Find Academic Supervisors

René FahrView profile

Professor

• Corporate Governance
• Business Ethics
• Sustainable Management
• +5 more

Prof. Dr. René Fahr is a Professor in the Department of Management at Paderborn University's Faculty of Business Administration and Economics, specializing in Corporate Governance and Behavioral Economics. He leads the Chair of Corporate Governance and co-directs the Behavioral Economic Engineering & Responsible Management research area at the Heinz Nixdorf Institute. His work focuses on ethical corporate decision-making, sustainable governance, and human-machine interaction, leveraging experimental methods in the BaER-Lab experimental economics laboratory. Research Interests: - Compliance and Ethical Decision-Making - Sustainable Corporate Governance - Behavioral Ethics - Experimental Economics - Human-Machine Collaboration in Industrial Systems Collaborations include industry partners like Weidmüller, PwC, and dSPACE, as well as academic partnerships such as with Queensland University of Technology. He co-founded the annual Business Ethics Forum to bridge academic and theological perspectives on business ethics. Fahr’s research outputs span over 50 publications in journals like Regional Science and Urban Economics and Customer & Service Systems . Teaching includes foundational and advanced courses on Corporate Governance, emphasizing practical applications through real-world case studies and lab experiments. He oversees student research projects and advises on master's theses in behavioral economics and corporate responsibility. Labs/Teams: Lead of the BaER-Lab and the Behavioral Economic Engineering group at the Heinz Nixdorf Institute.

Burkhard HehenkampView profile

Professor

• Applied Microeconomic Theory
• Competition Policy
• Contract Economics
• +3 more

Prof. Dr. Burkhard Hehenkamp is a Professor of Institutional Economics and Economic Policy at the University of Paderborn's Faculty of Business Administration and Economics, Department 4. He leads the Chair of Institutional Economics and Economic Policy, focusing on applied microeconomic theory with emphases on competition policy, healthcare economics, and institutional frameworks. His research explores topics such as quality competition in healthcare markets and strategic behavior in university admissions systems. Teaching responsibilities include courses like 'Cases in Competition Policy' and 'Health Economics,' while his team supports thesis supervision through centralized allocation processes. Recent activities include organizing the 21st European Health Economics Workshop and contributing to the A:RT-D Grids development project. Completed doctoral theses under his supervision include Angelika Endres-Fröhlich's work on industrial organization and networks. Research outputs emphasize practical applications of economic theory, with notable publications in journals like the Journal of Economic Behavior & Organization and Games and Economic Behavior . His work bridges theoretical analysis with real-world policy implications in healthcare, competition regulation, and institutional design.

Viktor LevandovskyyView profile

Visiting Professor

• Algebra
• Computer Algebra
• Non-commutative Gröbner Bases
• +8 more

Viktor Levandovskyy is a Visiting Professor at the Institute of Mathematics, Faculty of Mathematics and Natural Sciences, University of Kassel, Germany. He previously held the position of Assistant Professor at RWTH Aachen University and has been a postdoctoral researcher at the Research Institute for Symbolic Computation in Linz, Austria. His research focuses on Algebra, Computer Algebra, and Non-commutative Gröbner Bases , with significant applications in differential equations, symbolic computation, and control theory. His work bridges theoretical mathematics with practical algorithm development and software implementation. His recent publications demonstrate a strong trend in non-commutative algebraic computations , particularly in developing and applying Gröbner basis techniques for free algebras and Ore localizations, often implemented within the Singular computer algebra system. His work spans pure algebra (e.g., the Dixmier Conjecture) to applied symbolic methods (e.g., structural optimization). Co-editor, Journal of Symbolic Computation, Special Issue on Symbolic Computation and its Applications (2012) Co-editor, Journal of Symbolic Computation, Special Issue on Non-commutative Gröbner Bases and Applications (2007) Levandovskyy has led significant software development projects, most notably the Plural and Letterplace subsystems of Singular. He has advised students and led research teams, contributing to a network of over 5,700 reads and 769 citations. His work involves extensive collaboration with researchers in algebra and computer science. He is actively involved in the computer algebra community, presenting at major conferences like ISSAC and MTNS, and his research continues to advance algorithmic methods in non-commutative algebra.

