Marc Alexa is a Professor at the Technische Universität Berlin , leading the Department of Computer Graphics within the Institute of Computer Engineering and Microelectronics . His research spans computational geometry, rendering, and human-computer interaction, with a focus on differentiable rendering, mesh processing, and geometric modeling. PhD (2002) and MSc (1997) from Technische Universität Darmstadt under advisors Prof. Encarnacao and Prof. Gross (ETH Zurich) Research interests include: Differentiable rendering frameworks Geometric stylization and manifold reconstruction Optimization of polygonal and tetrahedral meshes Eye-tracking applications in mental imagery and visual perception Scientific awards include: ACM Fellow (2024) SIGGRAPH Academy inductee (2022) ERC Advanced Grant for geometric computation (2022) Eurographics Fellow (2018) Engineering Science Prize (2012) His recent publications (2023-2025) focus on differentiable acoustic path tracing, Poisson manifold reconstruction, and shadow mapping optimization. He has served as Editor-in-Chief of ACM Transactions on Graphics (2018-2021) and chaired key conferences like SIGGRAPH 2013 Technical Papers .
Gregory Gutin is Professor of Computer Science at Royal Holloway, University of London since 2000, with concurrent appointments as Distinguished Scientist at Shenzhen Institute of Advanced Technology (2024-2027) and Distinguished Professor at Nankai University (2024-2027). He earned his MSc in Mathematics from Gomel State University (1979) and PhD with distinction from Tel Aviv University under Noga Alon (1993), following early career positions in Belarusian research institutes. His academic journey includes visiting roles at Odense University and a lectureship at Brunel University prior to his current position. His research establishes foundational contributions across graph theory, combinatorial algorithms, and information security, with particular expertise in parameterized complexity and access control systems. This work manifests in over 250 publications exceeding 11,900 citations, including monographs translated into Chinese and editorial leadership for specialized volumes. Recent 2025 publications demonstrate continued innovation across three interconnected domains: theoretical graph structures (tournament analysis, digraph polynomials), algorithmic efficiency (GPU-accelerated simulation, matching market optimizations), and parameterized complexity frameworks—showcasing his unique ability to bridge abstract theory with practical computational challenges. His accolades include the Kirkman Medal (1996), Royal Society Wolfson Research Merit Award (2014-2018), dual academy memberships (Academia Europaea 2017, AAIA 2021), and unprecedented four consecutive ACM SACMAT best paper awards (2015-2022), culminating in the 2022 AAIA Outstanding Contribution Award: Kirkman Medal of International Institute of Combinatorics and Applications (1996) Royal Society Wolfson Research Merit award (2014-2018) Elected to Academia Europaea (2017) Elected to AAIA (2021) Best paper award at ACM SACMAT 2015 Best paper award at ACM SACMAT 2016 Best paper award at ACM SACMAT 2021 Best paper award at ACM SACMAT 2022 Amity Global Academic Excellence Award (2019) AAIA Outstanding Contribution Award (2022) Professor Gutin has supervised six doctoral students and directed six major research initiatives including EPSRC-funded workflow verification systems and Leverhulme Trust security frameworks. He actively contributes to the Centre for Algorithms and Applications and Centre for Intelligent Systems, with current projects exploring parameterized optimization techniques and security-aware computational models through 2027.
Fedor Fomin is a Professor at the Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Bergen. He is renowned for his contributions to theoretical computer science, particularly in parameterized complexity and exact exponential algorithms, earning him the ACM Fellow 2023 distinction. University: University of Bergen School: Faculty of Mathematics and Natural Sciences Department: Department of Informatics Academic Rank: Professor Research Interests: Fomin's work focuses on designing efficient algorithms for computationally hard problems, with a specialization in parameterized and exact exponential algorithms. His research spans graph theory, combinatorial optimization, and computational complexity, addressing foundational challenges in sparse graphs, planar graphs, and treewidth-based techniques. Key Contributions: His research includes kernelization methods, subexponential algorithms for planar graphs, and novel approaches to edge domination and satisfiability problems. He has published extensively in top venues like STOC, FOCS, and SODA. Awards: ACM Fellow 2023 EATCS Award 2019 ERC Advanced Grant 2016 Nordic Researcher Award in Theoretical Computer Science 2010 Publications: His work covers parameterized algorithms for cluster editing, feedback vertex sets, and induced subgraph problems, with applications in computational biology and network science. Collaborations: Fomin collaborates with leading researchers in theoretical computer science, including Petr Golovach and Saket Saurabh, mentoring numerous PhD students and shaping the field's future.
