Find Academic Supervisors

Daniel HaraborView profile

Associate Professor

• Artificial Intelligence
• Pathfinding Algorithms
• Optimization
• +3 more

Daniel Harabor is an Associate Professor in the Department of Data Science & AI at Monash University, Australia. He holds a PhD and BSc (Honours) in Computer Science from the Australian National University (ANU). His research focuses on pathfinding algorithms, multi-agent systems, and optimization, with notable contributions to multi-agent pathfinding (MAPF), transportation routing, and constraint-based reasoning. He leads or collaborates in projects like the 2023 MAPF Competition and the Future of Urban Routing initiative. Education: PhD in Computer Science, ANU (2014) BSc (Honours) in Computer Science, ANU (2007) Research Interests: His work emphasizes practical and efficient solutions for combinatorial search problems, including real-time pathfinding, public transport optimization, and large-scale multi-agent coordination. He develops algorithms for dynamic environments with applications in robotics, urban planning, and logistics. Awards: DECRA Research Fellowship (Australian Research Council) Projects & Grants: He has secured funding for projects such as 'Personalised Public Transport' (2019–2025) and 'Improved Constraint Reasoning for Robust Multi-agent Path Planning' (2021–2024). His work often involves collaboration with global experts in AI and robotics. Labs & Teams: Active in the Data Science & AI research group at Monash, contributing to MAPF competitions and open-source pathfinding tools like JPS (Jump Point Search).

Christoph LenzenView profile

Professor

• Distributed Computing
• Clock Synchronization
• Randomized Load Balancing
• +5 more

Christoph Lenzen is a Professor at CISPA Helmholtz Center for Information Security since July 2021. Previously, he served as a Group Leader at the Max Planck Institute for Informatics (2014-2021), and held postdoctoral positions at MIT CSAIL (2013-2014), Weizmann Institute (2012), and Hebrew University (2011). Research Interests Design and analysis of distributed algorithms Clock synchronization and adversarial fault tolerance Randomized and self-stabilizing systems Hardware algorithms for fault-tolerant systems Grants and Awards ERC Proof-of-Concept Grant (2021) ERC Starting Grant (2017-2022) ETH Zurich Medal for Outstanding Thesis (2011) Education Ph.D. in Computer Science (2011), ETH Zurich Diploma in Mathematics (2007), University of Bonn Teaching Clock Synchronization and Adversarial Fault Tolerance (2022 winter) How To Clock Your Computer (2022 summer) Theory of Distributed Systems (2019 winter, 2020 winter, 2018 winter, 2017 winter, 2016 winter, 2015 winter)

Rudesindo Núñez QueijaView profile

Professor

• Queueing Theory
• Stochastic Modeling
• Operations Research
• +7 more

Rudesindo Núñez Queija is a Professor at the Korteweg-De Vries Institute, Faculty of Science, University of Amsterdam (UvA), and a Scientific Staff Member in the Stochastics Department at Centrum Wiskunde & Informatica (CWI), Amsterdam. His work bridges theoretical stochastic modeling and practical applications in transportation and network systems. University: University of Amsterdam Research Institute: Centrum Wiskunde & Informatica (CWI) Department: Stochastics Role: Professor and Scientific Staff Member His research focuses on queueing theory, stochastic models, and dynamic systems, particularly in the context of transportation networks and service systems. He investigates problems such as dynamic routing under uncertainty, traffic congestion modeling, optimal dispatching in queues, and performance analysis of polling and processor-sharing systems. His methodological toolkit includes Markov decision processes, fluid approximations, heavy-traffic analysis, and perturbation techniques. The 15 most recent publications highlight a strong trend in applying stochastic modeling to real-world transportation challenges—such as intelligent routing, bottleneck dynamics under uncertainty, and urban traffic control—while also advancing fundamental queueing theory. His work frequently appears in high-impact journals like Transportation Research Part B , Queueing Systems , and Operations Research Letters . Notable scientific recognition includes: Applied Probability Trust Award for his PhD thesis on Processor-Sharing Models (2000) He has co-supervised several PhD students, including Daphne van Leeuwen, Peter Kovacs, and Nikki Levering, and has been actively involved in major research grants, such as the NWO Networks program and the NWO Sustainable Logistics project 'Dynafloat'. He teaches courses such as 'Statistics for Forensic Science', demonstrating a broad educational impact. His research is supported by funding from the Netherlands Organisation for Scientific Research (NWO), and he collaborates extensively within the Dutch academic and research community. He is affiliated with research groups at both CWI and UvA, particularly within the Stochastics and Networks domains, contributing to large-scale interdisciplinary projects focused on modeling and optimizing complex systems.

