Faculty Members of CAIDA

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.

MemberDepartmentResearch Interests
Muhammad Abdul-MageediSchoolNatural language processing; deep learning; social media mining
Ahmet AlacaogluMathoptimization algorithms for machine learning and AI; min-max games; stochastic algorithms
Benjamin Bloem-ReddyStatisticsBayesian methods; stochastic processes; invariance; symmetry; machine learning; statistical learning theory; network data; structured data
Alexandre Bouchard-CôtéStatisticsInference; Monte Carlo methods; phylogenetics; cancer genomics; Bayesian methods; combinatorial spaces; stochastic processes
Trevor CampbellStatisticsLarge-scale data; Bayesian inference; Bayesian nonparametrics; Optimization; Model approximation
Giuseppe CareniniComputer ScienceNatural Language Processing; Summarization; Discourse Parsing; Natural Language Generation; Intelligent User Interfaces; Interactive Topic Modeling; Decision Support; Preference Elicitation and Visualization; User Modeling;
Jeff CluneComputer ScienceCIFAR logo

   deep learning, deep reinforcement learning, open-endedness, robotics, neuroevolution, computer vision, AI neuroscience

Cristina ConatiComputer ScienceIntelligent User Interfaces, Intelligent Virtual Agents, Explainable AI, AI in Education, Affective Computing
Michael FriedlanderComputer ScienceOptimization
Eldad HaberEarth and Ocean SciencesDeep networks, PDEs, HPC
Nick HarveyComputer ScienceMachine learning theory, optimization
Laks LakshmananComputer ScienceSocial networks and media; recommender systems; data cleaning; data mining
Mathias LécuyerComputer ScienceDifferential Privacy; Causality; Reinforcement Learning; Generative Models; Federated Learning; System and Security Applications
Kevin Leyton-BrownComputer ScienceCIFAR logo

   Machine Learning; Algorithms; Optimization; Market design; Game theory

Xiaoxiao LiElectrical & Computer EngineeringCIFAR logo

Federated Learning; Trustworthy AI

Renjie LiaoElectrical & Computer EngineeringCIFAR logo

Deep Learning on Graphs; Deep Generative Models; Probabilistic Graphical Models; Optimization for Deep Learning

 

Mi Jung ParkComputer ScienceCIFAR logo

   Bayesian inference, Differential privacy, Neural network compression, Interpretability

Yaniv PlanMathTheoretical foundations of deep learning; Compressed sensing
Geoff PleissStatisticsCIFAR logo

Deep learning; probabilistic modeling; Bayesian optimization

Elina RobevaMathCIFAR logo

Graphical models; Causality; Linear Structural Equation Models

Margo SeltzerComputer ScienceDiscrete optimization for interpretable models
Mark SchmidtComputer ScienceCIFAR logo

   Machine Learning; Numerical Optimization

Vered ShwartzComputer ScienceCIFAR logo

   language processing; commonsense reasoning; commonsense knowledge; semantics; pragmatics; discourse; natural language understanding; natural language generation; machine learning; deep learning; representation learning; neurosymbolic methods

Leonid SigalComputer ScienceCIFAR logo

   Computer Vision, Visual Understanding and Reasoning, Deep Learning, Machine Learning

Danica SutherlandComputer ScienceCIFAR logo

   machine learning; distinguishing distributions; generative models; kernel methods; deep learning; representation learning; statistical learning theory

Christos ThrampoulidisElectrical & Computer Engineeringhigh-dimensional statistics; theory of overparameterized ML; fairness; bandits; optimization
Michiel van de PanneComputer ScienceDeep reinforcement learning; motion synthesis; computer animation; robotics and control
Frank WoodComputer ScienceCIFAR logo

   Probabilistic programming; artificial intelligence; unsupervised deep learning

 

Kwang Moo YiComputer Sciencecomputer vision; 3d geometry; deep sets; spatial attention; structure-from-motion; local features;
Ozgur YilmazMathCompressed 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.

