Machine learning

This subclass comprises research and experimental development in machine learning.

Parent Category

A

Aamodt, Tor

Department of Electrical & Computer Engineering, Faculty of Applied Science

Faculty (G+PS eligible/member)

Computer architecture; Machine learning; Computer Architecture; graphics processor units (GPUs); Machine Learning

Alacaoglu, Ahmet

Department of Mathematics, Faculty of Science

Faculty (G+PS eligible/member)

Mathematical optimization; Machine learning; Mathematical operations research; Numerical optimization; Machine Learning; Stochastic algorithms; Min-max games; Monotone operator theory

H

Heagy, Lindsey

Department of Earth, Ocean & Atmospheric Sciences, Faculty of Science

Faculty (G+PS eligible/member)

Geoelectrics and geoelectromagnetics; Magnetism and paleomagnetism; Gravimetry; Environmental monitoring; Numerical computation; Machine learning; Geophysics; Inverse theory; data science; Machine Learning; Electromagnetics; Carbon sequestration; Groundwater; Environmental geophysics; Resource exploration

M

Mallik, Wrik

Faculty of Applied Science

Postdoctoral Fellow

Fluid-structure interaction; Acoustics and noise control (except architectural acoustics); Machine learning; Reduced-order modelling; Machine Learning; Underwater wave propagation; Multidisciplinary design optimization

McDonald, Daniel

Department of Statistics, Faculty of Science

Faculty (G+PS eligible/member)

High dimensional data analysis; Computational methods in statistics; Statistical theory and modeling; Machine learning; Epidemiology (except nutritional and veterinary epidemiology); Methods and models for epidemiological forecasting; Estimation and quantification of prediction risk; Evaluating the predictive abilities of complex dependent data; Application of statistical learning techniques to time series prediction problems; Investigations of cross-validation and the bootstrap for risk estimation

P

Pleiss, Geoffrey

Department of Statistics, Faculty of Science

Faculty (G+PS eligible/member)

Statistical theory and modeling; Machine learning; Computational methods in statistics; Spatial statistics; Numerical analysis; Machine Learning; neural networks; Gaussian processes; Bayesian optimization; reliable deep learning

R

Robeva, Elina

Department of Mathematics, Faculty of Science

Faculty (G+PS eligible/member)

Statistical theory and modeling; Machine learning; Algebra; Algebraic statistics; Graphical Models; Tensor decomposition; Causality; Applied algebraic geometry; Shape-constrained density estimation; Tensor networks

S

Shelhamer, Evan

Department of Computer Science, Faculty of Science

Faculty (G+PS eligible/member)

Machine learning; Computer vision in artificial intelligence; Artificial intelligence (AI); Machine Learning; Computer Vision / Visual Recognition; Robustness and Adaptation; Self-Supervised / Unsupervised Learning; Applications to Remote Sensing and Sustainability

T

Tam, Roger

School of Biomedical Engineering, Faculty of Medicine

Faculty (G+PS eligible/member)

Machine learning; Biomedical signal processing; Biomedical Design and Innovation; Biomedical Technologies; Computer Science and Statistics; Data Analytics; Medical Imaging; Machine Learning; Neurodegenerative diseases; Precision Medicine; Radiology

Traboulsee, Tony

Division of Neurology, Faculty of Medicine

Faculty (G+PS eligible/member)

Neurology; Central nervous system; Biomedical signal processing; Machine learning; magnetic resonance imaging; multiple sclerosis; Neuromyelitls optica spectrum disorder (NMOSD); Myelin Oligodendrocyte Antibody Disorder (MOGAD); Brain MRI; Spinal Cord MRI

Picture of Shea, Betty

Betty Shea

Student

Doctor of Philosophy in Computer Science (PhD)

Optimization methods
Picture of Xi, Quanhan

Quanhan Xi

Student

Doctor of Philosophy in Statistics (PhD)

Representing latent interventions in generative models
Picture of Zandsalimy, Mohammad

Mohammad Zandsalimy

Student

Doctor of Philosophy in Mechanical Engineering (PhD)

Stability analysis and improvement of finite volume methods
Faeze Keshavarz's image

Faeze Keshavarz

Student

Doctor of Philosophy in Bioinformatics (PhD)

Understanding cellular pathways modifications in cancer using the transcriptome
Picture of Ebrahimi Kahou, Mahdi

Mahdi Ebrahimi Kahou

Student

Doctor of Philosophy in Economics (PhD)

Can machine learning enhance economic models with heterogeneity?
Picture of Richardson, Nicholas

Nicholas Richardson

Student

Doctor of Philosophy in Mathematics (PhD)

Signal decomposition and source separation
Picture of Lee, Eric

Eric Lee

Student

Doctor of Philosophy in Bioinformatics (PhD)

Computational approaches for exploring the spatial dynamics of the cellular ecosystem
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Brandon McNabb

Student

Doctor of Philosophy in Oceanography (PhD)

Characterizing the distributions and mechanisms driving oceanic methylated sulfur cycling
Picture of Adebara, Ife

Ife Adebara

Student

Doctor of Philosophy in Linguistics (PhD)

Inclusive by Design: Natural Language Technology for Africa
Picture of Adibi, Amin

Amin Adibi

Student

Doctor of Philosophy in Pharmaceutical Sciences (PhD)

Taking a Deep Breath: Insightful Discourses on Race and Spirometry Through Patient Engagement

Academic Units

French Name

Apprentissage machine

French Description

Cette sous-classe comprend la recherche et le développement expérimental en apprentissage machine.