• Algorithms
• Computational Geometry
• Wireless Communication
• +4 more

Stefan Funke is a researcher at the University of Stuttgart, Germany, with a focus on algorithms and computational geometry. His work spans wireless communication, route planning, and trajectory analysis. Research Interests: Algorithms, Computational Geometry, Wireless Communication, Route Planning, Trajectory Segmentation His recent publications (2024-2025) explore topics like 3D epithelial cell dynamics, graph radius computation, and polyline simplification, emphasizing scalability and efficiency. Earlier works (2017-2019) investigate contraction hierarchies, energy-efficient routing, and trajectory storage systems. Stefan collaborates frequently with Sabine Storandt, Claudius Proissl, and Tobias Rupp. He applies geometric methods to problems in wireless networks, road systems, and data structures, with a recurring emphasis on optimization and robustness.

• Operations Research
• Theoretical Operations Research
• Applied Operations Research
• +8 more

Evangelos F. Magirou is a Professor of Operations Research at the Department of Informatics, School of Information Sciences and Technology, Athens University of Economics and Business (AUEB), where he has served since 1986. His academic career includes significant administrative roles including Chairman of the Faculty Union at AUEB since 1994, Deputy Chairman of the Department of Informatics since 2003, and Member of the Governing Board of the Public Power Corporation since 2004. His educational background includes: PhD in Decision and Control Sciences, Harvard University (1972-76) MS in Decision and Control Sciences, Harvard University (1971-72) BS in Electrical Engineering, Princeton University (1967-71) Professor Magirou's research spans theoretical and applied operations research with particular emphasis on applications to Greek business environment challenges. His work demonstrates consistent focus on finance, shipping, and production systems, with fundamental contributions to optimization, probabilistic models, and quantitative methods. His research trajectory shows evolution from early theoretical work in control systems and game theory to applied research in shipping economics and financial mathematics, with recent work addressing contemporary challenges including infectious disease response and American option pricing. His publication record reveals a strong interdisciplinary approach, bridging operations research with computer science, economics, and maritime transport. The 15 most recent publications indicate continued research productivity with applications spanning finance (option pricing algorithms), public health (infectious disease response), shipping (vessel positioning), and computer security (spam modeling). Professor Magirou has held numerous leadership positions including: Chairman of the Executive Committee for the MSc Program in Business Mathematics Chairman of the Hellenic Procurement Institute (1994-97) Vice Chairman of the Energy Coordination Committee (1993-95) Member of the National Energy Council's Scientific Secretariat (1977-85) He has been actively involved with professional organizations including INFORMS (Institute for Operations Research and the Management Sciences) and the Technical Chamber of Greece. His teaching responsibilities include courses in Elementary and Intermediate Mathematics of Finance, Operations Research, Game Theory, and Decision Theory, for which he has developed extensive teaching materials available in Greek.

• Operations Research
• Management Science
• Optimization
• +5 more

Evangelos F. Mageirou serves as Professor of Operations Research at the Department of Informatics, School of Information Sciences and Technology, Athens University of Economics and Business (AUEB), a position held continuously since 1986. Previously, he worked at the Scientific Secretariat of the National Energy Council under Greece's Ministries of Coordination, Industry and Energy from 1977-1986. His academic credentials include: PhD in Decision and Control Sciences, Harvard University (1972-1976), Thesis: 'Topics in the Analysis of Interconnected Systems' MS in Decision and Control Sciences, Harvard University (1971-1972) BS in Electrical Engineering, Princeton University (1967-1971) Mageirou's research centers on Theoretical and Applied Operations Research with significant applications to the Greek business environment, particularly in finance, shipping logistics, and production systems. His foundational work spans optimization theory, probabilistic modeling, and quantitative methods development. The consistent publication record through 2020 demonstrates enduring scholarly productivity in his core domains. Analysis of recent publications reveals three dominant research trajectories: maritime logistics optimization (vessel speed/positioning studies), game-theoretic security applications (spam email modeling), and control theory extensions (policy iteration algorithms). These threads demonstrate methodological continuity from his early work on interconnected systems to contemporary applications in financial mathematics and pandemic response modeling.

