Our Mission!
Insight for Health (i4Health) Research Lab is dedicated to making generative AI models evolve as dynamic and adaptive tools to enhance health through iterative learning, alignment, and interpretability.
Research Themes and Focus Areas
Multimodal learning
Algorithmic Fairness
Interpretability and Explainability
(Human-AI) Evaluation and Alignment
News
March 2025 - Our paper Similarity-Aware Token Pruning: Your VLM but Faster is now available on arxiv.
Feb 2025 - Our lab is delighted to welcome Abeer Badawi as a postdoctoral fellow.
Jan. 2025 - Congratulations to Juan Medina on defending his Mater's at U of T.
Dec. 2024 - Our lab has received a seed grant from the LongCovid Web.
Sep. 2024 - Congratulations to Juan Medina on receiving CanTreatCOVID Master’s Scholarship
Sep. 2024 - Our lab is delighted to welcome three new brilliant members, Nathan Kabore, Shayan Emzad, and Negin Baghbanzadeh.
Sep. 2024 - Dr. Dolatabadi is featured in the Vector Institute Annual Report for the Kids Help Phone project.
Aug. 2024 - Our recent research, “Transitioning sleeping position detection in late pregnancy using computer vision from controlled to real-world settings: an observational study,” has been recently published in Nature Scientific Reports;
Jan. 2024 - Our lab is delighted to welcome three new brilliant members, Noor Qaiser, Mansoure Jahanian, and Yasaman Parhizkar.
Dec. 2023. Dr. Dolatabadi is featured in a National Post interview discussing the transformative impact of AI on healthcare in Canada. Additionally, my insights were quoted in a blog post titled "Five ways artificial Intelligence is improving health care in Canada”
Oct. 2023 - Our recent research, “Vision-based detection and quantification of maternal sleeping position,” has been recently published in PLoS Digital Health;
Sep 2023 - we have an open Research Internship position in Machine Learning and Bio-informatics (to be appointed at UHN): Job posting link and @UHN ;
Sep 2023 - Our recent collaborative work with @TELUS, @DeloitteCanada & @RocheCanada, “Using Social Media to Help Understand Patient-Reported Health Outcomes of Post–COVID-19 Condition: NLP Approach” has been recently published in @jmirpub
June 2023 - Our lab received collaborative seed funding for the project Machine Learning for Post-Covid Condition in collaboration with York University, GEMINI, and LongCovid Web.
June 2023 - Congratulations to Allan Kember on successfully defending his Master's thesis
May 2023 - Our lab received an NSERC Discovery Grant for the project titled "Deep Multimodal Learning for Healthcare: Towards Building Multimodal Pathway Health Networks".
May 2023 - Our paper on using NLP for clinical laboratory Data Repository Systems is published at JMIR AI
April 2023 - Congratulations to Sina Akbarian on his new IEEE access paper on evaluating knowledge transfer in NN for medical images.
Feb 2023 - Our paper on diagnosing harmful data shift is now available on medrxiv
Joining the Lab (Open Positions)
Thank you for your interest in working with us. We are constantly seeking individuals who are motivated and possess exceptional talent. We are committed to promoting Equity, Diversity, and Inclusion (EDI) in our lab and strongly encourage individuals from diverse backgrounds to apply.
Are you interested in ML for Health? Are you enthusiastic about playing a vital role in advancing the ongoing revolution in the field of Machine Learning for Health? Our lab is seeking highly motivated individuals; we have the following positions available:
Graduate Students for Fall 2024 at the School of Health Policy & Management (Faculty of Health) and also jointly with Lassonde School of Engineering at York
Postdoctoral Fellow
Research Volunteer, Practicum, Capstone Project, or Degree Research Paper
If you're interested in joining our team and wish to be contacted, kindly complete this Google form.
https://forms.gle/JLCqQb3LDbqf1wEWA
Email us:
If you are interested in collaborating with us or would like to obtain further information about our research projects, please do not hesitate to reach out to us at edolatab{AT}yorku{.}ca.