design, enabling lightweight structures and energy storage applications. His work bridges natural and engineering sciences and has been implemented in commercial/open-source software. He has published over 600 papers, 9 book chapters, and 3 books (including two in 2023). His research spans 2D materials, composites, machine learning interatomic potentials, flexoelectricity, and biomechanical engineering. Scientific Awards : ERC Consolidator Grant (2013), Thomson Reuters/Clarivate Analytics Highly Cited Researcher (2014-2021) Editorial Roles : Editor-in-Chief of CMC-Computers, Materials and Structures; Executive Editor of FSCE-Frontiers of Structural and Civil Engineering; Associate Editor of multiple journals including International Journal of Impact Engineering and Applied Physics A. He has graduated 38 PhD students and secured over €25 million in research funding from national and European agencies.

Edgar ErdfelderView profile

Professor

• Statistical power analysis
• Multinomial processing tree (MPT) modeling
• Sequential statistical inference
• +3 more

Edgar Erdfelder is a Full Professor of Psychology at the University of Mannheim, Germany, holding the Chair of Cognitive Psychology and Individual Differences since 2008. He is affiliated with the School of Social Sciences and has made significant contributions to cognitive psychology, statistical modeling, and decision-making research. Previously, he served as Full Professor at the University of Mannheim (2002–2008), Associate Professor at the University of Giessen (2001–2002), and Senior Lecturer at the University of Bonn (1987–2001). Ph.D. in Psychology, University of Trier (1986) Habilitation in Psychology, University of Bonn (2000) Diploma (M.Sc.) in Psychology, University of Göttingen (1980) Erdfelder's research focuses on statistical power analysis, multinomial processing tree (MPT) modeling, sequential statistical inference, and cognitive modeling. His work explores judgment and decision-making through mathematical and computational frameworks, integrating signal-detection theory with threshold models. He developed the widely used GPOWER software for statistical power analysis and advanced MPT models to measure cognitive process speeds. His recent publications with students highlight applications of Bayesian sequential methods, meta-analyses of sleep effects on memory, and theoretical extensions of the recognition heuristic. These studies span subfields like cognitive architecture, decision theory, and experimental design. Martin Irle Award (2020) Fellow of the Association for Psychological Science (2016) Heinz Heckhausen Award (1988) Erdfelder has held leadership roles, including Vice President of Research at the University of Mannheim and Academic Director of the Center of Doctoral Studies in Social and Behavioral Sciences funded by the DFG. He mentored numerous Ph.D. students and led the DFG-funded Research Training Group SMiP, focusing on statistical modeling in psychology.

Georg LangsView profile

Professor

• Machine Learning
• Medical Imaging
• Precision Medicine
• +3 more

Georg Langs is a Full Professor of Machine Learning in Medical Imaging at the Medical University of Vienna and Founding Director of the Computational Imaging Research Lab (CIR). He leads a 25-member interdisciplinary team focusing on machine learning methodologies for medical image analysis. Key roles include Director of the Joint Initiative on AI in Medical Imaging (European Institute of Biomedical Imaging Research) and Scientific Lead of the Respiratory Disease Phenotype Observatory (ZODIAC, UNO/IAEA). He is affiliated with MIT’s CSAIL and serves on advisory boards for global AI initiatives. Education: PhD in Computer Science, Graz University of Technology (2007) M.Sc. in Mathematics, Vienna University of Technology (2003) Research Interests: Machine learning-driven precision imaging, neuroimaging, clinical data phenotyping, and cross-species brain connectivity analysis. His work bridges imaging biomarkers with biological mechanisms and large-scale clinical data integration. Grants & Funding: Over €6M in competitive grants as Principal Investigator in the last two years. Projects include ARTEMIS (fatty liver disease digital twins) and AI-POD (personalized risk scores via imaging). Awards: 2022 IS3R Emerging Leaders Club 2022 National Academy of Medicine Emerging Leader Programme 2018 Advisor, AI Mission Austria 2030 Lab & Teams: CIR Lab focuses on AI-driven medical imaging solutions. Co-founded contextflow GmbH , a MedUni spin-off developing AI software for imaging analysis.

• Quantum Computing
• Quantum Information Science
• Quantum Simulation
• +3 more

Martin Ringbauer is an Associate Professor at the Department of Experimental Physics , University of Innsbruck . His research focuses on advancing quantum computing and quantum simulation through innovative applications of trapped ion qudits and high-dimensional quantum systems . Affiliation: Department of Experimental Physics, University of Innsbruck Research Areas: Lattice gauge theories, symmetry-protected topological phases, quantum verification protocols, and fidelity estimation Key Contributions: Development of qudit-based quantum processors for simulating complex physics, experimental demonstrations of quantum error correction and joint measurements His recent publications highlight advancements in quantum simulation (lattice gauge theories, Haldane phases), quantum verification (fidelity estimation, classical validation), and qudit engineering (mixed-dimensional frameworks, entanglement optimization). These works leverage trapped ion technology as a platform for scalable and precise quantum operations.

• Cybersecurity
• Blockchain
• Machine Learning
• +12 more

Edgar Weippl is a Professor at the Faculty of Computer Science, University of Vienna, where he serves as Vice Dean and Head of the Research Group Security and Privacy. His work spans cybersecurity, blockchain, and machine learning, with teaching roles in information security and software security courses. Current Positions: Vice Dean (Faculty of Computer Science), Head (Security and Privacy Research Group), Deputy Head (Neuroinformatics & Knowledge Engineering Groups) Research Interests: Cybersecurity, blockchain, IoT security, code obfuscation, privacy technologies, reinforcement learning, and socio-technical systems security Selected Publications: Focus on blockchain privacy, VoWiFi security, code obfuscation, and reinforcement learning applications