MemberDepartmentAI-Related Research Interests
Tor AamodtElectrical & Computer EngineeringHardware accelerators for machine learning
Purang AbolmaesumiElectrical & Computer EngineeringBiomedical engineering, medical image analytics
Yusuf AltintasMechanical EngineeringAdaptive control
Sam AparicioPathology and Laboratory Medicine 
Ali BashashatiBiomedical Engineering, Pathology & Laboratory MedicineComputational Pathology; Bioinformatics; Medical Image Analysis; Biological Signal Processing; AI Applications in Medicine
Curtis BerlinguetteChemistryAutonomous laboratory for discovery of clean energy materials
Ivan BeschastnikhComputer ScienceDistributed Learning; Federated Learning; Formal Methods for AI/ML; Software Engineering for AI/ML
Matthew BrownComputer ScienceComputer Vision, Object Recognition, Scene Understanding, 3D Perception, Energy and Sustainability
Yankai CaoChemical and Biological EngineeringLarge-scale Optimization; Machine Learning; Global Optimization;
Hasan CavusogluSauderApplied AI Research in Economics, NLP, Deep Learning
AJ ChenSauderdigital economy; artificial intelligence; sustainability; natural language processing; human computer interaction
James CollianderMathLearning analytics; image analysis; harmonic analysis; partial differential equations
Paul CubbonSauderHealth; bio; agtech; safety
Leanne CurrieNursingComputerized clinical decision support; data science in healthcare; patient-generated data; patient safety
Khanh Dao DucMathMolecular and Cell Biology; Image analysis; cryo-EM; Bioinformatics
Jiarui DingComputer ScienceLatent Variable Model; Probabilistic Deep Learning; Density Estimation; Manifold Learning; Geometric Deep Learning; Computational Biology; Bioinformatics; Single-cell Genomics
Guy DumontElectrical & Computer EngineeringPhysiological monitoring; Healthcare; Video monitoring; Intensive care; Home care; Neonatology; Weld Quality Monitoring; Robotic welding
Fatemeh FardComputer ScienceAI and NLP for Software Engineering and automation tools; Transfer learning to low resource languages; Multi-agent systems for SE
Vitor Farinha LuzVancouver School of EconomicsMechanism design and contract theory
Hu FuComputer ScienceAlgorithms; Market/Mechanism Design; Game Theory; Optimization
Qiang FuSociologyText & Data Mining, Survey Methodology, Demographic Methods, Network and Spatial Analysis
Makoto FujiwaraParticle PhysicsMachine Learning in Particle Physics and Antimatter Research
Ying GaoVancouver School of EconomicsGame theory; information economics; data and disclosure
Rafeef GarbiElectrical & Computer EngineeringComputer vision; Image analysis; Medical imaging; Signal computing; Biomedical applications
Mike GelbartComputer ScienceHyperparameter optimization
Bhushan GopaluniChemical and Biological EngineeringClassification (SVM), Regression, Dimensionality Reduction (PCA, PLS, ISOMAP), Learning Algorithms (Deep Learning, Gaussian Processes), Sequential Monte Carlo, Process Data Analytics
Chen GreifComputer ScienceNumerical linear algebra, constrained optimization, numerical solution of partial differential equations
Jason HeinChemistrySelf-Driving Chemical Laboratories; Laboratory Robotics; Autonomous Chemical Discovery
Alan HuComputer Science 
Hiroyuki KasaharaVancouver School of Economicscausal inference
Ed KnorrComputer SciencePrivacy; Ethics; Algorithmic Bias
Guy LemieuxElectrical & Computer EngineeringField-Programmable Gate Arrays
Hao LiVancouver School of Economicsmechanism design
Dominic Liao-McPhersonMechanical EngineeringControl Theory; Optimization; Active Learning; Uncertainty Quantification
Chao LiuMechanical EngineeringRobotics; Motion Planning and Control; Multimodal Perception; Robot Learning
Philip LoewenMathReinforcement Learning for Control
Karon MacLeanComputer ScienceGesture recognition; activity identification; dynamic emotion modeling
Vadim MarmerVancouver School of EconomicsEconometrics, Statistics
Jose MartiElectrical & Computer EngineeringDecision making in large complex systems; resilience of power system networks, disaster response; modelling of economic systems
Joanna McGrenereComputer ScienceAdaptive user interfaces
Bill MillerOccupational Science & Occupational TherapyMobility; wheelchair; health informatics; clinical application; evaluation;
Sanja MiskovicMining Engineering 
Ilija MiskovicMining EngineeringAI-Assisted Geoscience and Resource Modeling; Digital Twins for Mining and O&G; Intelligent Embedded Systems; Autonomous Resource Extraction Processes and Machinery.
Ian MitchellComputer ScienceSharing control between humans and automation; robots and cyber-physical systems; assistive technology for mobility; verification of safety and correctness; numerical computing; differential equations
Ahmad MohammadpanahMechanical EngineeringAI in Manufacturing; Applications of AI in Metal 3D Printing; Machine Learning Applications in Metal Machining
Christopher MolePhilosophyphilosophy; attention
Gene Moo LeeSauderIndustry intelligence; social media; cybersecurity; mobile ecosystem
Tamara MunznerComputer Scienceintegrating machine learning and visual analytics
Gail MurphyComputer ScienceRecommender systems and ML for software engineering and knowledge worker productivity
Ning NanSauderAgent-based models, computer simulations, AI-human interaction
Apurva NarayanComputer ScienceDeep Learning; Software Engineering; Safety and Security in Cyber Physical Systems; Data Mining
Laura NelsonSociologyapplied AI; computational sociology; computational social science; natural language processing; machine learning; machine vision; digital humanities
Raymond NgComputer ScienceNatural Language Processing
Shunya NodaVancouver School of EconomicsMarket Design; Mechanism Design; Blockchain
Shin OblanderSauderCausal inference; representation learning; probabilistic modelling; Bayesian models; bounded rationality
Dinesh PaiComputer ScienceMachine learning for digital humans, graphics, and simulation; Sensorimotor neuroscience; Robotics
Karthik PattabiramanElectrical & Computer EngineeringDependability, Security, Safety
Jesse PerlaVancouver School of EconomicsDifferentiable Programming in Economics; Scientific Machine Learning; Bounded Rationality
Benjamin PerrinPeter A. Allard School of LawAI & criminal justice; AI governance; AI in policing
Michael PetersVancouver School of Economicsmechanism design; matching
Rachel PottingerComputer Sciencedata management; intelligent data interaction; data understanding and exploration
Peter ReinerPsychiatryNeuroethics; extended mind; agency; autonomy; enhancement
Julie RobillardMedicineAssistive technology; Alzheimer disease; dementia, affective computing; emotion; identity; patient experience of AI technology
Rob RohlingElectrical & Computer EngineeringMedical imaging; ultrasound
Charlene RonquilloNursingartificial intelligence; nursing; bias; equity; natural language processing; decision support
Andrew RothBC Cancer Research CentreComputational biology; Bayesian models
Julia RubinElectrical & Computer EngineeringTesting of ML algorithms; fairness in ML; software engineering for ML
Tim SalcudeanElectrical & Computer EngineeringMedical 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 SchiebingerMathematicsoptimal transport; biology; trajectory inference
Paul SchrimpfVancouver School of Economicseconometrics; insurance; semiparametric inference
Sohrab ShahMolecular Oncology 
Azim ShariffPsychologyAI ethics; Psychology of Technology; AI and society
Alla ShefferComputer ScienceComputer Graphics; Shape Analysis;Shape Modeling
Sudip ShekharElectrical & Computer EngineeringMachine learning Processor Design, ASIC, Edge Computing, Low Power
Bruce ShepherdComputer ScienceOptimization; networks
Kevin SongVancouver School of Economicsstatistical decision theory; econometric models of game theory; causal inference
Adi SteifMedical GeneticsComputational biology; Cancer genomics
Aline TalhoukObstetrics & Gynaecologyclassification; decision-making; privacy
Roger TamRadiologyMedical imaging; MRI; clinical prognostication; precision medicine; classification; segmentation
Teresa TsangMedicine - Cardiology AI in heart disease; echo imaging; 3D echo; 2D echo; strain; Doppler echo; atrial fibrillation; heart failure; stroke; diastolic function
Mike Van der LoosMechanical EngineeringHuman-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 VenturaCivil EngineeringStructural Health Monitoring of Infrastructure, Structural Damage Detection and Condition Assessment
Rajesh VijayaraghavanSauderAccounting and risk management in banks and insurance companies; Machine learning; Corporate Finance; Corporate governance and performance measurement
Jane WangElectrical & Computer EngineeringAI medical; deep learning for media security; image/ video analytics
Lele WangElectrical & Computer Engineeringinformation processing on graphical data
Vincent WongElectrical & Computer Engineeringwireless communications; mobile networking; Internet of Things; energy systems
Carson WooSauderApplications of intelligent agent concepts (e.g., learning and reasoning) in requirements engineering and business analysis
Julia YanSaudertransportation; optimization
Dongwook YoonComputer ScienceAI applications to human-computer interaction; multimodal user interfaces; speech and gesture user interfaces; video user interfaces; computer-supported cooperative work.
Peter ZandstraBiomedical Engineering 
Andrew ZhengSauderBandits; Reinforcement Learning

