IMPACT-AI LAB

Innovative Machine Learning for Precision, Analytics, Care & Treatment

Led by Dr. Divya Sharma, York University

About Our Lab

Innovative Machine Learning for Precision, Analytics, Care & Treatment

The IMPACT-AI Lab at York University, led by Dr. Divya Sharma, is dedicated to building intelligent, ethically grounded, and clinically impactful AI systems for healthcare. Our work bridges the gap between advanced machine learning methods and real-world medical decision-making. We collaborate closely with clinicians and researchers at the University Health Network (UHN), including Toronto General Hospital, Princess Margaret Cancer Centre, and the Schroeder Arthritis Institute. Our research spans diverse domains such as liver transplantation, osteoarthritis, mental health, and precision oncology. From predicting graft injury in liver transplant recipients to identifying multi-omic signatures of osteoarthritis progression and designing generative AI companions for mental health support, we harness AI to enable personalized, explainable, and equitable care. Our interdisciplinary team develops and applies deep learning, reinforcement learning, and generative AI methods across structured, unstructured, and multi-modal biomedical data. We are committed to building AI systems that not only perform but also integrate into clinical workflows, ensuring relevance, transparency, and real-world utility.

Latest News

News 1

May 1, 2025

New CIHR-Team Grant Awarded

The IMPACT-AI Lab is proud to be part of the newly funded CIHR Team Grant, Team Liver AI. As co-PI, Dr. Divya Sharma leads the development of AI models to predict long-term graft health integrating clinical data with social determinants like income, geography, and systemic barriers. This work aims to build equitable, data-driven tools for Canada’s diverse liver transplant population.

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News 2

May 7, 2025

Connected Minds Knowledge Mobilization Grant

The IMPACT-AI Lab has received a Connected Minds Knowledge Mobilization Grant to host a symposium on AI and Mental Health. This event will bring together researchers, clinicians, and community members to explore the role of AI in advancing mental health care.

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News 3

May 26th, 2025

1st Prize in Oral Presentation at CSSC, Saskatoon

Master's student Jingwen Ji's work on RL for sepsis management was awarded 1st prize in Oral Presentation at the Canadian Statistical Student Conference part of SSC 2025 in Saskatoon.

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News 4: Dr. Divya Sharma delivered an invited talk on “Introduction to Machine Learning” at the Department of Medicine Clinician Scientist Training Program Workshop, co-hosted with T-CAIREM, U of T (Mar 12, 2025)
News 5: Dr. Divya Sharma presented “Advanced Machine Learning for Multimodal Data Integration in Healthcare” at the TABA Seminar (Feb 28, 2025)
News 6: Dr. Divya Sharma gave an invited talk on “Development of AI Tools to Address Clinical Nuances in Transplantation” at the Transplant AI Symposium 2024, hosted by the Ajmera Transplant Centre, UHN (Nov 18, 2024)

Archived News

Dr. Divya Sharma delivered a lightning talk at CANSSI Showcase 2024 titled “Beyond Traditional Statistics: Harnessing Machine Learning for Personalized Osteoarthritis Treatment with a Multimodal Deep Learning Approach."

Nov 15th, 2024

Dr. Divya Sharma organized and presented at the International Day of Women in Statistics and Data Science (IDWSDS 2024), delivering a talk titled “Harnessing Data Science and Machine Learning for Personalized Osteoarthritis Treatment”, highlighting the role of AI in advancing precision MSK care.

October 2024

Invited Talk at UoT

September 2024

Dr. Sharma gave an invited seminar on “Machine Learning Approaches in MSK Research: Challenges, Applications, and Future Scope” for the Collaborative Specialization in Musculoskeletal Sciences at the University of Toronto.

Research Highlights

Our key research areas

Research Area 1

Reinforcement Learning for Dynamic Systems

RL applied in the area of precision medicine to develop personalized treatment strategies and optimize clinical decision-making processes.

Research Area 2

Generative AI

Large language models for mental health support and therapeutic interventions, agentic AI systems for liver disease management and clinical decision support, and generative models for genomic data synthesis and interpretation.

Research Area 3

Multimodal Integrative Deep Learning

Multimodal data based deep learning models integrating multiple domains and applied to Mental Health Data and Osteoarthritis Data.

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