Lê Văn BằngView profile

Professor

• Theoretical Computer Science
• Graph Theory
• Algorithms
• +3 more

Lê Văn Bằng is a Professor in the Department of Computer Science at the University of Rostock, Germany. He holds a Diplom and PhD in Mathematics from Technische Universität Berlin and completed his Habilitation in Computer Science at the University of Rostock. His office is located in Room 259, Albert-Einstein-Straße 22, 18059 Rostock, and he can be reached at van-bang.le@uni-rostock.de or by phone at +49 381 498-7675. His educational background includes: Diplom in Mathematics from Technische Universität Berlin PhD in Mathematics from Technische Universität Berlin Habilitation in Computer Science from University of Rostock Professor Le's research focuses on Theoretical Computer Science , particularly Graph Theory and Algorithms . He is known for his work on graph classes, as evidenced by the Graph Class Zoo , a comprehensive database of graph classes. His expertise extends to Complexity Theory , Operations Research , and Cryptography . He has taught courses such as Graph Models, Operations Research, Efficient Graph Algorithms, and Algorithms, Complexity and Cryptography. Professor Le does not offer internship opportunities. There is no public information regarding current grants or advising of PhD students.

Gunnar TeegeView profile

Professor

• Formal Verification
• Virtualization
• Distributed Systems
• +7 more

Prof. Dr. Gunnar Teege is a faculty member at the Institute for Computer Engineering within the Faculty of Computer Science at Bundeswehr University Munich. His career spans over two decades, focusing on distributed systems, virtualization, and formal verification of operating system components. He has led numerous research projects, including collaborations with institutions like the Runder Tisch GIS eV and the Bavarian State Office for Surveying and Geoinformation. Education: Diploma in Computer Science from Technical University of Munich (1985), Doctorate in Computer Science from TUM (1991) Affiliations: Member of GI (Gesellschaft für Informatik) and ACM (Association for Computing Machinery) Research interests include formal verification of software components for secure systems, virtualization frameworks, distributed systems, military communications, geospatial data interoperability via OpenGIS standards, computer-supported cooperative work (CSCW), and E-Learning platforms. His work often bridges theoretical and applied domains, particularly in defense IT systems and education technology. He has contributed to projects like Targeteam (XML-based adaptable teaching materials), HoBIT (high-security embedded systems), and MiKscHA (microkernel applications for high-security environments). His publications emphasize modularity, tailorability, and security in software design. Teaching activities at Bundeswehr University Munich include courses on operating systems, distributed systems, virtualization, and cybersecurity. Previously, he taught problem-based learning in computer science at TU Munich and developed virtual lectures for the Virtual University of Bavaria (vhb) from 2001–2005.

• Computational chemistry
• Molecular modeling
• Drug discovery
• +5 more

Marcus Weber serves as Head of the Computational Molecular Design research group within the Modeling and Simulation of Complex Processes department at the Zuse Institute Berlin (ZIB), which operates in close affiliation with Freie Universität Berlin. His interdisciplinary work spans computational mathematics, molecular modeling, drug discovery, and unexpected connections to Egyptology, demonstrating the broad applicability of mathematical approaches across diverse scientific domains. Dr. Weber's research interests focus on the mathematical foundations of molecular simulation and drug design: Developing advanced Markov state models for complex molecular systems Creating computational methods for efficient drug discovery Applying machine learning techniques to molecular dynamics Modeling pH-dependent receptor-ligand interactions Exploring metastable dynamics in biological systems Bridging mathematical approaches with Egyptological research His recent publications reveal a sophisticated integration of computational mathematics with practical pharmaceutical applications, particularly in opioid receptor research. The work demonstrates how mathematical modeling can identify pH-dependent drug candidates that maintain efficacy while reducing side effects. His research group has developed innovative algorithms like ISOKANN for learning Koopman eigenfunctions and has made significant contributions to understanding molecular transition rates and metastable dynamics. Dr. Weber leads multiple significant research projects including 'Drug Candidates as Pareto Optima in Chemical Space,' 'HPC and ML for Drug Discovery,' and interdisciplinary collaborations connecting mathematical approaches with Egyptology. His work on 'Mathematics and Egyptology' and 'Ancient Egyptian' demonstrates the unexpected breadth of mathematical applications. His research has direct implications for developing safer opioid medications and understanding molecular behavior in complex environments.

