Stay updated with the latest news, achievements, announcements, and upcoming events from BAM Lab.
Aman Anand and Amir Eskandari were selected to attend the 2026 AI in Finance Summer School, organized by RBC Borealis at the University of British Columbia (UBC) in Vancouver, and both received financial support from RBC Borealis to participate. During the summer school, each presented a poster based on their published Transactions on Machine Learning Research (TMLR) paper: Aman presented 'ASMa: Asymmetric Spatio-temporal Masking for Skeleton Action Representation Learning,' while Amir presented 'InfGraND: An Influence-Guided GNN-to-MLP Knowledge Distillation.' Amir also took part in the program's challenge and won it. Congratulations to both Aman and Amir!
Our paper 'ElderBench: Benchmarking Personalized Open-Source LLMs for Older Adults,' was presented at the IEEE Annual Computers, Software, and Applications Conference (COMPSAC) 2026, as part of the Symposium on Cognitive Robotic Systems. The work introduces a benchmark for evaluating how well personalized, open-source large language models can understand and support the needs of older adults, contributing to the lab's broader research on AI-driven tools for healthy aging.
Our paper 'ASMa: Asymmetric Spatio-temporal Masking for Skeleton Action Representation Learning' by Aman Anand, Amir Eskandari, Elyas Rashno, and Dr. Farhana Zulkernine has been accepted at Transactions on Machine Learning Research (TMLR).
9:00 AM - 5:00 PM
Queen's University Conference Centre
Multiple Speakers
1:00 PM - 6:00 PM
Innovation Park
BAM Lab & Industry Partners
Aman Anand and Amir Eskandari were selected to attend the 2026 AI in Finance Summer School, organized by RBC Borealis at the University of British Columbia (UBC) in Vancouver, and both received financial support from RBC Borealis to participate. During the summer school, each presented a poster based on their published Transactions on Machine Learning Research (TMLR) paper: Aman presented 'ASMa: Asymmetric Spatio-temporal Masking for Skeleton Action Representation Learning,' while Amir presented 'InfGraND: An Influence-Guided GNN-to-MLP Knowledge Distillation.' Amir also took part in the program's challenge and won it. Congratulations to both Aman and Amir!
Our paper 'ElderBench: Benchmarking Personalized Open-Source LLMs for Older Adults,' was presented at the IEEE Annual Computers, Software, and Applications Conference (COMPSAC) 2026, as part of the Symposium on Cognitive Robotic Systems. The work introduces a benchmark for evaluating how well personalized, open-source large language models can understand and support the needs of older adults, contributing to the lab's broader research on AI-driven tools for healthy aging.
Our paper 'ASMa: Asymmetric Spatio-temporal Masking for Skeleton Action Representation Learning' by Aman Anand, Amir Eskandari, Elyas Rashno, and Dr. Farhana Zulkernine has been accepted at Transactions on Machine Learning Research (TMLR).
Our paper 'SK-DGCNN: Human activity recognition from point cloud data with skeleton transformation' by Zihan Zhang, Aman Anand, and Dr. Farhana Zulkernine has been accepted at Elsevier's Machine Learning with Applications journal.
Nafiz Sadman (Ph.D. student), co-authored with Dr. Furkan Alaca and Dr. Farhana Zulkernine, published his Master's thesis titled 'DepthPulse+: A Depth and Vital Sign Based Method for Face Presentation Attack Detection' at IEEE International Conference on Communications (Track: Communications and Information Systems Security). Congratulations!
Co-creating Intelligent Neuro-Technologies for Healthy Aging (CINTHeA). Source: CFREF Connected Mind Team Grant
Our paper 'InfGraND: An Influence-Guided GNN-to-MLP Knowledge Distillation' has been accepted at Transactions on Machine Learning Research (TMLR).
Dr. Zulkernine awarded NSERC Discovery Grant for 'Advancing Machine Perception for Situation-Aware Goal-Oriented Human Machine Interaction'. Source: NSERC Discovery
Our paper 'A Multiagent Summarization and Auto-Evaluation Framework for Medical Text: Development and Evaluation Study' has been accepted to the Journal of Medical Internet Research (JMIR).
When People Talk, Listen Completely. Source: CFREF Connected Mind Team Grant
Developing an AI-Based Tool for Optimizing Disability Accessibility of Pedestrian Networks in Marginalized Neighborhoods. Source: CFREF Connected Mind Seed Grant
Leveraging machine learning for competency-based medical education: A tool for facilitating decision making in resident progress and promotion assessments. Source: Queen's Annual Multidisciplinary DOR Health Sciences RG
Companion: A Cognitive Voice and Video Assistant Bot for Safe Aging. Source: NFRF Exploration