Nejib Zaguia is a Professor at the School of Computer Science and Electrical Engineering, University of Ottawa. His research focuses on algorithms, order optimization, graph algorithms, and combinatorial structures. He has contributed significantly to the study of ordered sets, graph theory, and network-related problems such as decontamination and distributed algorithms. His work spans theoretical foundations and practical applications in wireless networks, Bluetooth protocols, and cellular automata-based systems. Research Interests: Zaguia explores advanced topics in algorithms, including optimization of ordered sets, graph coloring, and network analysis. His work on cellular automata and Bluetooth networks highlights interdisciplinary applications of theoretical computer science. Publications: His recent articles address challenges in network decontamination, Bluetooth distributed algorithms, and the mathematical properties of ordered sets. These contributions reflect a blend of algorithm design, combinatorial analysis, and real-world network problem-solving. Grants & Advising: While specific grants or advisees are not detailed here, his prolific publication record indicates active research collaborations and mentorship in his field.
Kenji Shimada is the Theodore Ahrens Professor of Engineering at Carnegie Mellon University's Department of Mechanical Engineering. His research focuses on geometric computing, mesh generation, and advanced manufacturing technologies, particularly in additive manufacturing, robotics, and biomedical applications. He leads projects in autonomous drone navigation, custom-fit medical devices, and virtual factory simulations. Shimada's work bridges computational engineering with practical industry needs, emphasizing design efficiency and cost reduction. Education: Ph.D. (MIT, 1993), M.S. and B.S. (University of Tokyo, 1985/1983). Affiliations include the Engineering Research Accelerator and NextManufacturing Center. Research interests encompass robotics (aerial/medical), computational geometry, bioengineering, and generative manufacturing. His Bubble Mesh method revolutionizes mesh generation for FEM/BEM analysis. Collaborations with YKK AP and clinical trials highlight his translational research impact. Recent projects include drone navigation in dynamic environments, soft tissue measurement devices for CPAP masks, and AI-driven construction safety monitoring. Media mentions highlight innovations like the Moldable Mask and autonomous window installation robots. Grants and industry partnerships fund his work, with a focus on robotics, medical devices, and advanced manufacturing. Advising emphasizes student-led innovation in surgical training tools and additive manufacturing applications.
Will Evans is a Professor in the Department of Computer Science at the University of British Columbia (UBC). He specializes in computational geometry, graph drawing, information theory, data compression, and algorithms. His research focuses on geometric algorithms, graph visualization, and theoretical computer science applications. Recent work emphasizes optimization of algorithms for moving objects, congestion control, and geometric representations. His publications span topics from scheduling strategies to visualization techniques for complex data structures. While no formal awards or grants are listed, his extensive list of peer-reviewed publications underscores his contributions to the field. Advising details and lab affiliations are not explicitly mentioned in the provided materials.
Dr. Andre van Renssen is a Senior Lecturer at the School of Computer Science, University of Sydney, where he has been working since 2018. He is a member of the Sydney Algorithms and Computing Theory (SACT) research group, contributing to both research and teaching in theoretical computer science. Dr. van Renssen earned his Ph.D. in Computer Science from Carleton University in Canada. His academic journey has focused on computational geometry and algorithms research with applications to real-world network problems. His primary research focuses on geometric networks, particularly network construction, augmentation, and routing algorithms. He designs efficient algorithms for finding shortest paths through various networks - from computer communications to transportation systems - while accounting for dynamic constraints like traffic congestion and obstacles. His work considers time-varying conditions where the optimal route might change based on time of day or unexpected closures, aiming to optimize network performance without requiring additional physical infrastructure. Analysis of his recent publications reveals a strong emphasis on computational geometry problems, particularly related to spanners, routing algorithms in constrained environments, Voronoi diagrams, and geometric optimization. His work bridges theoretical foundations with practical applications, with research already influencing technologies like Google Maps' navigation functionality. Awarded Australian Research Council (ARC) Discovery Project grant in 2024 for "Algorithms for Future-Proof Networks" Dr. van Renssen supervises research students including Zijin HUANG (working on "Utilisation of Realistic Input Models and the Computation of Their Input Parameters") and Shuei SAKAGUCHI (working on "Geometric Spanner Networks and Local Routing Algorithms"). His teaching portfolio includes advanced courses in data structures, algorithms, and computational geometry across undergraduate and graduate levels. He is actively involved in the international computational geometry research community, collaborating with researchers worldwide on geometric network problems that have both theoretical significance and practical applications.
