AI Engineer · Full Stack Developer
Building AI-powered products across web, mobile, and robotics
I'm a Machine Learning Research Engineer working across LLM evaluation, multimodal AI, reinforcement learning, and robotics. My work spans simulation-based robot learning, imitation learning for contact-rich manipulation, and applied ML research — with a couple of publications in healthcare ML along the way. Currently sharpening Rust and Go, and always up for talking GPUs, deep learning systems, or open source.
🎓 MS Computer Science (STEM) — Clark University · ML for Robotics, 4.0 GPA — Worcester Polytechnic Institute
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Multi-task robotic simulation environments in MuJoCo modeling push-dynamics and forward kinematics. DDPG and A3C agents compared for continuous control across convergence, reward shaping, and policy robustness.
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Action Chunking Transformer for contact-rich peg-in-hole insertion — a UR10 arm trained in MuJoCo from expert demos, no RL reward signal. Multi-view RGB + pose + joint-state observation pipeline hit sub-millimeter precision.
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Real-time autonomous voice agent using GPT-4o and Whisper ASR with Twilio for end-to-end call handling. Hybrid LLM + state-machine architecture with session memory and TTS caching for low-latency, reliable task completion.
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Languages
Robotics & ML
Infra & Cloud
- Surgical Decision Making for Renal Cell Carcinoma using Machine Learning Models — Machine Learning for Cancer and Healthcare Systems Research, Taylor & Francis (accepted, to appear)
- Feature Selection for Renal Cancer Across Geographic Regions using AI Techniques — Machine Learning for Cancer and Healthcare Systems Research, Taylor & Francis (accepted, to appear)