Pavan Laxmipathy VeluvaliView profile

Researcher

• Computational Materials Science
• Numerical Modeling and Simulation
• Computational Fluid Dynamics
• +10 more

Dr. Pavan Laxmipathy Veluvali is a Computational Materials Scientist currently working as a Postdoctoral Researcher at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg, Germany. He is a member of Prof. Dr. Peter Benner's group focused on Computational Methods in Systems and Control Theory. His work integrates numerical mathematics and materials science to advance computational workflows. His educational background includes: Ph.D in Computational Materials Science, Karlsruhe Institute of Technology, 2021 Master of Science (M.Sc) in Materials Science and Simulation, Ruhr Universitaet Bochum, 2016 Bachelor of Technology (B.Tech) in Metallurgical and Materials Engineering, Jawaharlal Nehru Technological University, 2013 Dr. Veluvali's research focuses on computational materials science, particularly phase-field modeling of solidification microstructures. His work investigates the role of diffusive-convective regimes on solidification phenomena including grain boundary grooves, dendritic growth, tip splitting, and poly-phase microstructures in binary alloys. He has expanded his expertise to include alloy solidification, electrochemistry, thin-film coatings, multiphase flows, and additive manufacturing. Recently, he has been working on computational workflows that integrate numerical mathematics and materials science, with a focus on FAIR (Findable, Accessible, Interoperable, Reusable) data principles. His publication record demonstrates a strong focus on phase-field modeling applications in materials science, with recent work shifting toward computational workflows and data infrastructure. The earlier publications (2018-2021) primarily address fundamental materials science questions using phase-field methods, while more recent work (2022-2025) shows increasing emphasis on computational frameworks, metadata abstraction, and FAIR data principles in computational science. Dr. Veluvali serves as a peer reviewer for several prestigious journals including Journal of Applied Physics, Journal of Phase Equilibria, and Journal of Physics: Condensed Matter. Currently, he is a Teaching Assistant for the Scientific Computing-I course at Otto-von-Guericke-Universität Magdeburg, where he guides students through practical implementation of numerical algorithms, shell scripting, and memory management. He is an active participant in the research community, regularly presenting his work at conferences including SIAM CSE, DMV Annual Meeting, and MaRDI workshops. His research is supported by the Max Planck Institute and likely through collaborative projects with academic and industry partners.

Feliks NüskeView profile

Research Professor

• Data-driven modeling
• Molecular simulation
• Koopman operator theory
• +6 more

Dr. Feliks Nüske is a Max Planck Group Leader at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg, leading the Data-driven Modeling of Complex Physical Systems research group. He also holds a position as Guest Professor at Freie Universität Berlin (2023-2024). His research bridges applied mathematics, data science, and molecular simulation to develop novel algorithms for understanding complex physical systems at the molecular level. Dr. Nüske's educational background includes: Ph.D. in Mathematics from Freie Universität Berlin (2012-2017) Postdoctoral research at Universität Paderborn (2019-2022) and Rice University (2017-2019) His research focuses on developing data-driven methods that combine physical insights with machine learning to extract meaningful information from molecular simulation data. Key areas include Koopman operator theory for analyzing nonlinear dynamical systems, dimensionality reduction techniques, tensor methods for efficient computation, and kinetically consistent coarse-graining approaches. His work enables more efficient modeling of complex molecular processes that would otherwise be computationally prohibitive. Dr. Nüske's publication record shows a consistent trajectory of advancing both the theoretical foundations and practical applications of data-driven modeling in molecular science. His recent work emphasizes error analysis for data-driven models, control of stochastic systems, tensor-based dimensionality reduction, and methods to preserve kinetic properties in coarse-grained models. These contributions address critical challenges in scaling molecular simulations to biologically relevant timescales and system sizes. Dr. Nüske actively collaborates with researchers worldwide and has established partnerships with leading institutions including Freie Universität Berlin, Rice University, and TU Ilmenau. His collaborative network spans multiple disciplines, connecting mathematicians, chemists, and computational scientists. Dr. Nüske advises several Ph.D. students at the Max Planck Institute, including Vahid Nateghi, Lei Guo, Minakshi Verma, and Hauke Sprink. He has organized workshops on Uncertainty Quantification for molecular systems and regularly presents at major international conferences including SIAM MS, MTNS, and IMSI workshops. His research group continues to push the boundaries of what's possible in computational molecular science through innovative mathematical approaches.

Kenny JosephView profile

Associate Professor

• Computational Social Science
• Social Inequality
• Machine Learning
• +9 more

Kenny Joseph is an Associate Professor in the CSE Department at the University at Buffalo, leading the Computation and Equity Lab (cubelab) . His work bridges computational methods with social inequality research, focusing on predictive modeling for social good and analyzing systemic disparities through digital traces. Current affiliation: University at Buffalo Previous positions: Postdoc at LazerLab (Northeastern), Fellow at Harvard's Institute for Quantitative Social Science Research Interests: Combining machine learning with social theory to address structural inequalities in areas like foster care systems, neighborhood change, and gender disparities in academia. Key methodologies include agent-based modeling, network analysis, and large-scale data mining. Publication Trends: Recent work focuses on Social media dynamics and misinformation Equity-focused predictive modeling Political communication analysis Identity expression in digital spaces Urban planning applications Additional Contributions: Developer of computational tools for location extraction (GALLOC) and self-presentation analysis, with applications in disaster response and social inequality research.

