I’m a Principal Research Engineer in the Deep Learning Technology Center. I have a wide interest in Machine Learning spanning from theory to practice to system designs.
My current main research pursuit is reinforcement learning (RL) with focus on
- model-based reinforcement learning, uncertainty quantification, and planning/decision making under uncertainty;
- and real-world optimal control applications, including indoor farming optimization and industrial robotics at large.
Previously, I’ve also worked on
- Convolutional neural nets and computer vision (object detection, image segmentation, image classification, etc.)
- Image captioning and multimodal modeling
- Optimization algorithms (SDCA, etc.)
- DL/ML platform
I’ve led the research and development for projects such as
- Deep Reinforcement Learning for Control Problems in Data Center Energy Optimization, Indoor Agriculture, etc.
- Project FarmBeats: AI & IoT for Agriculture
- Computer Vision API for Cognitive Services
In addition, I’m also the chief mentor of Microsoft AI School’s advanced projects class.