Programming Semantics Professors and Supervisors in Canada | ApplySharif

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استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشی‌تان را پیدا کنید و با او ارتباط بگیرید.

نمایش ۱-۱۵ از ۲۷۶ استاد راهنما

اطلاعات این پروفایل‌ها از صفحات عمومی دانشگاه‌ها جمع‌آوری شده و ممکن است به‌روز نباشد.

Alan Ritterمشاهده پروفایل

دانشیار

McGill UniversityCanada

Alan Ritter is an Associate Professor at the School of Interactive Computing , Georgia Institute of Technology, with additional affiliation to the Machine Learning Center . His research focuses on Natural Language Processing , particularly robust models across domains/languages with fewer labels and efficient resource use, plus data-driven dialogue agents for open-topic conversations. Research Interests : Robust NLP models, cross-lingual transfer, resource-efficient learning, dialogue systems, cultural bias measurement, and privacy-aware language models Students : Mentors Ph.D. students in Georgia Tech's ML and CS programs, including Junmo Kang, Yang Chen, and Duong Minh Le. Alumni include Fan Bai (Ph.D. 2023), Yang Chen (Ph.D. 2024), and Andrew Li (M.S. 2024). Awards : NSF CAREER Award, Amazon Research Award, ACL 2024 Best Social Impact Paper, IUI 2009 Best Student Paper. Recent Work : Studies training budget allocation between supervised and preference-based finetuning, cross-lingual information extraction, cultural bias in LLMs, and privacy risk mitigation in social media disclosures. Service : Served as Program Chair for NAACL 2025, Area Chair for multiple top-tier conferences (COLM, EMNLP, ACL, EACL, AAAI). Email : alan.ritter@cc.gatech.edu

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Jackie Chit Kit Cheungمشاهده پروفایل

دانشیار

University of QuebecCanada

Jackie Chit Kit Cheung is an Associate Professor in the School of Computer Science at McGill University, where he co-directs the Reasoning and Learning Lab. He holds the Canada CIFAR AI Chair and serves as an Associate Scientific Co-Director at the Mila Quebec AI Institute. He is also a consulting researcher at Microsoft Research Montreal. Academic Background: Ph.D. in Computer Science, University of Toronto (2010–2014) M.Sc. in Computer Science, University of Toronto (2008–2010) B.Sc. (Honours) in Computer Science, minors in Linguistics and German, University of British Columbia (2004–2008) Research Interests: Jackie Cheung's research lies at the intersection of natural language processing, machine learning, and cognitive science. He focuses on natural language generation , automatic summarization , commonsense and pragmatic reasoning , and the evaluation of NLP systems . His work aims to build language models that reflect real-world structure and reasoning, with applications in health, education, and language revitalization. He is particularly interested in how implicit meaning is processed in context, a core concern in linguistic pragmatics. Publication Trends: His recent publications (2024–2025) show a strong emphasis on evaluation methodologies (e.g., COSMIC, ECBD), hallucination and factuality in language models, coreference and reasoning , and long-context modeling . He frequently collaborates across institutions and integrates insights from linguistics and psychology into NLP system design and analysis. Scientific Awards: Best Paper Award, ACL 2018 Outstanding Paper Award, NAACL 2018 Student Research Workshop SAC Award, ACL 2024 (for COSMIC) Best Poster Award, CMDO AI-Health Symposium 2024 Advising and Grants: He advises a large and diverse group of graduate students, including PhD and Master’s candidates, often in co-supervision with other faculty. His group has received support from major AI and health research initiatives, including CIFAR and Mila. He has trained alumni who have gone on to faculty and industry research positions. He has served in leadership roles in top NLP conferences, including as Senior Area Chair, Workshop Chair, and Program Chair of Canadian AI 2018. Labs and Teams: He co-directs the Reasoning and Learning Lab at McGill and is deeply involved with Mila – Quebec AI Institute . He founded the NLP Reading Group at McGill, which brings together researchers from computer science, linguistics, and information studies to discuss theoretical and applied NLP topics.

