Find Academic Supervisors

• Sparse Matrix Computation
• Optimization Algorithms
• High-Performance Computing
• +2 more

Shahadat Hossain is Professor and Program Chair of Computer Science at the University of Northern British Columbia. His research develops optimization algorithms for sparse matrix problems, complex networks, and high-performance computing. Key contributions include: DSJMToolkit for sparse Jacobian matrices Graph-based methods for matrix estimation Quantum-classical optimization hybrids He has supervised over 20 graduate students and secured NSERC Discovery Grants for optimization research. Hossain holds a Dr.Scient. from University of Bergen and completed visiting positions at Cornell University and Humboldt University. His 15 most-cited publications demonstrate consistent focus on sparse matrix computation, graph algorithms, and computational optimization techniques with applications in scientific computing and network analysis.

Paola LeccaView profile

Assistant Professor

• Graph Theory
• Dynamical Networks
• Control Theory
• +4 more

Paola Lecca is an Assistant Professor at the Free University of Bozen-Bolzano's Faculty of Engineering, specializing in theoretical and applied research on graph theory, dynamical networks, control theory, and causal inference. She is a Senior Professional Member of the Association for Computing Machinery and leads projects at the Smart Data Factory laboratory, focusing on technology transfer to industry. Her research integrates mathematical methods for complex systems in biological contexts, including systems biology, biophysics, and biochemistry. She develops computational approaches for network dynamics, simulation, and analysis, aiming to understand emergent properties in multi-agent systems. Courses taught include Mathematics and Statistics for Data Science and Preparatory Mathematics. She actively contributes to conferences and editorial boards, including Frontiers in Bioinformatics and Big Data Analysis for Medical Sciences.

Dan RalescuView profile

Professor

• Probability Theory
• Uncertainty Theory
• Fuzzy Sets
• +5 more

Dan Ralescu is a Professor of Mathematics at the University of Cincinnati since 1980, affiliated with the Department of Mathematical Sciences in the College of Arts and Sciences. He holds editorial roles in 10 journals and has delivered plenary lectures globally. His research focuses on probability theory, fuzzy sets, and uncertainty modeling, with applications in finance, engineering, and decision theory. Education: PhD in Statistics (Indiana University, 1980), M.A. Mathematics with Honors (University of Bucharest, 1972), and additional M.A. in Mathematics/Statistics (Indiana University, 1979). Research interests include limit theorems for random sets, mixed uncertainty models, Bayesian robustness, and large data set management. His work bridges statistical methodologies with fuzzy logic systems, particularly in financial modeling and risk analysis. Key contributions include the Liu Process in uncertainty theory, portfolio optimization models using fuzzy time series, and risk index frameworks for uncertain systems. Awards include the 2014 Lifetime Achievement Award from China’s Society for Uncertainty and IFSA Fellowship. Active in grants since 1985, including NSF-funded projects on decision-making under uncertainty and collaborative efforts with international institutions like Tokyo Institute of Technology. He has supervised numerous research collaborations and publishes extensively in top-tier journals.

Inne SinggihView profile

Assistant Professor

• Graph Theory
• Graph Labeling
• Discrete Mathematics
• +3 more

Inne Singgih is an Assistant Professor Educator in the Department of Mathematical Sciences at the University of Cincinnati. They hold a Ph.D. in Mathematics from the University of South Carolina (2020), an M.S. in Applied and Computational Mathematics from the University of Minnesota Duluth (2015), and a B.Sc. in Mathematics from Universitas Indonesia (2009). Their research focuses on Graph Theory, particularly graph labeling, including magic/antimagic labelings, DNA graph labeling, and genome rearrangement models. They have published extensively in top journals like Theoretical Computer Science and Electronic Journal of Combinatorics . Key research interests include exploring structural properties of graphs, algorithmic approaches to genome rearrangement, and combinatorial optimization. Recent work bridges graph theory with bioinformatics, such as analyzing pairwise rearrangement tractability in genome models. Their Erdős number is 2, reflecting strong collaborative networks in discrete mathematics. Teaching excellence is evident through awards like the 2020 Outstanding Graduate Student Instructor and multiple teaching grants. Active in pedagogical development, they led initiatives like the Jupyter NoteBook Calculus Classroom Resources project and hold certifications in inclusive teaching practices. Current projects include antimagic labeling collaborations and undergraduate research on DNA graph characterization. Notable grants include the 2021 University of Cincinnati Research Launch Award and teaching grants focused on improving calculus instruction. Their work often involves interdisciplinary teams, such as collaborations with bioinformaticians on genome rearrangement algorithms and combinatorialists on labeling theory advancements.