Prof. Dr. Pelin Dursun Çebi is a Professor at the Department of Architecture, Faculty of Architecture, Istanbul Technical University. She holds a PhD in Building Science from the same university. Her research focuses on architectural design, theory in urban planning, critical analysis of spatial narratives, and design methodology. She has led significant projects such as the 'Mekan Dizimi Tasarım Uygulaması' and contributed to studies on urban breccia and spatial syntax. Her work bridges architectural practice with theoretical frameworks, emphasizing the interplay between body, space, and technology. Education: PhD in Building Science (Istanbul Technical University, 2002), MSc in Building Science (1996), BSc in Architecture (1993). Research Interests: Urban spatial analysis, architectural representation, digital tools in design, bodily experience in urban spaces, and gender studies in academia. Her recent articles explore urban breccia, memory-centred space analysis, and virtual architectural representations. She has supervised over 30 graduate theses, focusing on topics like urban narratives, spatial syntax, and critical design practices. Her projects include developing dynamic design tools (e.g., SpaceChase) and investigating gender dynamics in higher education. She contributes to editorial boards and international conferences, emphasizing interdisciplinary approaches in architecture and urban studies.
Olivier Bernardi is a Professor of Mathematics and Chair of the Brandeis University Department of Mathematics. His research focuses on combinatorics, with applications in probability, mathematical physics, computer science, and algebra. He specializes in bijective methods, encoding complex geometric structures into simpler forms like lattice paths and trees. A key interest is the combinatorics of maps (embedded graphs), which intersect fields like random surface theory and representation theory. Education includes a Ph.D. from Université Bordeaux 1, and M.S. and B.S. degrees from École Normale Supérieure Paris. His work bridges theoretical combinatorics with practical algorithms, emphasizing structural insights through bijections. Recent publications explore Tutte polynomials, percolation on triangulations, and geometric drawing algorithms. Awards and grants are not explicitly listed, but his leadership role as Department Chair highlights institutional contributions. He advises on research in discrete mathematics and collaborates on projects involving graph enumeration and algebraic combinatorics. His research spans foundational topics, with applications in both pure and applied mathematical domains.
Prof. Michael Kaufmann is a Professor in the Department of Computer Science at Eberhard Karls University of Tübingen, within the Faculty of Mathematics and Natural Sciences. He is affiliated with the Wilhelm-Schickard Institute of Computer Science and leads the Algorithmics team. His research focuses on algorithms, complexity, computational geometry, graph drawing, and network visualization. He holds a prominent role in advancing theoretical computer science and combinatorial optimization. His research interests span algorithms and complexity, approximations, combinatorial optimization, computational geometry, graph drawing applications, and parallelism. His work bridges theoretical foundations with practical applications in network visualization and algorithmic design. Prof. Kaufmann has published extensively in leading venues, including Graph Drawing (GD), International Symposium on Theoretical Aspects of Computer Science (STACS), and International Workshop on Graph-Theoretic Concepts in Computer Science (WG). His publications address challenges in graph visualization, algorithmic techniques, and computational geometry. He advises students through the Algorithmics team and maintains an office at Room B112, reachable via email or phone. His work contributes to both academic and applied domains within computer science.
