جست‌وجوی استاد و پژوهشگر

Thomas Trappenbergمشاهده پروفایل

استاد

• Computational Neuroscience
• Machine Learning
• Neural Computation
• +۳ مورد دیگر

Dr. Thomas Trappenberg is a Professor in the Faculty of Computer Science at Dalhousie University. He is affiliated with the HAL Lab and the Big Data Analytics, AI & Machine Learning research cluster. His work bridges computational neuroscience and machine learning, contributing significantly to both research and education. PhD, Aachen University (1992) MSc, Aachen University (1989) Dr. Trappenberg's research focuses on computational neuroscience and machine learning , particularly in modeling neural systems and brain function. His work includes theoretical and applied aspects of neural computation, with implications for artificial intelligence and cognitive modeling. He is the author of the widely used textbook Fundamentals of Computational Neuroscience , now in its second edition, which integrates mathematical modeling with biological plausibility in neural systems. His recent publications center on foundational models in computational neuroscience, emphasizing neural dynamics, learning rules like Hebbian learning, and neural network architectures such as continuous attractor neural networks (CANN). These works span disciplines including neuroscience, artificial intelligence, and applied mathematics, with subfields such as neural modeling, synaptic plasticity, cognitive modeling, and neural dynamics. Funding: NSERC, CIHR Dr. Trappenberg has made significant contributions through his textbook and associated teaching resources, including MATLAB programs for neural simulations. He teaches undergraduate and graduate courses such as CSCI 1106: Animated Computing, CSCI 4150: Artificial Intelligence, CSCI 6508: Neural Computation, and NESC 4177: Theoretical Neuroscience. He advises students and supports research training through the HAL Lab, fostering interdisciplinary work in AI and neuroscience. He leads the HAL Lab, which is part of Dalhousie’s Big Data Analytics, AI & Machine Learning research cluster. The lab develops computational models of brain function and supports educational initiatives in neural computation.

Kyle Mahowaldمشاهده پروفایل

استادیار

• Computational Linguistics
• Machine Learning
• Cognitive Science
• +۴ مورد دیگر

Kyle Mahowald serves as an Assistant Professor in the Department of Linguistics at the University of Texas at Austin. His work bridges computational linguistics, machine learning, and cognitive science, focusing on extracting insights about human language from large language models and exploring information-theoretic explanations for linguistic variation across languages. Education: M.Phil in Linguistics (University of Oxford), Ph.D. in Cognitive Science (Massachusetts Institute of Technology), Postdoctoral Researcher in the Stanford Natural Language Processing Group. His research investigates the distinction between formal linguistic competence (rule-based knowledge) and functional competence (practical language use in real-world contexts), with implications for understanding both human cognition and AI capabilities. He actively contributes to interdisciplinary studies through publications in venues like ACL, EMNLP, NeurIPS, and Cognition. Awards include the Outstanding Paper Award at EMNLP and the National Science Foundation's CAREER grant, reflecting his impact in computational linguistics and cognitive science. Kyle participates in the "Using Language Models for Linguistics" session at the 2024 ISC Summer School, where he will discuss the scientific and ethical dimensions of large language models.

Gary Lupyanمشاهده پروفایل

استاد

• Cognitive Science
• Linguistics
• Psychology
• +۳ مورد دیگر

Gary Lupyan is a Professor of Psychology at the University of Wisconsin-Madison , focusing on the interplay between language and cognition. His research investigates how natural language shapes human cognition, the evolutionary origins of language, and its adaptive mechanisms for learners and users. He actively engages in interdisciplinary discussions, particularly in events addressing the implications of Large Language Models (LLMs) for understanding cognition. On June 12, he participated in a session titled What counts as understanding? as part of a summer school program, contributing to panels on benchmarking LLMs and lessons from computer vision.

