Ali Etemad, PhD, PEng, SMIEEE
Associate Professor, Mitchell Professor in AI for Human Sensing & Understanding, Queen's University, Canada
Ex-visiting Faculty at Google Research & University of Cambridge
Research focus: Artificial intelligence and deep learning, human-centered AI, affective computing, activity analysis, biometrics, health analytics, intelligent human-machine systems
Biography (click here)
Dr. Etemad is an Associate Professor in the Department of Electrical and Computer Engineering at Queen's University. He holds the endowed professorship of Mitchell Professor in AI for Human Sensing & Understanding and leads the Human-Centered AI and Interactive Machines (Aiim) lab. His main area of research is human-centered machine learning and deep learning. Dr. Etemad received his M.A.Sc. and Ph.D. degrees in Electrical and Computer Engineering from Carleton University, Ottawa, Canada, in 2009 and 2014, respectively. Prior to joining Queen’s, he held several industry positions as a lead scientist. He has published over 190 papers in top conferences (e.g., NeurIPS, ICLR, AAAI, CVPR, ECCV, ICCV, ICASSP, CHI, etc.) and journals (e.g., TMLR, T-PAMI, T-AFFC, T-IP, T-IFS, T-ITS, IoT J., JBHI, T-NSRE, T-ASLP, etc.), is a co-inventor of 10 patents, and has given over 30 invited talks. Dr. Etemad is an Associate Editor for IEEE Transactions on Affective Computing and IEEE Transactions on Artificial Intelligence. He has served as a PC member, Area Chair, and Organizing Committee member for various conferences and workshops. He has received a number of awards, including the Queen's Prize for Excellence in Research, the Queen's Supervisor of the Year Award, the Queen's Instructor of the Year Award, and several Best Paper Awards (e.g., at ACM ICMI'23). Dr. Etemad’s lab and research program have been funded by the Natural Sciences and Engineering Research Council (NSERC) of Canada, Ontario Centres of Excellence (OCE), the Canadian Foundation for Innovation (CFI), Mitacs, and other organizations, as well as the private sector. He has previously held Visiting Faculty positions at the University of Cambridge and Google Research.
Selected recent publications
Segment, Shuffle, and Stitch: A Simple Mechanism for Improving Time-Series Representations, NeurIPS, 2024
Diffusion Models with Deterministic Normalizing Flow Priors, TMLR, 2024
A Bag of Tricks for Few-Shot Class-Incremental Learning, TMLR, 2024
UPose3D: Uncertainty-Aware 3D Human Pose Estimation with Cross-View and Temporal Cues, ECCV, 2024
Consistency-guided Prompt Learning for Vision-Language Models , ICLR, 2024
Region-Disentangled Diffusion Model for High-Fidelity PPG-to-ECG Translation, AAAI, 2024
Scaling Up Semi-supervised Learning with Unconstrained Unlabelled Data, AAAI, 2024
XKD: Cross-modal Knowledge Distillation with Domain Alignment for Video Representation Learning, AAAI, 2024
Uncovering the Hidden Dynamics of Video Self-supervised Learning under Distribution Shifts, NeurIPS (*Spotlight paper*), 2023
Flow-based Spatio-Temporal Structured Prediction of Motion Dynamics, T-PAMI, 2023
Self-Supervised Audio-Visual Representation Learning with Relaxed Cross-Modal Temporal Synchronicity, AAAI, 2023
AVCAffe: A Large Scale Audio-Visual Dataset of Cognitive Load and Affect for Remote Work, AAAI, 2023
ObjectBox: From Centers to Boxes for Anchor-Free Object Detection, ECCV, 2022
Vote from the Center: 6 DOF Pose Estimation in RGB-D Images by Radial Keypoint Voting, ECCV, 2022
Deep Gait Recognition: A Survey, T-PAMI, 2022
PARSE: Pairwise Alignment of Representations in Semi-Supervised EEG Learning for Emotion Recognition, T-AFFC, 2022
Face Trees for Expression Recognition, FG, 2021
Teacher-Student Adversarial Depth Hallucination to Improve Face Recognition, ICCV, 2021
Multi-Perspective LSTM for Joint Visual Representation Learning, CVPR, 2021
CardioGAN: Attentive Generative Adversarial Network with Dual Discriminators for Synthesis of ECG from PPG, AAAI, 2021
View-Invariant Gait Recognition with Attentive Recurrent Learning of Partial Representations, T-BIOM, 2021
CapsField: Light Field-based Face and Expression Recognition in the Wild using Capsule Routing, T-IP, 2021
Self-supervised ECG Representation Learning for Emotion Recognition, T-AFFC, 2020
A Deep Neural Network for Short-Segment Speaker Recognition, Interspeech, 2019
Professional service
Journal Editorship
Associate Editor, IEEE Transactions on Affective Computing, 2023-present
Associate Editor, IEEE Transactions on Artificial Intelligence, 2022-present