Fabio MogaveroView profile

Associate Professor

• Theoretical Computer Science
• Formal Verification
• Temporal Logic
• +12 more

Fabio Mogavero is an Associate Professor in Theoretical Computer Science at the Department of Electrical Engineering and Information Technology, Università degli Studi di Napoli Federico II. His research spans formal specification, verification, and synthesis of systems, with a strong focus on logics, automata, games, and database theory. Ph.D. in Computer Science, Università degli Studi di Napoli Federico II, 2011 M.Eng. in Computer Science Engineering, Università degli Studi di Napoli Federico II, 2007 B.Eng. in Computer Science Engineering, Università degli Studi di Napoli Federico II, 2005 His primary research interests include formal verification, temporal and strategic logics, automata over infinite structures, decidability, and database theory—particularly bag semantics. He has made significant contributions to the theory of parity and mean-payoff games, strategy logic, and SHACL/RDF validation. His recent work explores fragments of first-order and monadic second-order logic, and he actively publishes in top venues such as LICS, ICALP, and IJCAI. The most recent articles highlight a sustained focus on logical characterizations (e.g., automata-theoretic models for temporal logics), game-solving algorithms, and foundational database theory, especially around SHACL and multiset semantics. His work bridges theoretical computer science with practical formal methods. Scientific Awards and Recognition: Erdös number at most 3 (via Erdös → J.H. Spencer → M.Y. Vardi → F. Mogavero) Fabio Mogavero has served on the program committees of major conferences including IJCAI, AAMAS, ECAI, and LICS. He has co-edited proceedings for the Strategic Reasoning (SR) and OVERLAY workshops. He has collaborated with leading researchers such as Moshe Y. Vardi, Orna Kupferman, and Michael Benedikt. He has held postdoctoral and teaching positions at the University of Oxford and Università di Verona. He is actively involved in the theoretical computer science community through conference organization and editorial work. He maintains research collaborations across Europe and the U.S. and continues to contribute to foundational and applied aspects of logic in computer science.

Mohamed Faouzi AtigView profile

Professor

• Formal Verification
• Concurrency
• Model Checking
• +7 more

Mohamed Faouzi Atig is a Professor in Computer Systems at the Department of Information Technology , Uppsala University since July 2021. Previously, he served as Senior Lecturer (Associate Professor) from June 2018 to June 2021 and as Associate Senior Lecturer (Assistant Professor) from June 2014 to May 2018. Current: Professor, Uppsala University (2021–present) Senior Lecturer, Uppsala University (2018–2021) Associate Senior Lecturer, Uppsala University (2014–2018) Researcher, Uppsala University (2012–2018) Post-doctoral Researcher, Uppsala University (2010–2012) Education : PhD in Computer Science from University of Paris Diderot-Paris 7 (2010) Docent (Habilitation) in Computer Systems from Uppsala University (2017) Research Interests : A multidisciplinary researcher in Formal Verification , focusing on Model Checking and Automata Theory for Concurrency and Weak Memory Models . His work spans Formal Methods , Software Verification , and Logics for system correctness. Publication Trends : His recent works (2015–2024) analyze Hardware Memory Models (Intel-x86, TSO), String Constraint Solving , and Stateless Model Checking under relaxed memory semantics. He applies Automata Theory to Persistent Memory verification and Concurrency problems. Committee Roles : Active in program committees for POPL (2020–2025), PLDI (2017–2024), and VMCAI (2017).