Josh Tenenbaumمشاهده پروفایل

استاد

• Computational Cognitive Science
• Artificial Intelligence
• Bayesian Inference
• +۸ مورد دیگر

Josh Tenenbaum is a Professor of Computational Cognitive Science at the Massachusetts Institute of Technology , affiliated with the Department of Brain and Cognitive Sciences , CSAIL , and CBMM . His research focuses on computational models of human cognition, integrating Bayesian inference, probabilistic programming, and machine learning with behavioral experiments in adults and children. Research spans concept learning, causal reasoning, word meaning acquisition, and theory-of-mind modeling. Recent publications emphasize neuro-symbolic integration, physical reasoning, and adaptive world modeling. Awards include multiple Cognitive Science Computational Modeling Prizes and IEEE CVPR/NIPS recognitions.

• Philosophy of Cognitive Science
• Artificial Intelligence
• Philosophy of Technology
• +۵ مورد دیگر

Karina Vold is an Assistant Professor at the University of Toronto's Institute for the History and Philosophy of Science and Technology (IHPST), cross-appointed to the Department of Philosophy. She holds multiple prestigious positions including PI at the Periscope Research Lab, AI2050 Early Career Fellow at Schmidt Sciences Foundation, Research Lead at the Schwartz Reisman Institute for Technology and Society, Associate Fellow at the University of Cambridge's Leverhulme Centre for the Future of Intelligence, Faculty Fellow at Victoria College, and Faculty Associate at the University of Toronto's Centre for Ethics. BA in Philosophy and Political Science from University of Toronto PhD in Philosophy from McGill University Postdoctoral Research Associate at the Leverhulme Centre for the Future of Intelligence, University of Cambridge Vold specializes in the intersection of Philosophy of Cognitive Science, Philosophy of Technology, Artificial Intelligence, and Applied Ethics. Her research spans extended cognition, ethical design of AI systems, effects of AI on human cognition and autonomy, and evaluation of existential threats from AI. She has published extensively on neuroprosthetics, human-AI cognitive teaming, trust in AI healthcare applications, and the philosophical implications of large language models. Her work bridges theoretical philosophy with practical ethical considerations in emerging technologies. Vold's scholarly output demonstrates a clear trajectory from foundational work on extended cognition to increasingly applied research on AI ethics and governance. Her publications reveal a growing focus on practical applications of philosophical frameworks to real-world AI systems, with particular attention to human-centered approaches to AI evaluation and design. Recent work shows strong engagement with interdisciplinary collaborations, spanning philosophy, computer science, neuroscience, and healthcare domains. 2021 Schwartz Reisman Institute Faculty Fellowship AI2050 Early Career Fellow, Schmidt Sciences Foundation Vold actively engages with students through graduate seminars on Cognitive Technologies and undergraduate courses like The Limits of Machine Intelligence. She has secured significant research funding through her fellowships and institutional affiliations, particularly with the Schwartz Reisman Institute and Schmidt Sciences Foundation. Her work regularly attracts media attention, with interviews in major outlets including CBC News, MIT Tech Review, The Guardian, and University of Toronto Magazine. She frequently participates in high-profile academic events and conferences on AI ethics and philosophy of technology. Vold leads the Periscope Research Lab and collaborates extensively with the Schwartz Reisman Institute for Technology and Society, the Leverhulme Centre for the Future of Intelligence, and the Centre for Ethics. Her research teams typically include interdisciplinary members from philosophy, computer science, cognitive science, and ethics backgrounds, reflecting her commitment to bridging theoretical and practical approaches to AI development and deployment.

Blake Richardsمشاهده پروفایل

استادیار

• Artificial Intelligence
• Neuroscience
• Machine Learning
• +۳ مورد دیگر

Blake Richards is an Assistant Professor at McGill University with dual appointments at The Montreal Neurological Institute-Hospital (The Neuro) and the School of Computer Science. His research bridges artificial intelligence and neuroscience to uncover universal principles of intelligence applicable to both biological and artificial systems. His laboratory focuses on two interconnected research thrusts: (1) developing machine learning models to decode brain function in decision-making and learning processes, and (2) applying AI to extract meaningful signals from complex neuroscience datasets. A core objective is leveraging biological intelligence insights to engineer next-generation AI systems with human-like capabilities currently absent in machines. Dr. Richards is a vocal advocate for open science, committing to open-access publications and active utilization of shared datasets. He emphasizes Montreal's unique ecosystem—where global AI leadership converges with neuroscience excellence—as critical for his interdisciplinary work. His major accolades include: Canadian Association for Neuroscience Young Investigator Award (2019) CIFAR Canada AI Chair (2018) While specific advising roles and grant details aren't documented in source materials, his CIFAR Chair position implies active research funding and mentorship within McGill's AI-neuroscience nexus. His lab functions as an interdisciplinary hub where computational models and neural data analysis advance dual frontiers in understanding intelligence.