Neil Julien Ross is an Associate Professor in the Department of Mathematics at Dalhousie University. His research primarily focuses on quantum computing and quantum programming languages, with extensive contributions to quantum circuit design, optimization, and formal verification methods. He maintains an active research profile with numerous publications in top-tier quantum computing conferences and journals. His research interests span: Quantum circuit synthesis and optimization techniques Formal methods for quantum programming languages (e.g., Proto-Quipper) Algebraic structures in quantum computation Quantum gate universality and resource theory Category theory applications in quantum information Ross's recent publications demonstrate a consistent focus on advancing quantum circuit design methodologies, particularly through symbolic synthesis techniques and formal verification approaches. His work frequently bridges theoretical computer science, algebraic structures, and practical quantum implementation challenges.
Marc Roth is a Lecturer in Theoretical Computer Science at the School of Electronic Engineering and Computer Science, Queen Mary University of London, and an Associate Member of the Department of Computer Science at the University of Oxford. He previously held research positions at Oxford, including Senior Research Associate in Algorithms and Complexity Theory and Junior Research Fellow at Merton College. His research focuses on computational counting problems, particularly the multivariate and exact complexity of infeasible counting problems, with applications in network analysis, bioinformatics, and graph neural networks. Key areas include motif counting in higher-order networks, parameterized and fine-grained complexity, approximation algorithms, and descriptive complexity theory. His recent work aims to extend motif counting beyond graphs to higher-arity relational structures, with implications for the expressive power of hypergraph neural networks. He is currently recruiting a PhD student to work on these topics. Marc Roth earned his PhD in Computer Science from Saarland University and the Cluster of Excellence MMCI under the supervision of Holger Dell. Scientific Awards: No scientific awards mentioned in the provided text. Advising and Grants: Marc Roth is actively involved in academic supervision, currently advertising a fully funded PhD studentship on motif counting in higher-order networks. The position includes tuition coverage and a UKRI-level stipend, indicating active grant support. He welcomes prospective PhD applicants and is engaged in mentoring and research guidance. Labs and Teams: Marc Roth is affiliated with the theoretical computer science group at Queen Mary University of London. He was previously part of the algorithms and complexity theory group at the University of Oxford under Leslie Ann Goldberg and associated with Merton College. His research is collaborative and theory-driven, focusing on algorithmic foundations of network analysis.
Dániel Marx is a tenured Professor at the CISPA Helmholtz Center for Information Security in Saarbrücken, Germany. He leads research in the area of Algorithmic Foundations and Cryptography, with a focus on parameterized algorithms and computational complexity. He has held previous positions at the Max Planck Institute for Informatics and the Institute for Computer Science and Control of the Hungarian Academy of Sciences (MTA SZTAKI). His work is highly theoretical, aiming to understand the precise complexity of algorithmic problems, especially on bounded-treewidth graphs and in parameterized settings. PhD: Budapest University of Technology and Economics, 2005 Postdoc: Tel Aviv University, Humboldt University Berlin Senior Research Fellow: MTA SZTAKI, 2012–2019 Senior Researcher: Max Planck Institute for Informatics, 2019–2020 Faculty: CISPA Helmholtz Center, 2020–present His research interests lie at the intersection of theoretical computer science and discrete mathematics. He is particularly known for his work on parameterized algorithms , fine-grained complexity , and lower bounds . His group investigates algorithmic graph theory problems, including domination, independence, homomorphism, and clustering, especially under structural constraints like bounded treewidth. He has pioneered techniques in dynamic programming, kernelization, and hardness proofs based on the Exponential Time Hypothesis. The recent publications of Dániel Marx reveal a consistent focus on establishing tight complexity bounds for fundamental algorithmic problems. His work spans from exact and parameterized algorithms to approximation and counting problems. A recurring theme is the analysis of problems on bounded-treewidth graphs, where he explores the boundary between tractable and intractable cases. He also contributes to network design (e.g., Steiner problems), clustering, and subgraph counting, often providing complete classifications of complexity based on parameters. European Research Council Starting Grant European Research Council Consolidator Grant Humboldt Research Fellowship for Experienced Researchers Dániel Marx has advised numerous researchers and collaborated widely across institutions. His research is supported by prestigious grants, including ERC grants that funded his group at MTA SZTAKI. He actively leads a research group at CISPA focused on parameterized algorithms and complexity. While specific PhD students are not listed in the provided text, his extensive co-authorship network indicates a strong mentoring and collaborative presence. His work has significant implications for the foundations of computer science and algorithm design. He leads the research group on Parameterized Algorithms and Complexity at CISPA, continuing his long-standing focus on theoretical algorithm design and analysis. His team works on foundational problems in graph algorithms and complexity theory, aiming to develop new algorithmic techniques and understand the limits of efficient computation.
