I'm a student at UC Santa Barbara with a strong interest of deep reinforcement learning, control theory, and scalable ML systems. I'm interested in learning about the design of intelligent autonomous systems as well as the infrastructure needed to deploy them in productions. Aside from academic interests, I'm also motivated to innovate and create effective solutions, both for the open source community through collaborative development, and for real-world business challenges with data-driven approaches.
Research Interests:
- Deep Reinforcement Learning for video games and autonomous systems
- Data-Driven Control methods that combine classical control theory with modern machine learning
- MLOps and Distributed Systems for deploying production-grade machine learning systems
- ML Algorithms and Natural Language Processing for building intelligent information retrieval systems
Currently exploring:
- Building robust distributed training infrastructure for large-scale ML and AI model deployment.
- Advanced RL algorithms (DQN, PPO, SAC) for real-time autonomous sytems and state-action space in video games.
- Designing efficient MLOps workflows tailored for AI agent systems, focused on automated agent deployment, monitoring and reliability in production environments.
- Developing algorithms and NLP techniques to enhance intelligent information retrieval, search relevance, and recommendation systems.
