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GLSVLSI 2025 (Conference)
GLSVLSI 2025 (Conference)
One of my recent projects, in collaboration with Prof. Peter A. Beerel at USC, explores secure and distributed inference for large language models. Our work proposes a lightweight framework that can detect and isolate faulty or malicious behavior during ML inference, a critical need for edge deployments. This project was accepted to GLSVLSI 2025, marking my first academic publication.
This is the link to our paper. Give it a read :)
Pituitary Tumor Classification using Deep Learning (Research)
Pituitary Tumor Classification using Deep Learning (Research)
Contributed to deep learning based tumor classification using MRI data, focusing on early-stage detection techniques. Gained exposure to clinical imaging workflows and interdisciplinary collaboration in a short term research capacity in Fan Magnetic Resonance (MR) Imaging Lab under Prof. Zhaoyang Fan.
Unification of Graphical Processing & Computation Architecture in GPU (Presentation)
Unification of Graphical Processing & Computation Architecture in GPU (Presentation)
Conducted a literature based research project on unified GPU architectures under Prof. Rahul Ratnakumar and presented applications and theoretical optimizations for parallel processing in healthcare and AI domains.
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