Yoshio Okamoto is a Professor at the Department of Computer and Network Engineering, Graduate School of Informatics and Engineering, at The University of Electro-Communications in Tokyo, Japan. He has held this position since April 2017, after serving as an Associate Professor at the same institution from April 2012 to March 2017. Prior to his appointment at the University of Electro-Communications, he held academic positions at Tokyo Institute of Technology, Japan Advanced Institute of Science and Technology, and Toyohashi University of Technology. His educational background includes: Bachelor of Systems Science from The University of Tokyo (1999) Master of Systems Science from The University of Tokyo (2001) Doctor of Theoretical Science from ETH Zurich (2005) Professor Okamoto's research spans several interconnected areas in theoretical computer science and discrete mathematics. His primary interests include Discrete and Computational Geometry, Graph Algorithms, Combinatorial Optimization and Polyhedral Combinatorics, Discrete Mathematics and Combinatorics, and Game Theory. His work often explores the interplay between these fields, developing theoretical foundations with practical algorithmic implications. He has made significant contributions to understanding the structural properties of geometric and combinatorial objects, as well as designing efficient algorithms for related problems. His recent publications demonstrate a continued focus on fundamental problems in discrete mathematics and theoretical computer science, with increasing applications in quantum computing, fair division, and reconfiguration problems. His work often appears in top-tier journals such as ACM Transactions on Algorithms, Algorithmica, and Theoretical Computer Science, reflecting his standing in the theoretical computer science community. Professor Okamoto has received several prestigious awards recognizing his contributions to the field: IPSJ-CS Outstanding Achievement and Contribution Award (January 2024) Research Award from The Operations Research Society of Japan (September 2020) Best Review Paper Award (with colleagues) from Japan Society for Software and Technology (September 2014) Research Encourage Award from The Operations Research Society of Japan (September 2012) 8th EATCS/LA Presentation Award (February 2010) Editors' Choice 2003 from Discrete Applied Mathematics (September 2004) As an educator, Professor Okamoto has taught numerous courses at The University of Electro-Communications since 2012, including Discrete Mathematics, Graphs and Networks, Discrete Mathematical Engineering, and Foundations of Discrete Optimization. He has served as an editor for multiple prestigious journals including Graphs and Combinatorics (Managing Editor since 2020), Acta Informatica, Journal of Computational Geometry, and Journal of Graph Algorithms and Applications. His extensive service on program committees for major conferences in theoretical computer science demonstrates his active engagement with the research community. Professor Okamoto leads a research laboratory at The University of Electro-Communications, where his team explores fundamental questions in discrete mathematics and theoretical computer science. The lab maintains strong connections with researchers worldwide, as evidenced by his numerous international collaborations. His research has been supported through various channels, including Japan Society for the Promotion of Science grants, and he has served as a reviewer for international funding agencies including the Swiss National Science Foundation and The Netherlands Organization for Scientific Research.
Prof. André Schulz is a Professor at the Faculty MI, Department of Theoretical Computer Science, Distance University. His research focuses on graph theory, computational geometry, and algorithm design, with a strong emphasis on geometric graphs, graph drawing algorithms, and topological representations. He has published extensively in top-tier journals and conferences such as Discrete & Computational Geometry , Journal of Graph Algorithms and Applications , and Graph Drawing and Network Visualization . His work spans topics like adjacency graphs of polyhedral surfaces, Lombardi drawings of knots, and experimental analysis of graph visualization techniques. He collaborates internationally, co-authoring over 30 peer-reviewed articles since 2015. His research addresses challenges in geometric algorithms, graph embeddings, and combinatorial optimization, with applications in social network analysis and geometric topology. Key contributions include minimizing geometric primitives in planar graph drawings and developing efficient algorithms for 1-planar and cubic graphs. His recent work (2023–2024) explores orthogonal circle arrangements and schematic hypergraph layouts. Despite no explicit mention of awards or grants, his prolific publication record underscores his academic influence.
Tsiaras Vasileios is a Teaching Professor in the Department of Electrical and Computer Engineering at the Technical University of Crete. He is currently on leave and based in the School of Electrical and Computer Engineering. His office is located at 141Α-29 in the Science/ECE Building (Λ), 1st Floor. Education: Ph.D. in Computer Science, University of Crete (2009) M.Sc. in Mathematics, Queen Mary and Westfield College, University of London (1992) Undergraduate Degree in Mathematics, Aristotle University of Thessaloniki (1990) Research Interests: His research focuses on Machine Learning , Graph Drawing , Analysis of Brain Signals (including EEG and MEG), and Text-to-Speech Synthesis . These areas integrate computational methods with neuroscience and signal processing to advance artificial intelligence and biomedical applications. Professional Contributions: No specific grants or advising roles are listed in the provided information. His work primarily involves laboratory teaching and research in his stated fields.
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.
