Presented a paper on efficient VLM inference (SparseVILA) at ICCV’25; Presented a paper on efficient fine-tuning (SparseLoRA) at ICML’25; Two papers at ECCV 2024; Awarded the Vector Scholarship in AI & the Edward S. Rogers Sr. Graduate Scholarships in 2024; Delivered an oral presentation for a paper on dataset distillation at CVPR-DD 2024; Paper on efficient model compression for transformers accepted to ICLR 2024; Paper on efficient probabilistic contrastive learning accepted to ICASSP 2024; Paper on dataset distillation accepted to ICCV 2023; Paper on common frequency domain pruning accepted to CVPR-ECV 2023.
Research Experience
Working at Google, building multi-modal machine learning models; Published papers at multiple international conferences.
Education
University of Toronto, Graduate Student, Advisor: Konstantinos N. Plataniotis
Background
A graduate student at the University of Toronto researching efficient machine learning applied to computer vision and natural language processing. Currently at Google building multi-modal machine learning models.