Guest Co-Editor, Special Issue on Sensors for Biological Signal Analysis, J. Sensors, 2020-2021
Conference Organization and Chairing
Workshops and Tutorials Co-Chair, IEEE International Conference on Automatic Face and Gesture Recognition (FG), 2025
Blue Sky Track Co-Chair, ACM International Conference on Multimodal Interaction (ICMI), 2024
Member of Organizing Committee, AAAI Workshop on Human-Centered Representation Learning, 2024
General Chair, AAAI Workshop on Representation Learning for Responsible Human-Centric AI, 2023
Chair, Session on Biometrics, Face, Gesture \& Pose, AAAI Conference on Artificial Intelligence (AAAI), 2023
Chair, Session on Faces, International Conference on Pattern Recognition (ICPR), 2022
Chair, Session on Speech and Acoustic Signal Processing II, IEEE International Joint Conference on Neural Networks (IJCNN), 2022
General Chair, AAAI Workshop on Human-Centric Self-Supervised Learning (HC-SSL), 2022
Publicity Co-Chair, European Workshop on Visual Information Processing (EUVIP), 2022
Chair, Session on Physiological Data Modeling, IEEE International Conference of Affective Computing and Intelligent Interaction (ACII), 2021
Co-chair, Session on Speech and Language Analysis, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
Chair of Industry Relations, Canadian Conference on AI + Graphics Interface + Computer and Robot Vision (AI/GI/CRV), 2019
Vice Chair (technical program), IEEE Kingston, Kingston, Canada, 2018-2019
Chair, Session 5, Canadian Conference on AI, 2019
Conference Area Chair/Senior Program Committee/Meta-reviewer
International Conference on Learning Representations (ICLR), 2025
International Conference on Artificial Intelligence and Statistics (AISTATS), 2025
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025
AAAI Conference on Artificial Intelligence (AAAI), 2024
International Conference of Affective Computing and Intelligent Interaction (ACII), 2021, 2022, 2023
ACM International Symposium on Wearable Computing (ISWC), 2023
ACM Symposium on Applied Perception (SAP), 2020
Conference Program/Review Committee
Neural Information Processing Systems (NeurIPS), 2024, 2023, 2022, 2021
International Conference on Machine Learning (ICML) , 2024, 2023, 2022
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024, 2023, 2022
IEEE/CVF International Conference on Computer Vision (ICCV), 2023
AAAI Conference on Artificial Intelligence (AAAI), 2025, 2024, 2023
International Conference on Learning Representations (ICLR), 2024, 2023, 2022
European Conference on Computer Vision (ECCV), 2024, 2022
IEEE International Conference of Affective Computing and Intelligent Interaction (ACII), 2023, 2022, 2021
ACM International Symposium on Wearable Computers (ISWC), 2023, 2021
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022, 2021, 2020
Canadian Conference on Artificial Intelligence (CanAI), 2023, 2022, 2021, 2020, 2019
ACM Symposium on Virtual Reality Software and Technology (VRST), 2021
23rd ACM International Conference on Multimodal Interaction (ICMI), 2021
Interspeech, 2021
IEEE Artificial Intelligence and Virtual Reality (AIVR), 2021, 2020, 2018
ACM Symposium on Applied Perception (SAP), 2020, 2019, 2018, 2017, 2016
IEEE Body Sensor Networks (BSN), 2021, 2019, 2018
IEEE Conference on Systems, Man, and Cybernetics (SMC), 2020, 2019
IEEE International Conf. on Ubiquitous Intelligence and Computing (UIC), 2018
ACM CHI Conference on Human Factors in Computing Systems, 2018
23rd ACM Symposium on Virtual Reality Software and Technology (VRST), 2017
ACM CHI Play, 2017
ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI), 2017
Journal Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Neural Networks and Learning Systems
IEEE/ACM Transactions on Audio, Speech, and Language Processing
IEEE Transactions on Human-Machine Systems
IEEE Transactions on Affective Computing
IEEE Transactions on Artificial Intelligence
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Neural Systems & Rehabilitation Engineering
IEEE Journal of Biomedical and Health Informatics
IEEE-EMBS Journal of Translational Engineering in Health and Medicine
International Journal of Computer Vision
Scientific Reports (Nature)
Scientific Data (Nature)
Pattern Recognition
Computer Vision and Image Understanding
Grant Review
NSERC New Frontiers Research Fund
NSERC CRD
NSERC Discovery
NSERC Idea to Innovation
MITACS Accelerate
MITACS Elevate
CFI JELF
Awards
Prize for Excellence in Research, Queen's University, 2023.