Ritwik Guptaمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۵ مورد دیگر

Ritwik Gupta is an Assistant Professor (starting Fall 2026) at the University of Maryland in the Department of Computer Science and the AI Interdisciplinary Institute. Concurrently, he serves as Technical Director for Autonomy at the Defense Innovation Unit (DIU) , focusing on AI governance and dual-use military-civil technology. Research Interests: His work bridges Artificial Intelligence , Computer Vision , and Technology Policy , with specific interests in physics-integrated vision models, multi-robot perception systems, AI governance frameworks, and climate modeling through hybrid physics-ML approaches. He advocates for data-centric policies over model-focused regulations and explores the societal implications of AI proliferation. Article Trends: Recent publications emphasize Bayesian behavior in LLMs through in-context learning Multi-scale geospatial analysis for climate and satellite imagery Critical evaluations of AI export control policies Advancements in vision-language interaction and dataset curation Awards: Best Paper at NeurIPS 2023 (D&B track) for ClimSim Timothy B. Campbell Innovation Award (2024) Outstanding Reviewer for CVPR 2025 Prospective Students: He encourages applicants to the University of Maryland CS Ph.D. or Public Policy Ph.D. programs to mention his name for advising opportunities, particularly in physics-integrated computer vision , multi-robot perception , and AI governance .

• Literacy
• Early Childhood Education
• Educational Psychology
• +۹ مورد دیگر

Marie-France Morin is a Professor at the Faculty of Education, Université de Sherbrooke , specializing in literacy development, learning disabilities, and educational interventions. She holds a PhD in Psychopedagogy (2002) and a Master’s in Psychopédagogie (1998) from Université Laval. Research Focus: Literacy, graphomotor skills, orthography, educational technology, and preventive strategies for at-risk learners. Awards: Mérite Estrien 2010 Best Thesis in Educational Sciences in Québec (2004) Excellence Doctoral Thesis Award (2003) Grants & Projects: Led/Co-led 22+ grants, including FRQSC-ANR France-Québec Project NumEc (2016-2023), BMO-funded literacy research (2017-2023), and TD Bank initiatives (2017-2023). International Collaborations: Co-founder of the International Symposium on Educational Literacy (SILE), with events in Canada, France, Portugal, Chile, and the Czech Republic. Recent Publications: 15+ articles on orthographic development, handwriting in dyslexia, tablet-based writing, and pedagogical practices (2022-2007).

Raviraj Adveمشاهده پروفایل

استاد

• Wireless Communications
• Radar Signal Processing
• Cooperative Networks
• +۷ مورد دیگر

Professor Raviraj Adve is affiliated with the University of Toronto , working in the Department of Electrical and Computer Engineering and cross-listed with the Electromagnetics Group . He holds a PhD in Electrical Engineering from Syracuse University (1996) and previously worked at Research Associates for Defense Conversion Inc. (1997–2000). Education: B.Tech, Indian Institute of Technology Bombay (1990) PhD, Syracuse University (1996) Research Interests span two main areas: Wireless Communications (heterogeneous networks, massive MIMO, cooperative communication, resource allocation) and Radar Signal Processing (waveform diversity, space-time adaptive processing, HF radar systems). His work emphasizes practical algorithm development for real-world constraints. Scientific Contributions include 15 recent articles covering cooperative networks , radar clutter modeling , low-complexity MIMO algorithms , and molecular communication . Notable awards: IEEE Fellow (2017), Young Radar Engineer of the Year (2009), and multiple teaching awards. Leadership Roles: Vice-chair of IEEE Radar Systems Panel, Associate Editor for IEEE Trans. on Aerospace and Electronic Systems , and editorial board member for IET Trans. on Radar, Sonar and Navigation .