Emeritus Members

MemberDepartmentAI-Related Research Interests
Uri AscherComputer Sciencescientific computing, optimization, computer animation simulation, continuous limits to discrete processes, learning methods for applied inverse problems
Holger HoosComputer ScienceAutomated algorithm design, local search, optimization
Maryam KamgarpourElectrical & Computer Engineeringgame 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 LittleComputer ScienceComputer vision; mobile robotics
Alan MackworthComputer ScienceConstraint-based artificial intelligence; hybrid systems; constraint-based agents; assistive technology; sustainability
Sara MostafaviStatisticsComputational Biology; Genomics
David PooleComputer ScienceStatistical relational AI; reasoning under uncertainty; machine learning; relational learning; knowledge representation; ontologies; preferences; probabilistic inference; probabilistic programming; actions; semantic science; AI education
Martin PutermanSauderMarkov decision processes:theory and applications; approximate dynamic programming; stochastic scheduling
Siamak RavanbakhshComputer ScienceDeep learning, equivariance
Helge RhodinComputer Sciencerepresentation learning; self-supervision; computer graphics; computer vision; virtual and augmented reality; human motion capture; autonomous driving; neuroscience
Taylor OwenJournalism 
Andrew WarfieldComputer Science 

259
K, Citations


49
$M, Research Income