Jonathan AldrichView profile

Professor

• Programming Languages
• Software Engineering
• Verification
• +3 more

Jonathan Aldrich is a Professor at Carnegie Mellon University's School of Computer Science, with joint appointments in the Software and Societal Systems Department and Computer Science Department. He directs the Master of Software Engineering program (as of July 2025) and previously led the Software Engineering Ph.D. program. Aldrich teaches courses in programming languages, software engineering, and program analysis. Education: Ph.D. in Computer Science and Engineering, University of Washington (2003) M.S. in Computer Science and Engineering, University of Washington (1999) B.S. in Engineering and Applied Science (Computer Science), Caltech (1997) Research Focus: Aldrich's work bridges programming languages and software engineering to improve software quality and productivity. His research explores how structural and behavioral design aspects can be expressed in source code, enabling better tooling and error reduction. Key innovations include gradual verification systems, typestate-oriented programming, and ownership models for security. His projects span blockchain safety (Obsidian), concurrency (AEminium), and visualization (Penrose). Publication Trends: Aldrich's 15 most recent articles reflect a strong emphasis on language-based security, formal verification (especially gradual verification techniques), and human-centered language design. His work increasingly integrates empirical studies to evaluate usability in advanced type systems. Awards: NSF CAREER Award (2006) Dahl-Nygaard Junior Prize (2007) ICSE Most Influential Paper Award (2012) DARPA Computer Science Study Group (2007) William Chan Memorial Dissertation Award (2003) Leadership & Service: Aldrich directs graduate programs, co-authored the textbook 'Programming Language Pragmatics,' and serves on the ACM Publications Board. As CTO of Noteful, he develops educational music technology. He has chaired program committees for OOPSLA, ECOOP, and SPLASH conferences.

Wolfgang GaißmaierView profile

Professor

• Judgment and decision making
• Individual differences in decision making
• Risk perception and communication
• +4 more

Prof. Dr. Wolfgang Gaißmaier is a full-time faculty member at the Department of Psychology, University of Konstanz, specializing in Social Psychology and Decision Sciences. His research explores judgment and decision-making processes under uncertainty, with particular focus on individual differences in decision strategies, risk perception and communication, medical decision-making, ecological rationality, and heuristic modeling. Current research projects include "Political Elites and Inequality: Information, Heuristics and Policy" Co-developer of the riskyrApp and FFTrees R packages for risk literacy and decision modeling Key contributor to the Collective Behaviour Cluster of Excellence at University of Konstanz His recent publications examine cognitive biases in statistical information processing, the effectiveness of visual risk communication tools, and the psychological foundations of collective behavior. He collaborates extensively with researchers across psychology, economics, and computer science, particularly with Dr. Hansjörg Neth and Dr. Helge Giese. Major contributions include: Developing computational models of decision heuristics Investigating social learning mechanisms in risk perception Advancing tools for transparent risk communication Exploring the narrative bias in health decision-making Studying group dynamics in knowledge diffusion

• Simulation
• Computer Science
• Financial Markets
• +8 more

Prof. Dr. Oliver Hein is a Professor at the Department of MND, Technische Hochschule Mittelhessen. His research focuses on simulation , computer science , and their applications in financial markets , economic forecasting , and behavioral economics . Research Interests: Simulation, Computer Science, Financial Markets, Economic Forecasting Contact: oliver.hein@mnd.thm.de | +49 (0) 6031 604 3478 His work explores network centrality , informational cascades , and scale-free networks in financial contexts. Publications like "Algorithmischer Handel" (2022) highlight his recent focus on machine learning and AI in trading, while earlier studies (2005-2015) examine behavioral biases and communication topologies in bond markets.

• Statistics
• Applied Mathematics
• Systems Biology
• +2 more

Dr. Hannes Matuschek is a Researcher in the Department of Applied Mathematics at the University of Potsdam, Germany, with office space 2.09.1.24 and contact email hannes.matuschek@uni-potsdam.de. He actively participates in the institute's academic events including working group seminars and colloquia. Research Interests: His work spans Statistics, Applied Mathematics, Systems Biology, and Biomechanics. Key contributions include statistical methodology for linear mixed models (addressing Type I error/power tradeoffs and interaction effects), smoothing spline ANOVA for eye movement analysis in reading, stochastic modeling of gene regulatory networks, and vector field manipulations on spherical domains. His research bridges theoretical frameworks with applications in cognitive science, systems biology, and fraud detection. Publication Trends: His 12 publications (2012-2019) reveal a trajectory from computational systems biology (stochastic biochemical kinetics tools like iNA) toward statistical methodology development. Early work focused on noise approximation in gene networks, evolving into eye-tracking analysis and vector field mathematics, demonstrating consistent integration of advanced statistics with domain-specific challenges across biological and cognitive sciences. Scientific Awards: No awards were mentioned in the provided materials. Advising and Grants: No information was provided regarding student supervision, grant funding, or research collaborations. Labs and Teams: He operates within the Applied Mathematics research group at the University of Potsdam, contributing to seminars and events in analysis and interdisciplinary applications as evidenced by his institutional presence.