Georg Northoffمشاهده پروفایل

استاد

• Neuroscience
• Philosophy
• Psychiatry
• +۷ مورد دیگر

Dr. Georg Northoff is a Professor at the University of Ottawa's Faculty of Medicine and cross-appointed member of the Mind, Brain Imaging and Neuroethics Research Unit at The Royal's Institute of Mental Health Research. Holding degrees in philosophy, neuroscience, and psychiatry, he bridges disciplines to investigate the brain-mind connection , focusing on self , consciousness , and mental disorders . MD, University of Bochum MA in Medicine, University of Muenchen PhD, University of Magdeburg His spatiotemporal neuroscience framework explores how brain dynamics generate subjective phenomena. Recent work includes AI consciousness, depression as a temporal disorder, and locked-in syndrome diagnostics. Awards include Fellow of the Royal Society of Canada and recognition as an Expertscape 'Expert' in Cerebral Cortex research . 15+ recent publications on brain dynamics, self-theory, and clinical applications International lectures and media features (Moscow, Armenia, podcast appearances) Lead on Canada-UK AI Initiative grant for brain-environment interaction research

Morad Benyoucefمشاهده پروفایل

استاد

• Computer Science
• Information Systems
• E-Commerce
• +۵ مورد دیگر

Professor Morad Benyoucef is a Full Professor at the University of Ottawa, affiliated with the Telfer School of Management. His academic journey includes a Ph.D. in Computer Science from Université de Montréal, an M.Sc. from Rochester Institute of Technology, and a B.Sc. from Constantine University. Education: B.Sc., Constantine University M.Sc., Rochester Institute of Technology Ph.D., Université de Montréal Benyoucef's research spans interdisciplinary domains at the intersection of Computer Science and Business, focusing on Online Marketplaces , Social Commerce , and Data Monetization . His work examines Web 2.0 applications, e-health systems, and digital negotiation frameworks through both empirical and theoretical lenses. Recent publications demonstrate expertise in Human-Computer Interaction , Behavioral Modeling , and Digital Commerce . His research program receives funding from NSERC CREATE, MITACS Accelerate, and NSERC Discovery Grants, with a focus on predictive analytics, social commerce platforms, and inside sales optimization. Scientific Awards: Associate Editor, Electronic Commerce Research Journal Associate Editor, Telecommunication Systems Journal Reviewer for international journals Benyoucef also contributes to academic leadership by supervising graduate students across the Ottawa Carleton Institute of Computer Science Program and the E-business Technologies Program, while teaching Management Information Systems and E-Business at both undergraduate and graduate levels.

Paulo Bliksteinمشاهده پروفایل

استاد

• Constructionism
• Learning Analytics
• Human-Computer Interaction (HCI)
• +۱۲ مورد دیگر

Paulo Blikstein is a Professor in the Department of Mathematics, Science and Technology at Teachers College, Columbia University, where he leads the Transformative Learning Technologies Lab (TLTL) . He previously held faculty positions at Stanford University and maintains strong interdisciplinary ties across computer science, education, and human-computer interaction. His research spans constructionist learning, learning analytics, data science education, and maker-based pedagogy. Research Interests: Core focus on constructionism , inspired by Seymour Papert, emphasizing learning through creating. Development of tangible and embodied interfaces for STEM learning. Innovation in multimodal learning analytics to assess student behavior in open-ended tasks. Advancing equitable and inclusive models for AI and computing education. Design and scaling of biology cloud labs and no-code data science tools for youth. Recent Research Trends: His latest work (2022–2025) shows a strong focus on integrating computational modeling with real-world data in middle school science, developing no-code platforms for community data science, and analyzing sustainability challenges in classroom technology adoption. He emphasizes teacher-driven curriculum design and systemic implementation of maker education globally. Scientific Awards: Best Pictorial Award Honorable Mention (ACM) Honorable Mention Short Paper Advising and Grants: He actively mentors graduate students, postdocs, and visiting scholars in the TLTL. His lab partners with schools, museums (e.g., New York Hall of Science), and policy makers to translate research into practice. Projects are funded by competitive grants, including awards from Columbia University’s School of Engineering and national competitions like the Learning Engineering Tools Competition. Labs and Teams: He directs the Transformative Learning Technologies Lab (TLTL) , a multidisciplinary research group focused on designing, researching, and scaling innovative STEM education technologies. The lab collaborates with institutions in Brazil, Switzerland, and China, and works closely with educators to ensure real-world impact.

