Position: Beyond Assistance—Reimagining LLMs as Ethical and Adaptive Co-Creators in Mental Health Care | ICML 2025
𝐀𝐮𝐭𝐡𝐨𝐫𝐬: 𝐀𝐛𝐞𝐞𝐫 𝐁𝐚𝐝𝐚𝐰𝐢, 𝐌𝐝 𝐓𝐚𝐡𝐦𝐢𝐝 𝐑𝐚𝐡𝐦𝐚𝐧 𝐋𝐚𝐬𝐤𝐚𝐫, 𝐉𝐢𝐦𝐦𝐲 𝐗𝐢𝐚𝐧𝐠𝐣𝐢 𝐇𝐮𝐚𝐧𝐠, 𝐒𝐡𝐚𝐢𝐧𝐚 𝐑𝐚𝐳𝐚, 𝐄𝐥𝐡𝐚𝐦 𝐃𝐨𝐥𝐚𝐭𝐚𝐛𝐚𝐝𝐢.
Professional Summary
Dr. Abeer Badawi is a Postdoctoral Researcher at York University and a Faculty Affiliate Researcher at the Vector Institute, with over 10 years of experience at the intersection of AI and healthcare. Her work bridges AI, LLM, health and mental health, digital biomarkers, and responsible AI, with a focus on fairness, evaluation, and real-world clinical impact. She has led and co-led projects on agitation prediction in dementia, digital biomarkers, and large-scale mental-health LLM evaluation, working with partners such as Kids Help Phone (KHP), University Health Network (UHN), CAMH (The Centre for Addiction and Mental Health), Ontario Shores Centre for Mental Health Sciences, and the Vector Institute.
Her research is supported by competitive awards, including the Connected Minds CFREF Postdoctoral Scholarship, Ontario Graduate Scholarship (OGS), and multiple institutional, national, and industry-funded research programs. Dr. Badawi earned her PhD in Computer Engineering and has authored publications in venues such as ICML, EMNLP, IEEE, and JMIR, alongside teaching over 15 engineering and AI courses across three universities. Dr. Badawi also worked in industry as a Machine Learning Researcher at York University, a Machine Learning Specialist at the Vector Institute, and Data Scientist at BetterCart Technologies Inc.
Interests
Machine Learning
Large Language Models
Healthcare and Mental Health
LLM Evaluation & Benchmarking
Responsible AI
Interpretability
Safety and Alignment
Large Language Model Psychometrics
Digital Biomarkers & Multimodal Sensing
Biomedical Signal Processing
Research Publications
When Can We Trust LLMs in Mental Health? Large-scale Benchmarks for Reliable LLM Evaluation
𝐀𝐮𝐭𝐡𝐨𝐫𝐬: 𝐀𝐛𝐞𝐞𝐫 𝐁𝐚𝐝𝐚𝐰𝐢, 𝐄𝐥𝐚𝐡𝐞 𝐑𝐚𝐡𝐢𝐦𝐢, 𝐌𝐝 𝐓𝐚𝐡𝐦𝐢𝐝 𝐑𝐚𝐡𝐦𝐚𝐧 𝐋𝐚𝐬𝐤𝐚𝐫, 𝐒𝐡𝐞𝐫𝐢 𝐆𝐫𝐚𝐜𝐡, 𝐋𝐢𝐧𝐝𝐬𝐚𝐲 𝐁𝐞𝐫𝐭𝐫𝐚𝐧𝐝, 𝐋𝐚𝐦𝐞𝐬 𝐃𝐚𝐧𝐨𝐤, 𝐉𝐢𝐦𝐦𝐲 𝐇𝐮𝐚𝐧𝐠, 𝐅𝐫𝐚𝐧𝐤 𝐑𝐮𝐝𝐳𝐢𝐜𝐳, 𝐄𝐥𝐡𝐚𝐦 𝐃𝐨𝐥𝐚𝐭𝐚𝐛𝐚𝐝𝐢.
