Researchers Focused on Fundamental Methods in AI
The researchers in this group focus most of their research on developing fundamental AI methods. They tend to publish regularly in top AI methods conferences such as NeurIPS, ICML, AAAI, IJCAI and journals such as JMLR, MLJ, AIJ, JAIR.
| Member | Department | Research Interests |
|---|---|---|
| Muhammad Abdul-Mageed | iSchool | Natural language processing; deep learning; social media mining |
| Ahmet Alacaoglu | Math | optimization algorithms for machine learning and AI; min-max games; stochastic algorithms |
| Benjamin Bloem-Reddy | Statistics | Bayesian methods; stochastic processes; invariance; symmetry; machine learning; statistical learning theory; network data; structured data |
| Alexandre Bouchard-Côté | Statistics | Inference; Monte Carlo methods; phylogenetics; cancer genomics; Bayesian methods; combinatorial spaces; stochastic processes |
| Trevor Campbell | Statistics | Large-scale data; Bayesian inference; Bayesian nonparametrics; Optimization; Model approximation |
| Giuseppe Carenini | Computer Science | Natural Language Processing; Summarization; Discourse Parsing; Natural Language Generation; Intelligent User Interfaces; Interactive Topic Modeling; Decision Support; Preference Elicitation and Visualization; User Modeling; |
| Jeff Clune | Computer Science |  deep learning, deep reinforcement learning, open-endedness, robotics, neuroevolution, computer vision, AI neuroscience |
| Cristina Conati | Computer Science | Intelligent User Interfaces, Intelligent Virtual Agents, Explainable AI, AI in Education, Affective Computing |
| Michael Friedlander | Computer Science | Optimization |
| Eldad Haber | Earth and Ocean Sciences | Deep networks, PDEs, HPC |
| Nick Harvey | Computer Science | Machine learning theory, optimization |
| Laks Lakshmanan | Computer Science | Social networks and media; recommender systems; data cleaning; data mining |
| Mathias Lécuyer | Computer Science | Differential Privacy; Causality; Reinforcement Learning; Generative Models; Federated Learning; System and Security Applications |
| Kevin Leyton-Brown | Computer Science | Machine Learning; Algorithms; Optimization; Market design; Game theory |
| Xiaoxiao Li | Electrical & Computer Engineering | Federated Learning; Trustworthy AI |
| Renjie Liao | Electrical & Computer Engineering | Deep Learning on Graphs; Deep Generative Models; Probabilistic Graphical Models; Optimization for Deep Learning
|
| Mi Jung Park | Computer Science | Bayesian inference, Differential privacy, Neural network compression, Interpretability |
| Yaniv Plan | Math | Theoretical foundations of deep learning; Compressed sensing |
| Geoff Pleiss | Statistics | Deep learning; probabilistic modeling; Bayesian optimization |
| Elina Robeva | Math | Graphical models; Causality; Linear Structural Equation Models |
| Margo Seltzer | Computer Science | Discrete optimization for interpretable models |
| Mark Schmidt | Computer Science | Machine Learning; Numerical Optimization |
| Vered Shwartz | Computer Science | language processing; commonsense reasoning; commonsense knowledge; semantics; pragmatics; discourse; natural language understanding; natural language generation; machine learning; deep learning; representation learning; neurosymbolic methods |
| Leonid Sigal | Computer Science | Computer Vision, Visual Understanding and Reasoning, Deep Learning, Machine Learning |
| Danica Sutherland | Computer Science | machine learning; distinguishing distributions; generative models; kernel methods; deep learning; representation learning; statistical learning theory |
| Christos Thrampoulidis | Electrical & Computer Engineering | high-dimensional statistics; theory of overparameterized ML; fairness; bandits; optimization |
| Michiel van de Panne | Computer Science | Deep reinforcement learning; motion synthesis; computer animation; robotics and control |
| Frank Wood | Computer Science | Probabilistic programming; artificial intelligence; unsupervised deep learning
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| Kwang Moo Yi | Computer Science | computer vision; 3d geometry; deep sets; spatial attention; structure-from-motion; local features; |
| Ozgur Yilmaz | Math | Compressed sensing and related methods, matrix and tensor completion, automated diagnosis from medical images via deep learning |
Other CAIDA Members
The remainder of CAIDA's membership is extremely diverse, with expertise spanning the full range from mathematical foundations of AI to applications (e.g., to medicine; chip design; graphics; and many more....) to public policy.
