Computer Engineering & Computer Science @ USC
Building AI/ML systems for healthcare and mission-critical applications
I'm a student researcher and engineer specializing in computer vision, multi-agent AI systems, and biomedical machine learning. My work focuses on translating AI research into practical tools for healthcare diagnostics, emergency response, and clinical applications.
Current focus: Real-time ML inference, agentic AI architectures, biomedical signal processing
Computer vision system for at-home medical guidance
Real-time guidance for accurate blood pressure measurement using object detection and pose estimation. Trained custom YOLOv8 model achieving 97% mAP on medical device detection, integrated with MediaPipe for pose-based feedback.
Python YOLOv8 MediaPipe PyTorch OpenCV
Emergency coordination platform with offline-first architecture
Edge computing platform enabling first responder communication during infrastructure failures. Implements guaranteed message delivery with UUID-based acknowledgment and automatic retry mechanisms.
TypeScript Node.js WebSockets Edge Computing
Software Engineering Intern • Chevron Corporation
May 2025 - July 2025
- Architected multi-agent generative AI system using Semantic Kernel, accelerating UI development by 95%
- Designed cross-agent validation algorithm improving system reliability by 40%
- Built real-time Angular dashboard for AI component preview and approval
Bioinformatics Research Intern • USC Institute for Technology and Medical Systems
August 2024 - May 2025
- Developed Python/Tkinter interfaces automating EEG data collection for 100+ patients
- Engineered feature extraction pipeline improving ML classification accuracy by 10%
- Reduced manual labeling time by 70% through automated biometric signal processing
Machine Learning Research Intern • UCLA Biomedical AI Lab
May 2024 - August 2024
- Built OCR model achieving 99% accuracy for retinal cancer biomarker extraction
- Developed preprocessing pipeline for 400+ medical images using TensorFlow and Keras
Machine Learning & AI
TensorFlow • PyTorch • Keras • YOLOv8 • MediaPipe • Scikit-learn • OpenCV
Languages
Python • Java • C/C++ • JavaScript • TypeScript • SQL • Go
Web & Cloud
React • Node.js • Angular • Vue.js • Express • PostgreSQL • Docker • Azure • GCP
Tools
Git • Linux • Supabase • RESTful APIs • SpringBoot
- Computer vision for medical applications
- Biomedical signal processing and ML
- Multi-agent AI systems and LLM orchestration
- Edge ML and real-time inference optimization
- HackSC 2025 Winner
- CURVE Research Fellowship - USC
- Asian Pacific Alumni Association Scholar
Open to research collaborations and technical discussions in AI/ML and healthcare tech.