Jesper Nederlof is an Associate Professor in the Algorithms and Complexity group at the Department of Information and Computing Sciences, Faculty of Science, Utrecht University. His research focuses on designing efficient algorithms for computationally hard problems, particularly in the areas of parameterized complexity, graph algorithms, and NP-complete problems. He received his M.Sc. in Applied Computing Science from Utrecht University in 2008 and his Ph.D. from the University of Bergen in 2011 with the thesis 'Space and Time Efficient Structural Improvements of Dynamic Programming Algorithms' under supervision of Pinar Heggernes. Nederlof's research interests span multiple areas of theoretical computer science, with a particular focus on designing algorithms for NP-complete problems with small exponential worst-case run time. His work extends to algorithmic game theory, information theory, representation theory, approximation algorithms, and online algorithms. He has made significant contributions to parameterized complexity, particularly in developing algorithms parameterized by structural graph parameters like treewidth and cutwidth. His publication record shows a consistent output of high-quality research in top theoretical computer science venues. His recent work demonstrates trends toward tighter bounds for exponential-time algorithms, improved space complexity, and connections between different complexity hypotheses like ETH. Many papers focus on structural parameters of graphs to develop more efficient algorithms for fundamental problems like Hamiltonian cycle, Steiner tree, and subset sum. EATCS-IPEC Nerode Prize (2023) WG best paper award (2020) Nederlof has been involved in teaching courses on algorithms, (non)-linear optimization, graph theory, (vector) calculus, modeling, and management and product development. His research has been supported by various grants including an NWO open competition project during his postdoctoral period and an EU ERC Starting Grant for the project 'Finding Cracks in the wall of NP-Completeness' (2020-2025). As a member of the Algorithms and Complexity group at Utrecht University, Nederlof collaborates with researchers working on foundational aspects of computing, contributing to the group's reputation in theoretical computer science research.
Daniel Lokshtanov is a Professor and Vice Chair at the Department of Computer Science at the University of California, Santa Barbara (UCSB) , with a visiting professor affiliation at the University of Bergen . He is renowned for his work in Theoretical Computer Science and Discrete Mathematics , particularly focusing on Algorithmic Graph Theory and Parameterized Complexity . Key roles: Professor (UCSB, since 2020), Vice Chair (UCSB), Visiting Professor (University of Bergen) Research focus: Kernelization, Graph Minors, Exact Algorithms, Treewidth, Subexponential Algorithms Research Trends : His recent publications (2022-2020) demonstrate expertise in applying Parameterized Complexity to Graph Algorithms , including work on Unit Disk Graphs , Graph Reconfiguration , and Subexponential Time Algorithms . Topics span Graph Contraction , Obstacle Removal , and Kemeny Rank Aggregation . Scientific Awards : Outstanding Young Researcher Meltzer Award Best ESA Paper Award (2015) Advising : While not actively seeking new PhD students, he supervises MS students at UCSB and has mentored numerous advisees through Parameterized Algorithms research. He co-organizes the Inter-Collegiate Programming Contest at UCSB and the Norwegian Informatics Olympiad for high school students.