| Member | Department | AI-Related Research Interests |
|---|---|---|
| Tor Aamodt | Electrical & Computer Engineering | Hardware accelerators for machine learning |
| Purang Abolmaesumi | Electrical & Computer Engineering | Biomedical engineering, medical image analytics |
| Yusuf Altintas | Mechanical Engineering | Adaptive control |
| Sam Aparicio | Pathology and Laboratory Medicine | |
| Ali Bashashati | Biomedical Engineering, Pathology & Laboratory Medicine | Computational Pathology; Bioinformatics; Medical Image Analysis; Biological Signal Processing; AI Applications in Medicine |
| Curtis Berlinguette | Chemistry | Autonomous laboratory for discovery of clean energy materials |
| Ivan Beschastnikh | Computer Science | Distributed Learning; Federated Learning; Formal Methods for AI/ML; Software Engineering for AI/ML |
| Matthew Brown | Computer Science | Computer Vision, Object Recognition, Scene Understanding, 3D Perception, Energy and Sustainability |
| Yankai Cao | Chemical and Biological Engineering | Large-scale Optimization; Machine Learning; Global Optimization; |
| Hasan Cavusoglu | Sauder | Applied AI Research in Economics, NLP, Deep Learning |
| AJ Chen | Sauder | digital economy; artificial intelligence; sustainability; natural language processing; human computer interaction |
| James Colliander | Math | Learning analytics; image analysis; harmonic analysis; partial differential equations |
| Paul Cubbon | Sauder | Health; bio; agtech; safety |
| Leanne Currie | Nursing | Computerized clinical decision support; data science in healthcare; patient-generated data; patient safety |
| Khanh Dao Duc | Math | Molecular and Cell Biology; Image analysis; cryo-EM; Bioinformatics |
| Jiarui Ding | Computer Science | Latent Variable Model; Probabilistic Deep Learning; Density Estimation; Manifold Learning; Geometric Deep Learning; Computational Biology; Bioinformatics; Single-cell Genomics |
| Guy Dumont | Electrical & Computer Engineering | Physiological monitoring; Healthcare; Video monitoring; Intensive care; Home care; Neonatology; Weld Quality Monitoring; Robotic welding |
| Fatemeh Fard | Computer Science | AI and NLP for Software Engineering and automation tools; Transfer learning to low resource languages; Multi-agent systems for SE |
| Vitor Farinha Luz | Vancouver School of Economics | Mechanism design and contract theory |
| Hu Fu | Computer Science | Algorithms; Market/Mechanism Design; Game Theory; Optimization |
| Qiang Fu | Sociology | Text & Data Mining, Survey Methodology, Demographic Methods, Network and Spatial Analysis |
| Makoto Fujiwara | Particle Physics | Machine Learning in Particle Physics and Antimatter Research |
| Ying Gao | Vancouver School of Economics | Game theory; information economics; data and disclosure |
| Rafeef Garbi | Electrical & Computer Engineering | Computer vision; Image analysis; Medical imaging; Signal computing; Biomedical applications |
| Mike Gelbart | Computer Science | Hyperparameter optimization |
| Bhushan Gopaluni | Chemical and Biological Engineering | Classification (SVM), Regression, Dimensionality Reduction (PCA, PLS, ISOMAP), Learning Algorithms (Deep Learning, Gaussian Processes), Sequential Monte Carlo, Process Data Analytics |
| Chen Greif | Computer Science | Numerical linear algebra, constrained optimization, numerical solution of partial differential equations |
| Jason Hein | Chemistry | Self-Driving Chemical Laboratories; Laboratory Robotics; Autonomous Chemical Discovery |
| Alan Hu | Computer Science | |
| Hiroyuki Kasahara | Vancouver School of Economics | causal inference |
| Ed Knorr | Computer Science | Privacy; Ethics; Algorithmic Bias |
| Guy Lemieux | Electrical & Computer Engineering | Field-Programmable Gate Arrays |
| Hao Li | Vancouver School of Economics | mechanism design |
| Dominic Liao-McPherson | Mechanical Engineering | Control Theory; Optimization; Active Learning; Uncertainty Quantification |
| Philip Loewen | Math | Reinforcement Learning for Control |
| Karon MacLean | Computer Science | Gesture recognition; activity identification; dynamic emotion modeling |