• Neurosciences
• Cognitive Neuroscience
• Atypical Dementias
• +۸ مورد دیگر

Alexandru Hanganu is an Adjunct Professor in the Department of Psychology, Faculty of Arts and Sciences, at the University of Montreal, Canada (2019-2023). He previously held an Associate Professor position at the same institution (2017-2019) and completed postdoctoral training at the University of Montreal and University of Calgary. His research focuses on neurodegenerative diseases, particularly Alzheimer's and Parkinson's, integrating Magnetic Resonance Imaging Machine Learning Neuropsychological Assessment Photochemical Switches Cognitive Neuroimaging methodologies. His recent publications examine topics such as longitudinal brain changes in Parkinson's disease peripheral nervous system complications in COVID-19 neuropsychiatric symptoms in Alzheimer's , reflecting his interest in diagnostic innovation and cognitive neurology. He has received the Étudiant-chercheur étoile award from Fonds de recherche du Québec - Santé (FRQS) in 2015.

• Neuroscience
• Psychiatry
• Epidemiology and Biostatistics
• +۷ مورد دیگر

Tomas Paus is a Professor at the Université de Montréal , holding joint appointments in the Department of Psychiatry and Addictology and Department of Neuroscience within the Faculty of Medicine . He is also a researcher at the CHU Sainte-Justine Research Center and contributes to interdisciplinary research through affiliations with IVADO and OPES . Specializes in Population Neuroscience integrating epidemiology, genetics, and brain imaging Published over 71,000 citations with Springer and MIT Press Active in lifespan brain development research across North America, South America, and Europe Scientific Contributions: Recipient of the Royal Society Wolfson Merit Award and Masaryk University Gold Medal Co-founder of Digital Ethology as a field of study Associate Editor of Human Brain Mapping and Social Neuroscience Research Themes: Developmental origins of mental health Environmental influences on brain maturation Gene-environment interactions

John Konstantine Tsotsosمشاهده پروفایل

استاد پژوهشی

• Computer Vision
• Visual Attention
• Active Vision Systems
• +۵ مورد دیگر

John Konstantine Tsotsos is a Research Professor in the Department of Electrical Engineering and Computer Science at Lassonde School of Engineering, York University . He is a member of the Centre for Innovation in Computing and the Centre for Vision Research at York, as well as an Adjunct Professor in the Department of Ophthalmology and Vision Sciences at the Temerty Faculty of Medicine, University of Toronto . Education Ph.D. in Computer Science, University of Toronto (1980), titled A Framework for Visual Motion Understanding M.Sc. in Computer Science, University of Toronto (1976) B.A.Sc. (Honours) in Engineering Science (Computer Science Option), University of Toronto (1974) Dr. Tsotsos is a world leader in interdisciplinary vision science , spanning human and computational vision . His Selective Tuning theory revolutionized visual attention research, predicting novel aspects of top-down processing in perception. Contributions include computational complexity of vision , active perception systems , and medical image analysis . His work underpins advancements in robotic vision , gaze prediction , and abnormal gait detection . His scientific awards include the Sir John William Dawson Medal (2015) , CS-Can|Info-Can Lifetime Achievement Award (2020) , and fellowships in the Royal Society of Canada (2010) , IEEE (2018) , and Canadian Academy of Engineering (2024) . He held the NSERC Tier I Canada Research Chair in Computational Vision (2003–2024) and has been cited for 1000+ research publications . Dr. Tsotsos has advised over 200 trainees (Ph.D., M.Sc., and postdocs) and shaped vision science through founding the Computer Vision Research Group at the University of Toronto (1980) and directing the Centre for Innovation in Computing at York University (2014–2024) . His patents in touch-sensitive displays and face recognition (e.g., US Patent #6,118,433) demonstrate practical applications of his research.