• High-Performance Computing
• Parallel Computing
• Heterogeneous Computing
• +7 more

Alberto José Gonçalves Carvalho Proença serves as Full Professor in the Department of Informatics at the School of Engineering, University of Minho, and holds the position of Senior Researcher with Dr. habil at Centro ALGORITMI. His academic career spans over 45 years, beginning at the University of Porto in 1976 before transitioning to the University of Minho in 1977 where he has remained ever since. His educational foundation includes: Licentiate in Electrical Engineering from Coimbra, Portugal (1976) MSc in Digital Electronics from UMIST, Manchester, UK (1979) PhD from Manchester, UK (1982) Dr. habil (Habilitation) from the University of Minho (1998) Professor Proença's research spans from digital electronics to cutting-edge high-performance computing, with core expertise in computer architecture, parallel computing, and heterogeneous computing systems. His work bridges theoretical computer science with practical applications across diverse domains including particle physics (LHC data analysis), forensic science (DNA library systems), materials science (crystallographic imaging), and cultural heritage preservation. Current research focuses on optimizing computational efficiency across heterogeneous resources for scientific applications, addressing challenges in big data processing, parallel random number generation, and scheduling algorithms for distributed environments. Throughout his career, Professor Proença has successfully supervised numerous MSc dissertations and PhD theses while contributing significantly to institutional computing infrastructure. He chaired the University Computer Centre for 17 years (1985-2002), establishing Portugal's first national parallel computing service. For 11 years (2006-2017), he led the Advanced Computing theme in the University of Texas at Austin-Portugal cooperation program. Since 2005, he has directed the university's SeARCH heterogeneous computing cluster, supporting research across multiple scientific disciplines. His research group has developed several influential frameworks including JaSkel (Java Skeleton-Based Framework for Cluster and Grid Computing), HEP-Frame (for LHC data analysis), Im2Cr (crystallographic imaging tool), and CROSS-Fire (risk management decision support system). These platforms demonstrate his commitment to translating theoretical advances into practical tools that address real-world scientific and societal challenges.

Grégoire SutreView profile

Research Fellow

• Formal Verification
• Model Checking
• Infinite-State Systems
• +7 more

Grégoire Sutre is a CNRS Research Fellow at LaBRI, University of Bordeaux, specializing in formal verification and model checking of infinite-state and concurrent systems. His research includes theoretical and practical aspects of verification, with applications ranging from systems code to biological models. Research Interests: Model-checking of safety properties Infinite-state and distributed systems Abstraction refinement techniques Vector addition systems and Petri nets Software verification and concurrent systems Teaching: He currently teaches Software Verification at the Master 2 level, with lab sessions in OCaml focusing on abstract interpretation and static analysis techniques. Students: He supervises several PhD students working on reachability, concurrency, and binary analysis. Projects: He has led or participated in multiple ANR-funded projects such as BraVAS, ReacHard, VACSIM, and SPaCIFY, focusing on formal methods and verification of critical systems.

Thomas Kjær RasmussenView profile

Associate Professor

• Transportation Science
• Transportation Systems Modelling
• Choice Modeling
• +12 more

Thomas Kjær Rasmussen is an Associate Professor and Head of the Transportation Systems Modelling section at the Department of Technology, Management and Economics, Technical University of Denmark (DTU). His research lies at the intersection of transportation science, behavioral modeling, and urban mobility, with a strong emphasis on sustainable transport systems. His research interests include transportation systems modelling , route choice behavior , cyclist and pedestrian safety , stochastic user equilibrium , and the application of crowdsourced data to model near-crashes and travel behavior. He actively contributes to advancing choice modeling techniques, particularly in integrating behavioral realism into dynamic traffic assignment. The recent publications highlight a consistent focus on improving the behavioral realism of route choice models, addressing route overlap, and leveraging novel data sources such as bicycle airbag helmet sensors. These works span methodological advances in equilibrium modeling and empirical applications in urban networks like Copenhagen. Scientific Awards: The International Choice Modeling Conference (ICMC) award for the Most innovative application of choice modelling (2022) Advising and Grants: Rasmussen is actively involved in supervising multiple PhD projects, serving as main supervisor or co-supervisor in areas such as human energy expenditure in mobility, dynamic traffic assignment, bicyclist behavior, and next-generation route choice models. These projects reflect sustained research funding and institutional support for advanced transportation research at DTU. Labs and Research Teams: He is a key member of a vibrant research group in transportation modeling at DTU, collaborating closely with Prof. Otto Anker Nielsen and other researchers such as Luke C. Duncan, David P. Watling, and Marie Paulsen. The team focuses on behavioral realism in transport models and leverages large-scale datasets for empirical validation.

