Machine Learning Engineer focused on LLM systems, retrieval, multimodal AI and efficient deep learning.
I recently completed my MS in ECE in Santa Clara University. My work includes sparse LLM fine-tuning, CUDA-based inference optimization, RAG systems, reinforcement learning, computer vision and multimodal research.
- LLM fine-tuning, inference optimization, activation sparsity, quantization, and CUDA kernels
- Retrieval-augmented generation systems
- Reinforcement learning applications
- Computer vision and multimodal ML across language, vision, and audio
- [ICLR 2025] SONICS: Synthetic Or Not - Identifying Counterfeit Songs
- [CVPRW 2024] Leveraging Generative Language Models for Weakly Supervised Sentence Component Analysis in Video-Language Joint Learning
- [IEEE ICIP 2023] ArtiFact: A Large-Scale Dataset with Artificial and Factual Images for Generalizable and Robust Synthetic Image Detection
- Syn-Att: Synthetic Speech Attribution via Semi-Supervised Unknown Multi-Class Ensemble of CNNs
- 1st at Deep Chimpact: Depth Estimation for Wildlife Conservation
- 1st(Jointly) at KaggleDays x ZbyHP Championship Meetup in Shanghai
- 1st (Student Team) & 4th at SIIM-FISABIO-RSNA COVID-19 Detection
- 1st at IEEE SP CUP 2022
- 2nd at IEEE VIP CUP 2020: Real-time vehicle detection and tracking at junction using a fisheye camera