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Freda Shiمشاهده پروفایل

استادیار

University of WaterlooCanada

Freda Shi is an Assistant Professor at the David R. Cheriton School of Computer Science at the University of Waterloo and a Faculty Member at the Vector Institute, where she holds a Canada CIFAR AI Chair. She joined the University of Waterloo in July 2024 after completing her Ph.D. at the Toyota Technological Institute at Chicago. Educational Background: Ph.D. in Computer Science, Toyota Technological Institute at Chicago (2024), advised by Professors Karen Livescu and Kevin Gimpel Bachelor's degree in Intelligence Science and Technology (Computer Science Track) with a minor in Sociology, Peking University (2018) Dr. Shi's research focuses on computational linguistics and natural language processing, particularly on deeper understandings of natural language and the human language processing mechanism. She is especially interested in learning language through grounding, computational multilingualism, and related machine learning aspects. Her work aims to inform the design of more efficient, effective, safe, and trustworthy NLP systems. She leads the CompLING Lab at the University of Waterloo, which investigates how language models process spatial relationships and acquire linguistic structures through grounded experiences. Her publication record shows a consistent trajectory of high-impact research, with recent work focusing on spatial reasoning in vision-language models, multilingual chain-of-thought capabilities, and grounded language acquisition. She has published in top-tier conferences including ACL, EMNLP, ICLR, and NAACL, with several papers receiving notable recognition including Best Paper Nominee status at multiple venues. Her research bridges theoretical linguistics with practical NLP applications, demonstrating how linguistic insights can improve AI systems. Scientific Recognition: Canada CIFAR AI Chair (2024) Google Ph.D. Fellowship Thesis of Distinction for her doctoral work Multiple Best Paper Nominee awards at major NLP conferences Dr. Shi teaches CS 784: Computational Linguistics and CS 486/686: Introduction to Artificial Intelligence at the University of Waterloo. She actively contributes to the NLP research community through conference participation, program committee service, and collaborative projects. Her research has significant implications for creating more robust, human-like language understanding systems and advancing the field of grounded language learning in artificial intelligence.

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Peter Selingerمشاهده پروفایل

استاد

Dalhousie UniversityCanada

Peter Selinger is a Professor in the Department of Mathematics and Statistics at Dalhousie University , with a cross-appointment in Computer Science. He specializes in mathematical methods in computer science, particularly quantum computing and combinatorial game theory . His work on quantum programming languages like Quipper and foundational research in category theory has garnered international recognition. Education : Ph.D. in Mathematics (University of Pennsylvania, 1997), undergraduate studies in Mathematics (Technische Universität Darmstadt). Research Interests span quantum computing, category theory, and combinatorial game theory. He has pioneered formalisms for quantum programming languages, developed categorical models for quantum mechanics, and analyzed game-theoretic structures in games like Hex. His recent work includes linear dependent type theory , quantum circuit synthesis , and combinatorial game classification . Publications demonstrate expertise in quantum programming languages, categorical semantics, and game theory. Key trends include Hamiltonian simulation , Clifford+T circuits , and monotone game realization . Scientific Honors include the Killam Professorship (2017–2022), Faculty of Science Award for Excellence in Teaching (2023), and fellowships from the Alfred P. Sloan Foundation and German National Scholarship Foundation . Students he has supervised include PhD graduates Xiaoning Bian , Francisco Rios , and Neil J. Ross , along with MSc students like Fahimeh Bayeh and Seth Greylyn . He has advised 16 postdoctoral researchers.