Darren Strash is an Associate Professor and Chair of the Computer Science department at Hamilton College. His research focuses on solving computationally challenging graph problems, including cliques, independent sets, and cuts, by integrating algorithm theory, combinatorial optimization, and operations research. He holds a Ph.D. and M.S. from the University of California, Irvine, and a B.S. from Cal Poly Pomona. Prior to Hamilton, he was a visiting professor at Colgate University and worked as a postdoctoral researcher at Karlsruhe Institute of Technology in Germany, followed by a career as a software engineer at Intel. Strash’s research interests emphasize practical data reduction techniques for graph problems, computational geometry, and dynamic data structures. His work often bridges theoretical foundations with real-world applications, such as maximum independent set algorithms and distributed graph generation. He has contributed to open-source projects like OpenStreetMap and teaches courses including Algorithms, Computational Geometry, and Design Principles. His recent publications highlight advancements in exact algorithms for edge clique cover, vertex clique cover, and scalable kernelization for maximum independent sets. He has advised students on topics like synergistic data reduction and exact solutions for graph problems. His work has been featured in conferences like ESA and ALENEX, and journals such as the ACM Journal of Experimental Algorithmics and SIAM proceedings.
David Schindl is a Lecturer in the Department of Informatics at the University of Fribourg's Faculty of Management, Economics and Social Sciences, with his primary appointment at Haute Ecole de Gestion (HEG) Geneva since 2008. His research bridges graph theory and combinatorial optimization with practical applications in logistics, vehicle routing, and academic timetabling systems. Education: PhD in Mathematics, EPFL, 2004 Research Interests: Dr. Schindl specializes in theoretical graph structures—including k-community detection, clique-width parameterization, and EPG graphs—with direct applications to transportation logistics, waste management, and educational scheduling. His work on course/exam timetabling at HEG since 2012 demonstrates his commitment to solving real-world operational challenges through mathematical optimization. Research Trends: Analysis of his 2020-2025 publications reveals sustained focus on community structures in graph classes and width-parameterized algorithms, alongside growing emphasis on sustainable logistics. His waste collection project exemplifies the environmental application of combinatorial optimization to reduce municipal fuel consumption and emissions. Grants and Projects: Efficient and sustainable waste collection (2019-2022): Funded by Innovation, this project developed optimization algorithms for waste collection routing in Swiss municipalities using electric vehicles and intermediate depots to minimize environmental impact. Teaching: At the University of Fribourg, he teaches decision support and graph theory courses. At HEG Geneva, he delivers instruction in statistics and mathematics for economics students, emphasizing practical applications of quantitative methods.
Prof. Dr. Hans Bodlaender is a Full Professor of Algorithms and Complexity at Utrecht University's Faculty of Science, Department of Information and Computing Sciences. He holds a Ph.D. in Mathematics from Utrecht University (1985) and has held academic positions since 1983, including roles at Eindhoven University of Technology. His research focuses on algorithms, computational complexity, graph theory, and parameterized complexity, with a particular emphasis on treewidth and network algorithms. He has been recognized with the EATCS-IPEC Nerode Prize (2014) and has contributed to over 500 publications. His work includes developing algorithms for graph decomposition, scheduling, and NP-hard problem analysis. He has organized international workshops and served on editorial boards, including the Journal of Discrete Algorithms. Education: B.Sc. Mathematics, Utrecht University (1981) M.Sc. Mathematics, Utrecht University (1983) Ph.D. in Distributed Computing (1985), supervised by Jan van Leeuwen Research Interests: Algorithms, complexity theory, parameterized complexity, treewidth, graph algorithms, network optimization, and computational problem-solving. His work bridges theoretical foundations with practical algorithm design, emphasizing efficient algorithms for NP-hard problems. Recent Article Trends: Focus on parameterized complexity, treewidth applications, scheduling algorithms, and algorithmic lower bounds. Recent work explores fixed-parameter tractability, graph decompositions, and hardness results for problems on structured graphs. Awards: EATCS-IPEC Nerode Prize (2014) for contributions to parameterized complexity. Grants/Advising: Extensive involvement in grant-funded research projects and academic leadership roles. Supervised numerous PhD and Master's students (details not fully listed here). Labs/Teams: Active in the Algorithms and Complexity research group at Utrecht University, collaborating on theoretical computer science and algorithmic challenges.
Kamyar Khodamoradi is an Assistant Professor in the Department of Computer Science at the University of Regina, Faculty of Science. His research focuses on theoretical computer science, particularly approximation algorithms and combinatorial optimization, where he designs algorithms with mathematically provable guarantees for intractable problems. Dr. Khodamoradi earned his Ph.D. from Simon Fraser University and completed postdoctoral appointments at the University of British Columbia and several European institutions. His research explores fundamental challenges in optimization across disciplines like computational geometry, graph theory, and resource allocation. Recent work demonstrates advanced techniques for clustering, scheduling, and network optimization problems. Publications emphasize algorithm design with theoretical rigor, frequently appearing in top-tier computer science venues.
