🎓 I'm a PhD student in Health Systems Research at the University of Toronto (IHPME), and I get to work out of the Digital Mental Health Lab at CAMH!
🧠 These days I'm digging into AI safety in health care, especially how large language models behave when people turn to them for mental health support.
🏥 Before Toronto, I did my MS in Computer Science (Biomedical Informatics) at Arizona State University, where I built tools that help patients control how their sensitive health data gets shared.
💼 I also spent three fun years writing trading and compliance software at Credit Suisse, and graduated from VNIT Nagpur with a B.Tech in Computer Science.
🎸 When I'm not at my desk, I'm practicing bass guitar (suboptimally), playing football, or hunting down the best thrift finds in Toronto. Shoutout to Kensington Market!
💬 Always happy to chat about health AI, AI safety, FHIR, or any of the projects here, so feel free to reach out!
🌐 You can find my publications and projects at abhisheksinghdhadwal.github.io.
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University of Toronto
- Toronto, Canada
Highlights
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Indian-Sign-Language-Translator
Indian-Sign-Language-Translator PublicAn Indian Sign Language Translator, created with the aim of achieving near-real time outputs, along with background and illumination independence.
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TS4H_4Hz_4Pages
TS4H_4Hz_4Pages PublicCode associated with the NeurIPS 2025 Time Series 4 Health (TS4H) Workshop Paper - "4Hz, 4 Pages"
Python 1
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cqframework/cql-studio
cqframework/cql-studio PublicForked from preston/cql-studio
Clinical Quality Language development suite for artifact authoring, testing, and engine validation.
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MRUNet-Masking
MRUNet-Masking PublicAn experimental implementation of MultiRes-U-Net for facial feature segmentation using the CelebAMaskHQ dataset.
Jupyter Notebook 1
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Generating-T2-MRI-from-T1-Scans-Using-CycleGAN
Generating-T2-MRI-from-T1-Scans-Using-CycleGAN PublicCycleGAN-based model for generating T2-weighted MRI images from T1 scans to enhance diagnostic accuracy with unpaired datasets.
Jupyter Notebook
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In-Surely
In-Surely PublicAn interactive insurance policy query-answering notebook with a Retrieval-Augmented Generation (RAG) pipeline with semantic search, caching, and GPT-based response generation.
Jupyter Notebook
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