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Zhenman Fangمشاهده پروفایل

دانشیار

Simon Fraser UniversityCanada

Dr. Zhenman Fang is an Associate Professor at the School of Engineering Science , Simon Fraser University (SFU) , where he founded and directs the HiAccel Lab . He also holds an associate membership in the School of Computing Science at SFU. His research focuses on customizable computing with software-defined hardware acceleration , addressing performance, energy-efficiency, and reliability in post-Moore’s law computing across domains like machine learning , big data analytics , quantum chemistry , and precision medicine . Education: Ph.D. in Computer Science from Fudan University (2014), with a visit to University of Minnesota during his studies. Postdoctoral Work: University of California, Los Angeles (UCLA) (2014-2017). Industry Experience: Staff Software Engineer at Xilinx (2017-2019). Dr. Fang’s research spans the entire computing stack , including application characterization , accelerator-rich architecture design , and programming/tool support . He has developed frameworks like HiSpMV , SyncNN , and SQL2FPGA , emphasizing FPGA acceleration for vision transformers , quantum chemistry , and spiking neural networks . His work has been recognized with 3 best paper awards (FPL 2024, TCAD 2019, MEMSYS 2017) and 3 best paper nominees (FCCM 2025, HPCA 2017, ISPASS 2018). Recent publications highlight trends in low-precision machine learning ( ShiftQuant , ESRU ), quantum chemistry acceleration ( SERI ), and vision transformer optimization ( Quasar-ViT ). His HiAccel Lab actively mentors PhD and MASc students , with notable graduates like Alec Lu (PhD 2024, now at Meta) and Philip Stachura (MASc, now with BC Graduate Scholarship). Scientific Awards: Inaugural SFU Research Excellence Award - Horizon Award (2025) FPL 2024 Stamatis Vassiliadis Best Paper NSERC Alliance Award (2020) CFI JELF Award (2019) Xilinx University Program Award (2019) IEEE Senior Member (2023) Grants: NSERC Discovery Grant (2019) CFI JELF Funding (2019) Huawei and Xilinx sponsorships Dr. Fang leads open-source initiatives like SyncNN , PASTA , and SQL2FPGA , and serves as General Chair for ASAP 2025 and Program Co-Chair for RAW 2025 . His lab collaborates globally with institutions such as UCLA , Northeastern University , and Xidian University .

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Caroline Lemieuxمشاهده پروفایل

استادیار

University of British ColumbiaCanada

Caroline Lemieux is an Assistant Professor at the Department of Computer Science, University of British Columbia (UBC), with research focused on advancing software correctness, security, and performance through innovative testing and synthesis techniques. Her work bridges Programming Languages and Software Engineering , particularly in fuzz testing, specification mining, and program synthesis. PhD from University of California, Berkeley (2021), advised by Koushik Sen Postdoctoral researcher at Microsoft Research, NYC (2021-2022) Key contributions: FuzzFactory , CodaMOSA , Arvada , and Gauss Her research integrates machine learning with traditional testing methods, exemplified by projects like RLCheck (reinforcement learning for test generation) and AutoPandas (neural synthesis for dataframes). Recent publications analyze generator-based fuzzing challenges and propose hybrid strategies combining coverage feedback with AI-driven insights. Scientific Awards : ACM/SIGSOFT Best Paper Award (ESEC/FSE 2019) ACM/SIGSOFT Tool Demonstration Award (ISSTA 2019) ACM/SIGSOFT Distinguished Artifact Award (ISSTA 2019) NSERC Postgraduate Scholarship-Doctoral (PGS D) UBC Governor General's Silver Medal (2016) Teaching roles include: 2025W2: CPSC 539L - Topics in Programming Languages 2024W2: CPSC 410 - Advanced Software Engineering 2023W2: CPSC 410 (with Alex Summers) She supervises graduate and undergraduate researchers working on projects like ExploTest (automated unit test generation) and GRIMOIRE (grammar extraction from pseudo-rules). Her research team collaborates with institutions including Microsoft Research, Google, and academic partners in systems security and AI-driven testing.

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Charles Yangمشاهده پروفایل

استاد

University of QuebecCanada

Charles Yang is a Professor of Linguistics and Computer Science at the University of Pennsylvania , where he also directs the Cognitive Science Program. His research integrates computational models with studies of language acquisition, processing, and evolution. Education: Ph.D. in Computer Science, MIT, 2000 Yang's work spans language acquisition , computational linguistics, and the evolution of cognition. He has authored The Price of Linguistic Productivity (2016), which received the Leonard Bloomfield Award from the LSA. Recent publications focus on large language models as cognitive models, the Chinese aspectual system , and statistical approaches to linguistic patterns. His 15 most recent articles (2025-2021) demonstrate a trajectory from computational models of language change to machine translation and multiword expression analysis . Yang has received significant funding from the National Science Foundation and the Guggenheim Foundation . He co-directs the Integrated Language Science and Technology group with John Trueswell and mentors students in linguistics, computer science, and psychology.