Fedor Fomin is a Professor in Algorithms at the Department of Informatics, University of Bergen, Norway, since 2002. His research focuses on fundamental problems in computer science and mathematics, particularly in algorithm design and graph theory. Research Interests: His work spans advanced algorithmic techniques such as Matroid algorithms Algorithmic graph minors Treewidth and its applications Exact and exponential time algorithms Pursuit-evasion games and graph searching Parameterized algorithms and kernelization Graph coloring Publications: He has authored over 150 peer-reviewed journal articles in venues like J. ACM, SIAM J. Computing, and Combinatorica, alongside 160 conference papers in top-tier events including FOCS, STOC, and AAAI. His research demonstrates expertise in bridging theoretical computer science and discrete mathematics. Scientific Awards: EATCS Fellow (2019) ERC Advanced Investigator Grant (2010) EATCS-IPEC Nerode Prize 2017 (with F. Grandoni and D. Kratsch) EATCS-IPEC Nerode Prize 2015 (with E. D. Demaine, M. T. Hajiaghayi, and D. M. Thilikos) Norway's Outstanding Young Investigator Award (2005) Grants: He has secured major grants from The Research Council of Norway (NFR), the Russian Ministry of Education and Science (mega-grant), and the European Research Council (ERC) as Principal Investigator.
Dr. Pradeesha Ashok is an Associate Professor and Controller of Examinations at IIIT Bangalore. She holds a Ph.D. from the Indian Institute of Science, Bangalore, and previously worked as a Postdoctoral Fellow at the Institute of Mathematical Sciences, Chennai. Her research focuses on Theoretical Computer Science, with specializations in Algorithms, Graph Theory, Combinatorics, and Parameterized Complexity. Her research interests include geometric problems such as polygon guarding, covering, and packing, as well as conflict-free coloring in graphs and hypergraphs. She has contributed to developing exact and parameterized algorithms for these problems. Dr. Ashok has also taught courses like Exact and Parameterized Algorithms, Graph Theory, and Design and Analysis of Algorithms. Her publications span conferences like IWOCA, CSR, and COCOON, as well as journals such as Discrete Applied Mathematics and SIAM Journal on Discrete Mathematics. Her work emphasizes algorithmic efficiency and combinatorial optimization in geometric and graph-theoretic contexts. Dr. Ashok has advised several students, including PhD candidates and MTech thesis students, focusing on topics like the chromatic art gallery problem and parameterized complexity of coloring problems. She is affiliated with the Department of Computer Science & Engineering at IIIT Bangalore and contributes to the institute's academic governance through her role as Controller of Examinations. Her research also extends to geometric separability, bichromatic covering problems, and experimental studies of the Steiner Tree problem. She collaborates on projects involving theoretical and applied aspects of computational geometry and algorithms.
James Abello Monedero is a Professor in the Computer Science Department at Rutgers University , specializing in algorithms, graph mining, and visualization of massive datasets. He earned a Ph.D. in Computer Science from the University of California, San Diego, and held postdoctoral and academic positions at UC Santa Barbara, Texas A&M University, and Bell Labs. Ph.D. in Computer Science, UC San Diego M.S. in Computer Science, UC Santa Barbara His research interests span external memory algorithms , graph mining , relational learning , and visual analytics for massive datasets. He has pioneered techniques for dynamic weighted multi-digraph analysis, large-scale network visualization, and interdisciplinary applications in epidemiology and cultural analytics. James’s publications focus on scalable graph algorithms, visual metaphors for data exploration, and network decomposition. His work includes foundational contributions to graph sketches , quasi-clique detection , and 3D graph navigation , with applications to telecommunications, web graphs, and homeland security. Scientific awards include the ESA Test of Time Award (2017) , Best Teaching Award at Rutgers (2015) , and Fellow of the Institute of Combinatorics (1993) . He has advised numerous Ph.D. and M.S. students, and his research has been funded by NSF , DHS , and LLNL . James leads the Universal Information Graphs Project at DyDAn (DHS Center) and has developed software systems like MGV and Ask-GraphView for interactive graph analysis. He is an active organizer of conferences and workshops in data mining and visualization.