• Graph Algorithms
• Convex Optimization
• Fine-Grained Complexity Theory
• +3 more

Rasmus Kyng is an Assistant Professor at the Department of Computer Science, ETH Zurich, since Fall 2019. He focuses on developing fast algorithms for graph problems, convex optimization, and structured linear equations, with a specialization in fine-grained complexity theory and dynamic graph algorithms. Assistant Professor, Department of Computer Science, ETH Zurich (2019–present) Postdoc, Theory of Computation Group, Harvard (2018–2019) Research Fellow, Simons Institute, UC Berkeley (Fall 2017) His research explores the intersection of graph algorithms, optimization, and complexity, particularly through dynamic graph data structures, sparsification, and applications in machine learning. Recent work includes breakthroughs in almost-linear time algorithms for network flow problems. Key trends in his publications include: Advancements in dynamic graph algorithms and data structures Applications of convex optimization to graph theory Connections between matrix theory and algorithmic efficiency Derandomization techniques for algorithmic speed Expander graph-based oblivious routing Sparsification and low-congestion vertex sparsifiers Scientific recognition includes the FOCS Best Paper Award (2022), ICBS Frontiers of Science Award (2022), and the Machtey Award for Best Student Paper (2017). His group mentors PhD candidates and postdocs, including Ming Ding , Federico Soldà , Simon Meierhans , Aurelio Sulser , and Wuwei Yuan . Research is supported by Swiss National Science Foundation grants (project no. 200021 204787, starting grant no. TMSGI2 218022).

Stephan HolzerView profile

Researcher

• Distributed algorithms
• Graph theory
• Wireless networks
• +3 more

Stephan Holzer is a computer scientist and mathematician currently affiliated with the Massachusetts Institute of Technology , where he works within the Computer Science and Artificial Intelligence Laboratory (CSAIL) . He has held postdoctoral positions at MIT (2013–2017) and visiting roles at Harvard and ETH Zurich. His expertise lies in the theory of distributed systems, with a focus on efficient algorithms for networks. Education: Stephan earned his Diplom (M.Sc.) and B.Sc. from TU Munich within Germany’s TopMath excellence program (2006–2008), followed by a Ph.D. in Computer Science from ETH Zurich (2009–2013) under the supervision of Prof. Roger Wattenhofer. Research Interests: His work spans distributed algorithms , graph theory , wireless communication , communication complexity , and network optimization . He particularly explores how devices in large-scale networks can compute distances, disseminate information, and coordinate despite interference and limited resources. Publications & Impact: Stephan has published extensively in premier venues such as PODC, DISC, SODA, and TCS. His recent work addresses security of crypto-currencies, leader election in wireless models, and approximation algorithms for shortest-path problems, reflecting a blend of theoretical rigor and practical relevance. Scientific Awards & Honors: Best Paper Award, 24th SIROCCO 2017 Member, Young Academy | Mainz 2016 Nominated delegate, Global Young Scientist Summit 2016 Participant, Heidelberg Laureate Forum 2013 Teaching & Mentoring: Stephan co-created and lectures the MIT graduate course 6.S899 Distributed Graph Algorithms with Profs. Mohsen Ghaffari and Nancy Lynch. He has mentored numerous undergraduate and master’s students through UROP, UAP, and thesis projects at MIT and ETH Zurich. Service: He has served on the program committees of SPAA, ICDCN, SSS, SOFSEM, and ALGOSENSORS, and regularly reviews for top-tier journals and conferences in distributed computing and algorithms.

