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Kuldeep S. MeelView profile

Associate Professor

• Automated Reasoning
• Formal Methods
• Artificial Intelligence
• +6 more

Kuldeep S. Meel is the Stephen Fleming Early-Career Associate Professor at the School of Computer Science, Georgia Institute of Technology, and an Associate Professor at the University of Toronto (on leave). He previously held a NUS Presidential Young Professorship at the National University of Singapore. His research focuses on automated reasoning, aiming to enable computing systems to handle uncertain real-world environments through scalable techniques integrating randomized algorithms, statistical inference, formal methods, distribution testing, and software engineering. Core research areas: Automated Reasoning, Formal Methods, Approximate Model Counting, Probabilistic Inference, Constraint Solving His research group has achieved significant recognition in both individual awards and publications. Key trends in his recent work include advancing model counting algorithms, developing frameworks for probabilistic explanations, and improving scalability in formal verification and constraint satisfaction. His tools have consistently ranked top in international competitions, demonstrating practical impact in automated reasoning. 2019 NRF Fellowship for AI 2022 ACP Early Career Researcher Award 2020 IEEE Intelligent Systems AI's 10 to Watch Top placements in Model Counting, SAT, and CAV competitions He mentors a diverse group of PhD and Master's students and collaborates with institutions worldwide. His group's publications span premier conferences in AI, formal methods, and design automation, reflecting interdisciplinary contributions to theoretical and applied computer science.

Rachel PottingerView profile

Professor

• Data Management
• Database Systems
• Data Integration
• +7 more

Rachel Pottinger is a Professor in the Department of Computer Science at the University of British Columbia within the Faculty of Science. She has been at UBC since 2004, progressing from Assistant Professor to Associate Professor in 2012 and to full Professor in 2021. She is affiliated with research centers including CAIDA (Centre for Artificial Intelligence Decision-making and Action) and DFP (Designing for People), and is part of ICICS (Institute for Computing, Information and Cognitive Systems). Her research focuses on data management, particularly semantic data integration, metadata management, and making data more accessible and understandable to users. She leads the Data Management and Mining Lab and has supervised numerous doctoral and master's students. Her work addresses three main areas: helping people understand and explore their data, managing data not well supported by databases, and coordinating data across multiple databases. Her recent publications demonstrate strong trends in database usability, data provenance visualization, query recommendation systems, and building information modeling integration. Her work bridges theoretical database concepts with practical human-centered applications, particularly in making complex data systems more accessible to non-expert users. UBC Computer Science Department Faculty Teaching Award 2013 Computer Science Department Teaching Award 2010 CS Department Teaching Award Denice Denton Emerging Leader Award 2007 Pottinger has supervised numerous PhD and Master's students, with research focusing on data provenance, database usability, and data coordination. She has been involved in significant research projects related to data lakes, open data navigation, and query recommendation systems. Her current research explores table annotation and discovery in data lakes, query refinement for aggregation queries, and query prediction based on past user behavior. She is actively involved in the academic community, serving as Secretary-Treasurer for SIGMOD, on the VLDB Journal editorial board, and as a member of the Computing Research Association's Board of Directors. She previously served as General Co-Chair of SIGMOD 2020 and as Associate Head for the Undergraduate Program of the Department of Computer Science from 2018-2020.

Parke GodfreyView profile

Associate Professor

• Databases
• Data Mining
• Artificial Intelligence
• +7 more

Parke Godfrey is an Associate Professor in the Department of Electrical Engineering & Computer Science at York University. His research focuses on databases, data mining, and artificial intelligence, particularly cooperative query answering, skyline queries, and logic-based query optimization. PhD in Computer Science from University of Maryland, College Park (1999) MS in Information and Computer Science from Georgia Institute of Technology BS in Mathematical Sciences from University of North Carolina at Chapel Hill His current research endeavors include: SPQL (Skyline-based Preference Query Language) for extending SQL Understanding properties of skyline sets Relational algorithms for skyline computation Pareto Search for effective web search Optimizing RDBMS for data mining and scientific applications He has affiliations with: Laboratory for Computer Systems Research at York University IBM Visiting Research Scientist at IBM Toronto Laboratory

• Logic Programming
• Automated Reasoning
• Neural-Symbolic Integration
• +3 more

Dr. Krysia Broda is an Honorary Senior Lecturer in the Department of Computing at Imperial College London's Faculty of Engineering. She directs the HiPEDS CDT Programme and coordinates the PhD Teaching Scholarship Programme, actively supervising doctoral candidates. Her office is located at 180 Queen’s Gate, London SW7 2BZ, U.K., and she can be contacted via phone (+44 20 7594 8426) or email. Her research bridges logic programming , automated reasoning , and neural-symbolic integration , with applications in computational biology and multi-agent systems. Key focus areas include: Abductive/Inductive Logic Programming Answer Set Programming (ASP) for knowledge representation Probabilistic reasoning in biological networks Teleo-reactive agent policies Her publications emphasize logic-based methods in AI, spanning theoretical foundations and real-world applications like gene regulation analysis and legal case inference. Recent work shows a trend toward integrating probabilistic models with symbolic AI for complex system validation. She leads the Structured and Probabilistic Intelligent Knowledge Engineering (SPIKE) group and collaborates with the Machine Learning Group. Current projects involve distributed abductive reasoning and ASP-based theory refinement.

• Cyber-Physical Systems
• System Safety and Security
• Smart Grids
• +5 more

Edward Griffor is an Adjunct Professor in the Department of Computing and Software at McMaster University . His scholarly activity spans over four decades, focusing on Cyber-Physical Systems (CPS) , System Safety , Smart Grids , and Ontology-Based Reasoning . Griffor’s research bridges theoretical computer science with practical applications in Automated Driving Systems , Embedded Systems , and Real-Time Analytics . His work emphasizes formal methods for ensuring trustworthiness, security, and timing constraints in complex systems. Recent publications highlight trends in CPS testing frameworks , IoT capability composition , and human-centric system design . Griffor has contributed to IEEE and LNCS journals, with a particular focus on safety-critical systems and energy infrastructure.

• Declarative Programming
• Answer Set Programming
• Knowledge Representation
• +2 more

Jia-Huai You is Professor in the Department of Computing Science at the University of Alberta, where he previously served as Department Associate Chair (Graduate). His research focuses on declarative problem-solving paradigms in artificial intelligence. Research examines computational aspects of knowledge representation systems including answer set programming, constraint programming, and SMT solving. Current investigations analyze semantic foundations, computational properties, and implementation strategies for declarative systems.