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Jelle Hellingsمشاهده پروفایل

استادیار

McMaster UniversityCanada

Jelle Hellings is an Assistant Professor in the Department of Computing and Software at McMaster University , Canada. His research focuses on high-performance large-scale data management systems with a strong theoretical and algorithmic component, including resilient systems (blockchains) , graph databases , and external-memory algorithms . He previously worked as a Postdoc Scholar at the University of California, Davis and earned his PhD from Hasselt University in Belgium. Education: Doctor of Sciences in Computer Science (2018), Hasselt University Master of Science in Computer Science and Engineering (2011), Eindhoven University of Technology His research interests include scalable resilient systems with Byzantine fault tolerance, database theory, graph query languages, constraints on graph data, and external-memory algorithms for large graph datasets. He has authored numerous high-impact publications on blockchain-based resilient systems, query optimization in graph databases, and theoretical advancements in relation algebra expressiveness. Hellings actively contributes to academic service through program committee memberships and tutorial organization, and he currently teaches courses on future resilient databases and foundational computer science topics.

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Dirk Bernhardt-Waltherمشاهده پروفایل

استاد

University of TorontoCanada

Professor Dirk Bernhardt-Walther is an academic at the University of Toronto, serving as Program Director of the Cognitive Science Program and Department of Psychology . He investigates neural and computational mechanisms underlying high-level sensory perception, focusing on real-world scenes, mid-level vision, and visual aesthetics. Education: PhD in Computation and Neural Systems (Caltech, 2006), M.Phil (University of Cambridge) Research Focus: His lab employs fMRI, MEG, EEG , and GAN-generated stimuli to study scene categorization, perceptual organization, and aesthetic processing. Recent work explores curvature perception, emotion representation in scenes, and neural dissociations between computational and subjective visual metrics. Laboratory Members: The Bernhardt-Walther Lab includes PhD students like Gaeun Son (scene perception), Charlotte Leferink (scene representation), and Dela Farzanfar (aesthetic processing), alongside postdocs and collaborators. Advising: Supervises graduate students in projects combining computational modeling, psychophysics, and neuroimaging, particularly those with backgrounds in computer science or cognitive neuroscience.

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Diana Inkpenمشاهده پروفایل

استاد

University of OttawaCanada

Professor Diana Inkpen is a faculty member at the School of Electrical Engineering and Computer Science, University of Ottawa. She holds a Ph.D. from the University of Toronto's Department of Computer Science and degrees from the Technical University of Cluj-Napoca, Romania (M.Sc. and B.Eng.). Her research focuses on computational linguistics, natural language processing (NLP), and artificial intelligence, with specialties in natural language understanding/generation, lexical semantics, and semantic web agents. Education: Ph.D., Computer Science, University of Toronto M.Sc., Computer Science and Engineering, Technical University of Cluj-Napoca B.Eng., Computer Science and Engineering, Technical University of Cluj-Napoca Affiliations: Director, NLP Lab Editor-in-Chief, Computational Intelligence journal Associate Editor, Natural Language Engineering journal Her research has led to roles such as program co-chair for AI 2012 and leadership in organizing international workshops. She has received funding from NSERC, SSHRC, and OCE, and was honored with a Visiting Professor title at the University of Wolverhampton, UK. Her teaching spans courses like Information Retrieval, Natural Language Processing, and Prolog programming. Professor Inkpen's work bridges NLP innovations with societal challenges, including mental health surveillance via social media analysis and bias mitigation in AI systems. She actively contributes to interdisciplinary projects, such as detecting hate speech and legal text entailment, while maintaining a global research network through collaborations and international conference involvement.

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Angel Xuan Changمشاهده پروفایل

