I am a third-year Computer Science student at York University (Lassonde School of Engineering). I work at two layers of the stack: deep learning for medical imaging, and computer arithmetic and VLSI. The thread between them is a design taste I keep returning to: put the hard, verifiable guarantee in the core and reserve the intelligence for the edge, where it earns its cost.
I am building toward the intersection of technology and research.
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A medical reversal radar that flags treatments whose evidence has already been overturned by an updated guideline. A deterministic rules engine does the safety-critical flagging with zero LLM cost; Microsoft Foundry IQ supplies on-demand, citation-grounded explanations.
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Connect on LinkedIn for research collaborations, ML engineering conversations, or hardware-adjacent opportunities.
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Also: RISC-V · SystemVerilog / Verilog (RTL design) · MONAI · FastAPI · Electron · MS SQL Server · Vivado · Jupyter