Zulaikha Ayub is an Adjunct Assistant Professor at The Cooper Union's Irwin S. Chanin School of Architecture. Her research focuses on media, secrecy, and technology in relation to the Manhattan Project and nuclear armaments, employing interdisciplinary methodologies from critical geography, new materialism, nuclear studies, and media archaeology. She is Co-Director and Head of Expressions for the LoPh Lab (www.lo-ph.agency) and a founding member of the Graphe critical geography collective (www.geo-graphe.org). Dr. Ayub holds a B.Arch. from Cooper Union, an MDesS (Distinction) from Harvard University, and is completing her Ph.D. at Princeton University with a dissertation titled *“Translations from Drawing to Bombing (and Other Disarrays)”*. She has taught design studios, lectures, and seminars at institutions including Pratt Institute, City College of New York, and the Mountainview Correctional Facility.
Nart Shawash is an Associate Professor in the Department of Mathematics and Computer Science at the University of Detroit Mercy's College of Engineering & Science. He joined the department in 2008 and teaches courses including Differential Equations, Advanced Engineering Mathematics, Calculus (single and multivariable), and Graph Theory. Education: Ph.D. in Mathematics from Oakland University (2008) B.Sc. in Electronics Engineering from Princess Sumaya University for Technology (PSUT), Jordan His research focuses on geometric visualization of mathematical concepts, graph drawing algorithms, and dynamical processes on symmetric/random graphs using computational tools like MATLAB and Maple. While no scientific awards or publications are listed in the provided text, his work emphasizes applying graph theory to network modeling and computational analysis.
Ioannis Brilakis is the Laing O’Rourke Professor of Construction Engineering and Director of the Construction Information Technology Laboratory at the University of Cambridge’s Department of Engineering. He holds a PhD from the University of Illinois, Urbana-Champaign and has held academic roles at the University of Michigan, Georgia Tech, and visiting appointments at Stanford and Technical University of Munich (TUM) as a Visiting Professor and Hans Fischer Senior Fellow (2019–2021). His work focuses on construction automation, digital twins, and infrastructure sensing technologies. Research interests include generating/updating digital twins for infrastructure, computer vision for construction site analysis, automated design/construction tasks, and project management technologies. Awards include the NSF CAREER Award, ASCE J. James R. Croes Medal, and ASCE John O. Bickel Award. Collaborations include projects funded by EPSRC, H2020, InnovateUK, and industry partners like BP and Trimble. His lab develops AI-driven solutions for infrastructure monitoring and BIM integration. Recent work emphasizes climate resilience of critical infrastructure and graph-based construction scheduling analysis.
Julia Chuzhoy is a Manuel Blum Professor at the Toyota Technological Institute at Chicago (TTIC) and holds a part-time Professor appointment in the Department of Computer Science at the University of Chicago. She is a leading researcher in theoretical computer science with a focus on graph-related optimization problems and approximation algorithms. Her research interests span theoretical computer science, particularly graph theory, approximation algorithms, dynamic algorithms, and hardness of approximation proofs. She has made significant contributions to graph minor theory, routing problems, and algorithmic graph theory. Her recent publications demonstrate expertise in subpolynomial approximation algorithms for graph crossing number, hardness results for node-disjoint paths in grids, polynomial bounds for the grid-minor theorem, and routing in undirected graphs with constant congestion. Her work consistently addresses fundamental questions in algorithm design with strong theoretical foundations. NSF Career award Alfred P. Sloan research fellowship Multiple NSF grants (CCF-1318242, CCF-1616584, CCF-2006464, CCF-2402283) NSF HDR TRIPODS award 2216899 Professor Chuzhoy has advised several PhD students including Ron Mosenzon, Rachit Nimavat (expected graduation Summer 2023), Zihan Tan (graduated Spring 2022), David H.K. Kim (graduated Spring 2018), and Parinya Chalermsook (graduated Summer 2012). She has also mentored numerous summer interns from institutions including MIT, CMU, Princeton, and UIUC. She is an active member of the theoretical computer science community, having served on program committees for major conferences including STOC (as PC chair in 2020), FOCS, and APPROX. She has also served on editorial boards for Algorithmica and SICOMP, and is a member of the SODA and ITCS steering committees.