دانشیار

Simon Fraser UniversityCanada

Angel Xuan Chang is an Associate Professor at Simon Fraser University's School of Computing Science, where she leads research at the intersection of natural language processing, computer vision, and 3D scene understanding. She holds the prestigious Canada CIFAR AI Chair position and is affiliated with multiple research groups including 3DLG, GrUVi, SFU NatLang, SFU AI/ML, and VINCI. PhD in Computer Science, Stanford University MSc in Computer Science, Stanford University M.Eng in Electrical Engineering and Computer Science, MIT BSc in Computer Science and Engineering, MIT Professor Chang's research primarily focuses on connecting language to 3D representations of shapes and scenes, with particular emphasis on grounding language for embodied agents in indoor environments. Her work spans natural language processing and understanding, linking natural language with visual and 3D representations, multimodal grounding of language, embodied AI, and machine learning applications for biodiversity monitoring through the BIOSCAN project. She has developed methods for synthesizing 3D scenes and shapes from natural language and created various datasets for 3D scene understanding. Her recent publications reveal a strong trend toward integrating language understanding with 3D scene generation and manipulation, with increasing focus on practical applications in embodied AI and biodiversity monitoring. The research shows progression from foundational work on text-to-3D scene generation to more sophisticated approaches for evaluating semantic coherence in generated scenes and developing efficient methods for zero-shot scene modeling. Canada CIFAR AI Chair TUM-IAS Hans Fischer Fellow (2018-2022) Best paper award at 3DV 2025 for 'An Object is Worth 64x64 Pixels: Generating 3D Object via Image Diffusion' Professor Chang actively advises numerous graduate students who appear as first authors on her publications, indicating a strong mentoring program. Her research is supported through multiple channels including the CIFAR AI Chair position and likely various research grants supporting her BIOSCAN-related work and 3D scene understanding projects. She has been involved in organizing multiple workshops at major conferences including ICML, CVPR, and ICLR. Her research is conducted through several interconnected groups: 3DLG (3D Language and Graphics), GrUVi (Graphics, Vision, and Interaction), SFU NatLang (Natural Language Processing), SFU AI/ML, and VINCI. These groups work collaboratively on problems spanning language grounding, 3D scene understanding, embodied AI, and biodiversity applications, creating a rich interdisciplinary research environment.

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Xiaohui Yuمشاهده پروفایل

استاد

York UniversityCanada

Xiaohui Yu is a Professor and Graduate Program Director in the School of Information Technology at York University. He holds a BSc from Nanjing University, an MPhil from the Chinese University of Hong Kong, and a PhD from the University of Toronto. His research focuses on the intersection of data management and machine learning, including ML-based database systems, large-scale machine learning, and spatio-temporal data analysis in contexts like intelligent transportation systems and social networks. Supported by grants from NSERC and industry partners, his work has been published in top venues such as SIGMOD, VLDB, and TKDE. He serves as an Associate Editor for journals like IEEE TKDE and ACM TKDD, and actively participates in conference program committees. Education: BSc (Nanjing University), MPhil (Chinese University of Hong Kong), PhD (University of Toronto). Research Interests: Big data management, database systems, machine learning, spatio-temporal data analytics, and video query processing. Recent articles emphasize ML-driven database components, efficient video query optimization, and scalable algorithms for large-scale data. His work addresses challenges in query processing, indexing, and real-time systems. Service: Serves on editorial boards (e.g., Information Systems), and chairs/workshops (e.g., Symposium on Data Markets). Active in program committees for SIGMOD, ICDE, and other leading conferences. Advising & Grants: Directs graduate programs and leads research groups. Collaborates with industry on data marketplaces and AI model integration. No specific student names listed, but actively recruits PhD/Master’s candidates.

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Soo Jeonمشاهده پروفایل

استاد

University of WaterlooCanada

Mechatronics
Robotics
Control Systems
+۷ مورد دیگر

Soo Jeon is a Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo, part of the Faculty of Engineering. He holds a PhD from the University of California at Berkeley (2007) and prior degrees from Seoul National University. His research focuses on mechatronics, dynamic systems, and control, with applications in robotics, autonomous systems, and precision motion control. He has held roles as Assistant Professor (2009–2015), Associate Professor (2015–2024), and Full Professor (2024–present). Professor Jeon’s expertise includes intelligent sensing and control for mechatronic systems, nonlinear dynamics, and autonomous systems. He has received notable awards such as the 2022 Engineer of the Year Award (AKCSE/KOFST), 2015 NSERC Discovery Accelerator Supplement, and 2010 ASME Rudolf Kalman Best Paper Award. He serves as an Associate Editor for several journals, including the ASME Journal of Dynamic Systems and IEEE Transactions on Automation Science and Engineering. His research interests span robotics, control systems, and automation, with recent work on autonomous navigation, tactile exploration, and model predictive control. He supervises graduate students in MASc and PhD programs and teaches courses like ME 649 (Control of Machines and Processes) and ME 360 (Introduction to Control Systems). Jeon holds patents in areas like low-power magnetic locks and remote plasma source seasoning. His lab, the Waterloo Mechanical Systems & Control Laboratory (WMSCL), focuses on advanced mechatronics and robotics projects, including collaborations with international institutions such as the Korea Institute of Machinery & Materials (KIMM).

