Rasa Khosrowshahi

CS PhD Student @ Brock University · Previously: MASc. @ Ontario Tech University

prof_pic.jpg

rkhosrowshahli [at] brocku [dot] ca

I’m a Computer Science PhD student at Brock UniversityBrock University logo working under supervision of Prof. Shahryar Rahnamayan and Prof. Beatrice Ombuki-Berman.

My research focuses on gradient-free optimization and learning for memory compression and other challenging machine learning problems, especially when gradients are unavailable, expensive, or difficult to use effectively. I use gradient-free evolutionary algorithms with subspace optimization for efficient fine-tuning, working at the intersection of learning, optimization, and model efficiency. More broadly, my interests include multi-task and single-task learning, multi-objective learning, representation learning, machine unlearning, responsible AI, and dimensionality reduction in optimization.

Previously, I earned MASc. in Computer Engineering at Ontario Tech University Ontario Tech University logo, where I worked on center-based sampling, large-scale global optimization, differential evolution, and multi-objective optimization.

I also work on gradient-based multi-objective learning through research software. I am a member of the Simplex LabSimplex Lab logo organization, where I build open-source ML infrastructure for scalable experimentation, PyTorch training workflows, and reproducible optimization research, and I am currently contributing to the TorchJD framework, an open-source PyTorch library for Jacobian descent and multi-objective optimization.

Alongside research, I enjoy teaching, mentoring, and course design. I was lecturer for “Topics in Computational Intelligence” COSC 4P96 (Winter 2026) at Brock UniversityBrock University logo and have assisted artificial intelligence, data structures, machine learning, engineering design, and software engineering courses.

Brock students interested in undergraduate research projects, including COSC 3P99 or COSC 4F90, with me and Prof. Beatrice Ombuki-Berman are welcome to reach out.

news

May 27, 2026 We are thrilled to announce the acceptance of TorchJD into the PyTorch Ecosystem!
Mar 16, 2026 Our work Center-based Sampling in Optimization and Machine Learning: A Theory and Review was accepted to the CEC Theory session at WCCI 2026.
Jan 27, 2026 Our work Multi-Objective Reference-Aligned Machine Unlearning was accepted at Canadian AI 2026.
Aug 01, 2025 Our work Enhancing image retrieval through optimal barcode representation was accepted by Scientific Reports.

latest posts