Machine Learning Engineer building large-scale ML systems, with a background in robotics and 3D perception.
Currently working on production recommendation systems at TikTok, serving billions of users across global markets. My work focuses on designing scalable ML systems, improving efficiency, and bridging modeling with real-world system constraints.
Before industry, my research at Georgia Tech focused on robotics perception:
- 3D vision, object pose estimation, and tracking
- Category-level understanding and robust perception under real-world conditions
- Publications at ICRA / IROS
- Large-scale ML systems (training, serving, optimization)
- User intent modeling & decision systems
- System efficiency (latency, throughput, compute trade-offs)
- Bridging models with infrastructure in production
- Robotics & autonomy (perception + decision-making)
- Real-world ML systems beyond offline metrics
- RL / learning-based control for large-scale systems
- Bringing research ideas into production environments
Interested in robotics, autonomy, or building ML systems that work in the real world.