| Vadim Marmer | Vancouver School of Economics | Econometrics, Statistics |
| Jose Marti | Electrical & Computer Engineering | Decision making in large complex systems; resilience of power system networks, disaster response; modelling of economic systems |
| Joanna McGrenere | Computer Science | Adaptive user interfaces |
| Bill Miller | Occupational Science & Occupational Therapy | Mobility; wheelchair; health informatics; clinical application; evaluation; |
| Sanja Miskovic | Mining Engineering | |
| Ilija Miskovic | Mining Engineering | AI-Assisted Geoscience and Resource Modeling; Digital Twins for Mining and O&G; Intelligent Embedded Systems; Autonomous Resource Extraction Processes and Machinery. |
| Ian Mitchell | Computer Science | Sharing control between humans and automation; robots and cyber-physical systems; assistive technology for mobility; verification of safety and correctness; numerical computing; differential equations |
| Ahmad Mohammadpanah | Mechanical Engineering | AI in Manufacturing; Applications of AI in Metal 3D Printing; Machine Learning Applications in Metal Machining |
| Christopher Mole | Philosophy | philosophy; attention |
| Gene Moo Lee | Sauder | Industry intelligence; social media; cybersecurity; mobile ecosystem |
| Tamara Munzner | Computer Science | integrating machine learning and visual analytics |
| Gail Murphy | Computer Science | Recommender systems and ML for software engineering and knowledge worker productivity |
| Ning Nan | Sauder | Agent-based models, computer simulations, AI-human interaction |
| Apurva Narayan | Computer Science | Deep Learning; Software Engineering; Safety and Security in Cyber Physical Systems; Data Mining |
| Laura Nelson | Sociology | applied AI; computational sociology; computational social science; natural language processing; machine learning; machine vision; digital humanities |
| Raymond Ng | Computer Science | Natural Language Processing |
| Shunya Noda | Vancouver School of Economics | Market Design; Mechanism Design; Blockchain |
| Shin Oblander | Sauder | Causal inference; representation learning; probabilistic modelling; Bayesian models; bounded rationality |
| Dinesh Pai | Computer Science | Machine learning for digital humans, graphics, and simulation; Sensorimotor neuroscience; Robotics |
| Karthik Pattabiraman | Electrical & Computer Engineering | Dependability, Security, Safety |
| Jesse Perla | Vancouver School of Economics | Differentiable Programming in Economics; Scientific Machine Learning; Bounded Rationality |
| Benjamin Perrin | Peter A. Allard School of Law | AI & criminal justice; AI governance; AI in policing |
| Michael Peters | Vancouver School of Economics | mechanism design; matching |
| Rachel Pottinger | Computer Science | data management; intelligent data interaction; data understanding and exploration |
| Peter Reiner | Psychiatry | Neuroethics; extended mind; agency; autonomy; enhancement |
| Julie Robillard | Medicine | Assistive technology; Alzheimer disease; dementia, affective computing; emotion; identity; patient experience of AI technology |
| Rob Rohling | Electrical & Computer Engineering | Medical imaging; ultrasound |
| Charlene Ronquillo | Nursing | artificial intelligence; nursing; bias; equity; natural language processing; decision support |
| Andrew Roth | BC Cancer Research Centre | Computational biology; Bayesian models |
| Julia Rubin | Electrical & Computer Engineering | Testing of ML algorithms; fairness in ML; software engineering for ML |
| Tim Salcudean | Electrical & Computer Engineering | Medical imaging with a focus on the classification of tissue on digitized histopathology slides, registration of multi-modality images for image guided medical interventions, and correlation of images with pathology slides; Demonstration-acquired skills and autonomy in robotics. |
| Geoffrey Schiebinger | Mathematics | optimal transport; biology; trajectory inference |
| Paul Schrimpf | Vancouver School of Economics | econometrics; insurance; semiparametric inference |
| Sohrab Shah | Molecular Oncology | |