Gabriele RögerView profile

Lecturer

• Classical Planning
• Heuristic Search
• Artificial Intelligence
• +4 more

Gabriele Röger is a Lecturer and Senior Research Associate at the University of Basel , affiliated with the Department of Mathematics and Computer Science . She previously earned her Dr. rer. nat. in 2014 from the University of Freiburg. Research Interests : Her work focuses on classical planning and heuristic search , with significant contributions to planning systems like Fast Downward and Temporal Fast Downward. She has developed advanced techniques for cost partitioning , unsolvability certification , and merge-and-shrink frameworks , advancing the field of automated planning . Recent Publications (2025-2018) highlight innovations in stochastic shortest path problems , state space reduction , certificate generation , and planning heuristics based on linear programming and symmetry analysis . Awards & Recognition : ICAPS 2024 Influential Paper Award Best Student Paper Runner-Up (ICAPS 2022) SoCS 2020 Best Paper Award ICAPS 2019 Best Paper Award ICAPS Best Dissertation Award (2016) Multiple International Planning Competition wins (2008-2018) Leadership Roles : Co-Chair, SoCS 2013 Program Co-Chair, ICAPS 2018 Associate Program Co-Chair, AAAI 2021 ICAPS President (2022-2024) Member, JAIR Editorial Board Lab Affiliation : Actively contributes to the AI Group at the University of Basel, collaborating on heuristic search and planning systems development.

Juan Vidal PugaView profile

Professor

• Game Theory
• Economics
• Cost Allocation
• +4 more

Juan Vidal Puga is a Full Professor ( Professor Catedrático ) at the Department of Statistics and Operations Research, University of Vigo, since August 2022. He holds a PhD in Mathematical Sciences (2002) with an Extraordinary Doctoral Award and is accredited as a University Professor in both Science and Social/Legal Sciences branches. Research Areas: Game Theory, Economics, Environmental Sciences, Public Management Key Projects: Game theory and economic inequalities (2021-2025) , Climate change resilience (2022-2024) His research focuses on cooperative game theory, particularly bargaining models, cost allocation in network problems (minimum cost spanning trees, land rental agreements), and applications to environmental risk prevention. Recent work includes developing efficient Shapley-type solutions for fuzzy games and analyzing freight transportation models. Scientific Awards : Erasmus scholarship (1994-1995) Extraordinary doctoral award (2002) He has supervised two PhD students and evaluated international journals like Journal of Economic Theory , Games and Economic Behavior , and European Journal of Operational Research . Teaching includes courses on Game Theory in Public Management, Quantitative Methods, and Microsoft Office workshops.

Florian RöselView profile

Researcher

• Optimization under Uncertainty
• Data Science
• Operations Research
• +4 more

Dr. Florian Rösel is a researcher affiliated with the Department of Data Science at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). He works under the Professorship of Optimization under Uncertainty & Data Analysis led by Prof. Dr. Frauke Liers, focusing on data-driven optimization techniques and their applications in aviation logistics and complex system modeling.

Eric RuppertView profile

Associate Professor

• Distributed Computing
• Shared-Memory Algorithms
• Data Structures
• +3 more

Eric Ruppert is an Associate Professor in the Department of Electrical Engineering & Computer Science at York University, where he has taught computer science since 2000. He is a member of the Theory of Computing Group and teaches foundational computer science courses including algorithms and theory of computation. He has served on program committees for major conferences including PODC 2025 and WADS 2025. Ruppert received his education at the University of Toronto. He has held postdoctoral positions at Brown University and served as a visiting professor at the École Polytechnique Fédérale de Lausanne. His research focuses on the theory of distributed computing, with particular emphasis on algorithm design and lower bound proofs. His recent work has centered on shared-memory data structures for multi-core architectures. His research interests span distributed algorithms, computational complexity, and the theoretical foundations of concurrent systems. He has made significant contributions to understanding the computational power of population protocols, consensus problems, and non-blocking data structures. His publication record shows a consistent focus on distributed computing theory, with recent work emphasizing non-blocking and wait-free data structures. Over the past decade, his research has increasingly addressed challenges in concurrent programming for multi-core systems, developing efficient algorithms for queues, deques, and binary search trees that provide strong progress guarantees. Ruppert has been actively involved in the distributed computing research community, serving on program committees for major conferences including PODC and WADS. His work has been published in top-tier venues such as Distributed Computing, Journal of the ACM, and proceedings of ACM SIGACT/SIGOPS conferences. At York University, Ruppert teaches courses on algorithms, theory of computation, and computational complexity. He has supervised numerous graduate students through project courses and thesis work. He is known for his dedication to teaching, including coaching students for the annual ACM programming contest. Ruppert is a member of the Theory of Computing Group at York University, which focuses on foundational aspects of computer science including algorithms, complexity theory, and distributed systems. His work bridges theoretical computer science with practical applications in concurrent and parallel computing.