Nicola SantoroView profile

Research Professor

• Algorithms
• Communication Networks
• Data Structures
• +8 more

Nicola Santoro is a Distinguished Research Professor in the School of Computer Science at Carleton University, Ottawa, Canada. His academic career spans over four decades, with a focus on distributed computing, algorithms, and network systems. He holds a Ph.D. from the University of Waterloo (1979) and a D.Sc. from the University of Pisa (Italy). His research interests include algorithms, communication networks, distributed computing, robotics, graph theory, and wireless communication. He has contributed extensively to the theoretical foundations of distributed systems, mobile robotics, and fault-tolerant computing. Santoro's work emphasizes scalable and efficient solutions for dynamic networks and multi-agent systems. Key contributions include studies on black hole search in dynamic networks, distributed algorithms for autonomous robots, and network decontamination. His publications span over 400 articles in top-tier journals and conferences. He has also authored influential textbooks, such as Design and Analysis of Distributed Algorithms (Wiley, 2007) and Distributed Computing by Mobile Entities (Springer, 2019). Prof. Santoro has advised numerous graduate students and researchers, shaping the next generation of computer scientists. His work bridges theory and practice, with applications in robotics, sensor networks, and parallel computing.

• Computational Complexity
• Algorithm Design
• Cognitive Science
• +4 more

Dr. Harold Wareham is a tenured Professor in the Department of Computer Science at Memorial University of Newfoundland (MUN), Faculty of Science. He holds a Ph.D. from the University of Victoria and has been at MUN since 1999, advancing through roles including Assistant Professor, Associate Professor, and Full Professor. His research focuses on computational complexity theory applied to cognitive science, robotics, and computational biology. He has served on numerous academic committees and international conference program committees. Education: B.Sc. (Computer Science) and B.A. (Linguistics/Mathematics) from MUN, followed by an M.Sc. in Computational Biology and a Ph.D. in Parameterized Complexity in Computational Phonology from the University of Victoria. Research Interests Computational complexity of cognitive processes Algorithm design for robotics and swarm control Parameterized complexity in biological systems Machine learning interpretability Recent Work Trends Recent publications emphasize applying complexity theory to AI interpretability (e.g., neural network reverse-engineering) and cognitive science (segmentation processes). His robotics research explores algorithmic foundations for swarm construction tasks. He also investigates computational challenges in software reconfiguration and modularization. Awards 2017 Best Professor Award (MUN CS Graduate Society) Teaching Fellow at Radboud University (2014–) F. A. Aldrich Alumni Graduate Scholarship (1989) Grants & Advising Has supervised numerous courses across undergraduate and graduate levels, including AI topics, computational biology, and theoretical computer science. Active in grant review roles for NSERC and international funding bodies. Served on MUN committees for promotion, tenure, and graduate studies. Labs & Collaborations Associated with the MUN CS Theory Group and the Bio-inspired Robotics (BOTS) Lab. Collaborates internationally on projects like the Dagstuhl Complexity Workshops and cognitive science initiatives.

Amin Coja-OghlanView profile

Professor

• Probabilistic Combinatorics
• Mathematical Physics
• Disordered Systems
• +2 more

Amin Coja-Oghlan is Professor of Efficient Algorithms and Complexity Theory at TU Dortmund University's Department of Computer Science. His research integrates probabilistic combinatorics, information theory, and statistical physics to solve fundamental problems in theoretical computer science. Education includes a doctorate in Mathematics (University of Hamburg, 2002) and habilitation in Computer Science (Humboldt University Berlin, 2005). Research advances understanding of phase transitions in constraint satisfaction problems, optimization landscapes, and random structures. Recent publications analyze SAT thresholds, group testing, and sparse matrix properties. Academic appointments include professorships at Goethe University Frankfurt and lectureships at Edinburgh and Warwick. Research contributions bridge discrete mathematics with computational complexity.