Multimodal Detection of Agitation in People With Dementia in Clinical Settings: Observational Pilot Study | JMIR Aging 2025
𝐀𝐮𝐭𝐡𝐨𝐫𝐬: 𝐀𝐛𝐞𝐞𝐫 𝐁𝐚𝐝𝐚𝐰𝐢, 𝐒𝐨𝐦𝐚𝐲𝐲𝐚 𝐄𝐥𝐦𝐨𝐠𝐡𝐚𝐳𝐲, 𝐒𝐚𝐦𝐢𝐫𝐚 𝐂𝐡𝐨𝐮𝐝𝐡𝐮𝐫𝐲, 𝐒𝐚𝐫𝐚 𝐄𝐥𝐠𝐚𝐳𝐳𝐚𝐫, 𝐊𝐡𝐚𝐥𝐢𝐝 𝐄𝐥𝐠𝐚𝐳𝐳𝐚𝐫, 𝐀𝐦𝐞𝐫 𝐌 𝐁𝐮𝐫𝐡𝐚𝐧.
Not Lost After All: How Cross-Encoder Attribution Challenges Position Bias Assumptions in LLM Summarization | EMNLP 2025
𝐀𝐮𝐭𝐡𝐨𝐫𝐬: 𝐄𝐥𝐚𝐡𝐞 𝐑𝐚𝐡𝐢𝐦𝐢, 𝐇𝐚𝐬𝐬𝐚𝐧 𝐒𝐚𝐣𝐣𝐚𝐝, 𝐃𝐨𝐦𝐞𝐧𝐢𝐜 𝐑𝐨𝐬𝐚𝐭𝐢, 𝐀𝐛𝐞𝐞𝐫 𝐁𝐚𝐝𝐚𝐰𝐢, 𝐄𝐥𝐡𝐚𝐦 𝐃𝐨𝐥𝐚𝐭𝐚𝐛𝐚𝐝𝐢, 𝐅𝐫𝐚𝐧𝐤 𝐑𝐮𝐝𝐳𝐢𝐜𝐳.
A Scoping Review of Algorithmic Equity, Data Diversity, and Inclusive Design in the Transformer Era of Clinical NLP | medRxiv 2025
𝐀𝐮𝐭𝐡𝐨𝐫𝐬: 𝐒𝐡𝐞𝐫𝐢 𝐆𝐫𝐚𝐜𝐡, 𝐀𝐛𝐞𝐞𝐫 𝐁𝐚𝐝𝐚𝐰𝐢, 𝐅𝐚𝐫𝐚𝐡 𝐀𝐡𝐦𝐚𝐝, 𝐄𝐥𝐡𝐚𝐦 𝐃𝐨𝐥𝐚𝐭𝐚𝐛𝐚𝐝𝐢.
Investigating Multimodal Sensor Features Importance to Detect Agitation in People with Dementia | CCECE 2023
𝐀𝐮𝐭𝐡𝐨𝐫𝐬: 𝐀𝐛𝐞𝐞𝐫 𝐁𝐚𝐝𝐚𝐰𝐢, 𝐊𝐡𝐚𝐥𝐢𝐝 𝐄𝐥𝐠𝐚𝐳𝐳𝐚𝐫, 𝐁𝐢𝐧𝐠 𝐘𝐞, 𝐊𝐫𝐢𝐬𝐭𝐢𝐧𝐞 𝐍𝐞𝐰𝐦𝐚𝐧, 𝐀𝐥𝐞𝐱 𝐌𝐢𝐡𝐚𝐢𝐥𝐢𝐝𝐢𝐬, 𝐀𝐧𝐝𝐫𝐞𝐚 𝐈𝐚𝐛𝐨𝐧𝐢, 𝐒𝐡𝐞𝐡𝐫𝐨𝐳 𝐒. 𝐊𝐡𝐚𝐧.
Research Labs
i4Health Research Lab
Dr. Elham Dolatabadi - Digital health and AI research - York University and Vector Institue - Faculty of Health and faculty of Engineering
IoT Research Lab
Dr. Khalid Elgazzar - Wearable sensors, AI and IoT - Computer Engineering , Ontario Tech University
IATSL Lab
Dr. Shehroz Khan - Intelligent assistive technology and systems lab - Department of Occupational Science and Occupational Therapy at the University of Toronto
Dr. Frank Rudzicz's Lab
Dr. Frank Rudzicz's - Machine learning, NLP, and healthcare - Faculty of Computer Science - Dalhousie University