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Karim El-Basyounyمشاهده پروفایل

استاد

University of AlbertaCanada

Dr. Karim El-Basyouny is a Killam Laureate Professor and City of Edmonton Urban Traffic Safety Research Chair at the University of Alberta's Faculty of Engineering, where he serves as Associate Dean (Research Infrastructure and Innovation) in the Civil and Environmental Engineering Department. A licensed Professional Engineer in Alberta, he holds advanced degrees in Transportation Engineering from the University of British Columbia and has dedicated his career to advancing road safety through data-driven management frameworks. His academic credentials include: Doctor of Philosophy, Civil Engineering, University of British Columbia, 2011 Engineering Management Sub-specialization, Civil Engineering, University of British Columbia, 2010 Master of Applied Science, Civil Engineering, University of British Columbia, 2006 Bachelor's degree (ABET Equivalent), Civil & Environmental Engineering, United Arab Emirates University, 2003 El-Basyouny's research pioneers the integration of remote sensing, machine learning, and statistical modeling to enhance transportation safety. His work develops automated tools for infrastructure digitization, collision prediction, and speed management, treating safety as a systemic product requiring management frameworks. Key contributions include LiDAR-based road feature extraction, network-level safety evaluations, and frameworks for vision-zero outcomes that address both human-driven and autonomous vehicle contexts. His recent publications demonstrate a cohesive research trajectory centered on leveraging point cloud data and computational intelligence for safety management. Over 15 major publications since 2021 focus on automated infrastructure assessment (light pole detection, clear zone mapping, vertical clearance evaluation), weather-impact modeling, and enforcement resource optimization. This body of work bridges transportation engineering with computer vision and operations research to create scalable safety solutions. His scientific contributions have been recognized with prestigious honors including: 2024 Killam Annual Professorship Award 2024 Road Safety Achievement Award from TAC 2023 Donald Stanley Award for environmental engineering 2022 Faculty of Engineering Graduate Teaching Award 2021 Daniel B. Fambro Student Paper Award As an academic leader, El-Basyouny actively mentors graduate students and secures significant research funding through his endowed chair position. He currently recruits fully-funded PhD and postdoctoral candidates specializing in remote sensing applications, machine learning, and geomatics for road digitization projects. His research group collaborates with national safety committees and municipal agencies to translate findings into policy, while he serves on editorial boards for Transportation Research Record and Analytic Methods in Accident Research. The research group operates at the intersection of transportation engineering and computational science, developing automated frameworks that merge sensor technologies with data processing tools. Current projects focus on semantic segmentation of 3D point clouds, safety implications of infrastructure digitization, and machine learning applications for road feature extraction in both urban and rural environments.

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Alexander Summersمشاهده پروفایل

دانشیار

University of British ColumbiaCanada

Alexander Summers is an Associate Professor at the Department of Computer Science , University of British Columbia . He joined UBC in March 2020 after serving as a Senior Researcher (Oberassistent) at ETH Zurich from 2014-2020. His research bridges Programming Languages , Formal Methods , and Software Engineering , with a focus on automated verification tools for heap-based and concurrent programs. MSc Joint Mathematics and Computer Science, Imperial College London (2004) PhD Computer Science, Imperial College London (2009) Postdoc, ETH Zurich (2009-2014) Summers leads the Prusti Project , developing deductive verification tools for Rust, and contributes to the Viper Project for intermediate verification languages. His work addresses challenges in: Memory safety and concurrency verification Ownership models and aliasing control Automated reasoning with SMT solvers Resource-oriented programming specifications Debugging verification condition quantifiers Formal validation of verification infrastructure His research has been recognized with a Amazon Research Award and ACM SIGPLAN Distinguished Paper Awards . He teaches courses like Advanced Software Engineering and Program Verifiers and Program Verification , and supervises graduate students in formal verification and Rust-related research.

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