Marc NoyView profile

Professor

• Combinatorics
• Graph Theory
• Discrete Geometry
• +3 more

Marc Noy is a Professor at the Department of Applied Mathematics II, Polytechnic University of Catalonia (UPC), affiliated with the School of Mathematics and Statistics. He is the Director of the Barcelona Graduate School of Mathematics (BGSMath) and leads the 2015-2019 Excellence program BGSMath/María de Maeztu. His research focuses on Combinatorics and Graph Theory, including asymptotic enumeration, random graphs, discrete geometry, and Tutte polynomials. He has advised multiple PhD and Master’s students and contributes to editorial roles for the Electronic Journal of Combinatorics and the Catalan Mathematical Society’s Bulletin. His teaching spans undergraduate and graduate courses in Combinatorics, Graph Theory, Complex Analysis, and Discrete Mathematics at UPC. He has participated in numerous international conferences and workshops, including the ICM 2014 and FOCM 2017. His work emphasizes the probabilistic analysis of graph structures, limit laws, and enumerative combinatorics. His recent publications explore topics like logical limit laws in graph classes, random planar graphs, and Tutte polynomial evaluations. He maintains active collaborations in combinatorial enumeration, with contributions to understanding graph properties in minor-closed classes and random geometric configurations.

• Enumerative Combinatorics
• Graph Theory
• Random Graphs
• +4 more

Juanjo Rué Perna is an Associate Professor at the Universitat Politècnica de Catalunya (UPC), holding a position in the Department of Mathematics . He also serves as Director of the CFIS (Centre de Formació Interdisciplinària Superior). Previously, he was a Juniorprofessor (Assistant Professor) at Freie Universität Berlin (2013-2016), affiliated with the Combinatorics and Graph Theory group. His academic journey includes postdoctoral positions at ICMAT (Madrid, 2010-2013) and École Polytechnique (France, 2009-2010). Rué obtained his PhD in Discrete Mathematics from UPC in 2009 under Marc Noy, focusing on the enumeration of topological graphs. His research interests span Enumerative Combinatorics , Graph Theory , Random Graphs , and Additive Combinatorics , with notable contributions to planar maps and asymptotic analysis. He has supervised four PhD students, including Clément Requilé and Christoph Spiegel. He has organized major conferences like EUROCOMB 2021 and authored books such as El arte de contar: Combinatoria y enumeración and academic works on transcendental numbers. Rué's work bridges theoretical mathematics with applications in quantum gravity and statistical physics, emphasizing interdisciplinary approaches.

• Theoretical Computer Science
• Algorithm Design
• Online Algorithms
• +3 more

Dr. Denis Pankratov is an Associate Professor in the Department of Computer Science and Software Engineering at Concordia University. His research focuses on theoretical computer science, including algorithm design, complexity theory, and information theory, with an emphasis on bridging the gap between theoretical guarantees and practical algorithm performance. He has taught undergraduate and graduate courses in algorithm design, probability theory, and online algorithms, often for large classes (80–150 students). His mentoring includes supervising postdocs, Masters and PhD students, and undergraduate researchers. Education: Bachelors from the University of Toronto, PhD and Master’s from the University of Chicago, followed by a postdoc at the University of Toronto before joining Concordia. Professional experience includes roles at Toyota Technological Institute at Chicago, Google Inc., and Zurich Insurance Company. Research interests span algorithm design, online algorithms, communication complexity, and proof complexity. His work often employs an information-theoretic lens to understand algorithmic behavior beyond worst-case scenarios. Hobbies include programming contests (e.g., ICPC-style), woodworking, and 3D printing. For a full list of publications, visit his Google Scholar profile . Teaching and professional activities emphasize research, mentoring, and service to the academic community.

• Medical Image Computing
• Image-Guided Surgery
• Human-Computer Interaction
• +9 more

Dr. Yiming Xiao is an Associate Professor in the Department of Computer Science and Software Engineering at Concordia University, holding the Research Chair in Intelligent & Intuitive Surgical Technology. His work focuses on medical image computing, image-guided surgery, and AI-driven surgical applications. He leads the HealthX Lab, advancing neurotechnology, explainable AI, and virtual/augmented reality systems for surgical planning. Research interests include medical image segmentation , deep learning , VR/AR in surgery , and collateral circulation analysis . Notable projects include PreVISE (VR SEEG planning), CABLD (brain landmark detection), and MedCLIP-SAM (text-driven medical segmentation). Publications emphasize few-shot learning , ultrasound-MRI co-registration , and neurological disorder diagnostics . He actively supervises PhD students in computer science, with a focus on interdisciplinary applications of AI in healthcare. His work bridges computational methods and clinical needs to improve surgical precision and patient outcomes.