| Azim Shariff | Psychology | AI ethics; Psychology of Technology; AI and society |
| Alla Sheffer | Computer Science | Computer Graphics; Shape Analysis;Shape Modeling |
| Sudip Shekhar | Electrical & Computer Engineering | Machine learning Processor Design, ASIC, Edge Computing, Low Power |
| Bruce Shepherd | Computer Science | Optimization; networks |
| Kevin Song | Vancouver School of Economics | statistical decision theory; econometric models of game theory; causal inference |
| Adi Steif | Medical Genetics | Computational biology; Cancer genomics |
| Aline Talhouk | Obstetrics & Gynaecology | classification; decision-making; privacy |
| Roger Tam | Radiology | Medical imaging; MRI; clinical prognostication; precision medicine; classification; segmentation |
| Teresa Tsang | Medicine - Cardiology | AI in heart disease; echo imaging; 3D echo; 2D echo; strain; Doppler echo; atrial fibrillation; heart failure; stroke; diastolic function |
| Mike Van der Loos | Mechanical Engineering | Human-robot interaction in social, therapy and industrial collaborative robotics; machine vision for robot SLAM; machine learning for human-movement characterization during sleep and physical therapy |
| Carlos Ventura | Civil Engineering | Structural Health Monitoring of Infrastructure, Structural Damage Detection and Condition Assessment |
| Rajesh Vijayaraghavan | Sauder | Accounting and risk management in banks and insurance companies; Machine learning; Corporate Finance; Corporate governance and performance measurement |
| Jane Wang | Electrical & Computer Engineering | AI medical; deep learning for media security; image/ video analytics |
| Lele Wang | Electrical & Computer Engineering | information processing on graphical data |
| Vincent Wong | Electrical & Computer Engineering | wireless communications; mobile networking; Internet of Things; energy systems |
| Carson Woo | Sauder | Applications of intelligent agent concepts (e.g., learning and reasoning) in requirements engineering and business analysis |
| Julia Yan | Sauder | transportation; optimization |
| Dongwook Yoon | Computer Science | AI applications to human-computer interaction; multimodal user interfaces; speech and gesture user interfaces; video user interfaces; computer-supported cooperative work. |
| Peter Zandstra | Biomedical Engineering | |
| Andrew Zheng | Sauder | Bandits; Reinforcement Learning |
Emeritus Members
| Member | Department | AI-Related Research Interests |
|---|---|---|
| Uri Ascher | Computer Science | scientific computing, optimization, computer animation simulation, continuous limits to discrete processes, learning methods for applied inverse problems |
| Holger Hoos | Computer Science | Automated algorithm design, local search, optimization |
| Maryam Kamgarpour | Electrical & Computer Engineering | game theory; learning Nash equilibria; online and bandit optimization; safe learning; safe control synthesis; mixed integer optimization; stochastic optimization; distributed decision making; multi-agent control; rescue/distaster-response robotics, transportation systems, power grid systems |
| Jim Little | Computer Science | Computer vision; mobile robotics |
| Alan Mackworth | Computer Science | Constraint-based artificial intelligence; hybrid systems; constraint-based agents; assistive technology; sustainability |
| Sara Mostafavi | Statistics | Computational Biology; Genomics |
| David Poole | Computer Science | Statistical relational AI; reasoning under uncertainty; machine learning; relational learning; knowledge representation; ontologies; preferences; probabilistic inference; probabilistic programming; actions; semantic science; AI education |
| Martin Puterman | Sauder | Markov decision processes:theory and applications; approximate dynamic programming; stochastic scheduling |
| Siamak Ravanbakhsh | Computer Science | Deep learning, equivariance |
| Helge Rhodin | Computer Science | representation learning; self-supervision; computer graphics; computer vision; virtual and augmented reality; human motion capture; autonomous driving; neuroscience |
| Taylor Owen | Journalism | |
| Andrew Warfield | Computer Science |