Best Paper Award, ACM International Conference on Multimodal Interaction (ICMI), Title: EEG-based Cognitive Load Classification using Feature Masked Autoencoding and Emotion Transfer Learning, 2023
Best Poster Award, FEAS Research Symposium at Queen's University, Title: Cardiac Insights On-the-Go: Inexpensive Continuous ECG Monitoring from PPG using Diffusion Models, 2023
Second Place Winner, Emotion Physiology and Experience Challenge (EPiC), awarded for our work entitled: Robust End-to-End Emotion Recognition from ECG using Transformers, Organized at the International Conference on Affective Computing and Intelligent Interaction (ACII), 2023
Best Poster Award (honorable mention), FEAS Research Symposium at Queen's University, Title: Affective Computing and Cognitive Load Analysis in Remote Meetings for Enhanced Mental Health, 2022
Best AI Poster Award (first place), Ingenuity Labs SymposiumRobotics and AI, Title: Toward Wearables of the Future: Affordable Acquisition of Continuous ECG with Deep Learning, 2021
Best AI Poster Award (second place), Ingenuity Labs SymposiumRobotics and AI, Title: Human Activity Recognition with Self-Supervised Learning of Wearable Data, 2021
Supervisor of the Year Award, Queen's ECE, 2020
Best Poster Award (second place), International Conference on Predictive Vision, Title: Automatic initialization and tracking of markers in optical motion capture by learning to rank, 2019
Best Full Paper Award (first place), Computer Graphics International (CGI), Title: Auto-labelling of Markers in Optical Motion Capture by Permutation Learning, 2019
Best Instructor Award, Queen's ECE, 2019
Best Paper Award (third place), Canadian Medical and Biological Engineering Conference (CMBES), Title: Improving Wrist Force Estimation with Surface EMG During Isometric Contractions, 2018
Invited talks
Learning Effective Human-Centered Representations: Methods and Applications, University of British Columbia, 2024.
Advancements in Face, Speech, and Video Representation Learning, Ericsson, 2024.
Distribution Shifts in Human-Centered Representation Learning, University of Cambridge, 2024.
Toward Ubiquitous Human-Centered Representation Learning, Nokia Bell Labs, 2024.
Battle of the Brains: Can universities compete with industrial labs in AI research? [debate], Robotics and AI Symposium, Queen’s University, 2023.
AI in Mental Health: help or hindrance [debate], Queen’s Psychiatry Conference, 2023.
Sensitivity Machines: Affect, Cognitive Load, and AI, Google Research, 2023.
Beyond Self-Driving: Toward Understanding Passengers for a Customized User Experience, Volvo, 2022.
Bringing Deep Learning to Wearables for Ubiquitous Human Understanding, Halmstad University, Sweden, 2022.
Toward Ubiquitous Human Understanding with Deep Learning, Google Research, 2022.
Current and Future of AI [panel], Casgrain Lecture, 2021.
Understanding Human Emotions with Deep Learning, Queen’s University Biomedical Engineering Seminar Series, 2021.
Understanding Humans in Smart Environments and Wearables with Deep Learning, Carleton University, 2021.
Affective Computing with Deep Learning, Canada Artificial Intelligence, Machine Learning, Data Science, Engineering & Analytics Digital Forum, 2021.
Toward User-centered Brain-Computer Interfaces, Queen's Neurotech Workshop, 2021.
Understanding Humans with Deep Learning”, Ingenuity Labs Seminar Series, 2020.
The Future of Smart Environments and Interactive Machines”, Queen’s FEAS Research Symposium, 2019.
Machine Learning and Deep Learning for Biomedical and Health Informatics, ChosenMed, Beijing, China, 2019.
Ambient Intelligence: The Future of AI and Human-Centric Computing, AI Alliance, Changsha, China, 2019.
Deep Learning for Human-Machine Interaction, Central South University, Changsha, China, 2019.
Ambient Intelligence in Smart Environments with IoT and Wearables, University of Lisbon, 2019.
Artificial Intelligence and Machine Learning in Industry [panel], Academia to Industry Meeting, Kingston, 2019.
Unpacking AI [panel], Future of Work Summit, Toronto, Canada, 2019.
Towards Intelligent IoT and Wearable Devices, York University EECS Seminar Series, 2019.
Ambient Intelligence: A Paradigm Shift in Wearables and the Internet of Things, IoT613, Ottawa, Canada, 2018.
Ambient Intelligence & Interaction: The Future of Smart Vehicles, Irdeto Canada, Ottawa, Canada, 2017.
Ambient Intelligence: User-centric computing and beyond, Queen’s University, 2017.
Detecting Emotions from Human Motion with Machine Learning, Machine Learning Ottawa, 2016.
Perceptual Machines, TEDxKanata, Semifinals, Ottawa, Canada, 2016.
Unlocking the Power of Wearable Technologies with Data Science: Present, Future, and Challenges”, Carleton University Data Science Distinguished Speaker Seminar Series, 2016.
Perceptually Valid Motion Processing, Carleton University Advanced Biomechatronics and Locomotion Laboratory, 2014
Education
PhD, Carleton University, Canada
MASc, Carleton University, Canada
BSc, Isfahan University of Technology, Iran