Gary MacGillivrayView profile

Professor

• Algorithms
• Combinatorics
• Graph Theory
• +7 more

Gary MacGillivray is a Professor and Chair of the Department of Mathematics and Statistics at the University of Victoria (UVic). He holds credentials including B.Sc., M.Sc. (UVic), and Ph.D. (Simon Fraser University). His research focuses on algorithmic complexity in combinatorial problems, dynamic processes on graphs, mathematics in sports, and mathematics education. He is actively involved in teaching courses such as Geometry, Discrete Mathematics, and seminars on independent projects. Education: B.Sc. in Mathematics, UVic M.Sc. in Mathematics, UVic Ph.D. in Mathematics, Simon Fraser University Research Interests: Algorithmic and complexity issues in graph colourings/homomorphisms and graph domination. Dynamic processes on graphs, including pursuit-evasion games and dynamic domination. Applications of mathematics in sports scheduling and performance analysis. Improving student success in university-level mathematics and curriculum development. Teaching (2024-2025): Fall 2024: MATH 366 (Geometry), MATH 585 (Seminar), MATH 498/STAT 498 (Seminar and Independent Project). Spring 2025: MATH 222 (Discrete and Combinatorial Mathematics), MATH 498/STAT 498 (Seminar and Independent Project). Additional Roles: Advisor to undergraduate and graduate students. Contributor to the Mathematics and Statistics Assistance Centre.

Jonathan NoelView profile

Assistant Professor

• Extremal Combinatorics
• Probabilistic Combinatorics
• Combinatorial Limits
• +7 more

Jonathan Noel is an Assistant Professor in the Department of Mathematics and Statistics at the University of Victoria. His research focuses on extremal combinatorics, probabilistic combinatorics, and combinatorial limits, with applications to quasirandomness, Ramsey theory, and graph theory. He holds a DPhil (PhD) from the University of Oxford and teaches courses such as MATH 122 (Logic and Foundations) and MATH 529 (Topics in Discrete Mathematics). His research interests include extremal set theory, graph colouring, graph homomorphisms, bootstrap percolation, and computational complexity. He explores how local patterns in discrete structures influence global properties, such as the interplay between edge densities and cycle counts in graphs. Recent work emphasizes quasirandomness through permutation patterns and entropy methods, alongside bootstrap percolation dynamics in hypercubes and cellular automata. His articles often bridge combinatorial limits with analytic approaches, such as the Szemerédi Regularity Lemma. No awards are listed for Jonathan Noel in the provided text. He advises no formally listed students but contributes to academic supervision through course instruction.

Natasha MorrisonView profile

Assistant Professor

• Extremal Combinatorics
• Probabilistic Combinatorics
• Graph Theory
• +6 more

Natasha Morrison is an Assistant Professor in the Department of Mathematics and Statistics at the University of Victoria, Canada. She holds a PhD from the University of Oxford (supervised by Alex Scott) and completed her undergraduate studies at Durham University. Previously, she was a Research Fellow at Sidney Sussex College, Cambridge, and a Postdoctoral Research Fellow at IMPA in Brazil under Rob Morris. Her research focuses on extremal and probabilistic combinatorics, including extremal graph theory, random graphs, bootstrap percolation, Ramsey Theory, and additive combinatorics. She teaches courses such as Matrix Algebra and Graph Theory. She actively collaborates with researchers globally and supervises PhD, Master's, and undergraduate students. Morrison’s work has been published in leading journals like Journal of Combinatorial Theory, SIAM Journal on Discrete Mathematics, and Duke Mathematical Journal. She is known for contributions to topics like graph saturation, cross-Sperner systems, and pseudorandom graphs. Her research often bridges theoretical insights with probabilistic methods. Students supervised include Shannon Ogden (PhD), Ashna Wright (Master’s), and Akina Kuperus (Master’s). She collaborates with notable researchers such as Jonathan Noel, Shoham Letzter, and Rob Morris. Her academic journey includes postdoctoral work in Brazil and UK, reflecting her international research network.

• High-Performance Computing
• Parallel Processing
• Code Optimization
• +3 more

Georgios Goumas is an Associate Professor in the Division of Computer Science at the School of Electrical and Computer Engineering, National Technical University of Athens. His research focuses on high-performance computing, parallel systems, and efficient resource management for modern computing platforms. Research domains: Serverless computing scalability and memory management Quantum algorithm design for classification Virtual memory optimization Hardware acceleration for sparse computations NUMA-aware concurrent data structures Recent innovations include DaeMon for disaggregated systems, eBPF-based Linux memory management, and multi-GPU matrix multiplication optimizations. Publications demonstrate consistent advancement in low-level system efficiency across quantum, serverless, and heterogeneous computing domains. Dr. Goumas teaches undergraduate and graduate courses on Operating Systems, Parallel Processing, and Code Optimization Techniques. His lab develops open-source tools like Paralia runtime for auto-tuning linear algebra and FPGA-based accelerators for scientific computing.