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 controlled environment agriculture (CEA) optimization, energy optimization, etc.
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
- DL/ML platform
Below are some of the projects in which I’ve played a leading role:
- 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
- Our autonomous greenhouse control work (codename Sonoma) was featured on Venture Beat.
- We have been selected as one of the top 5 teams to compete in the Autonomous Greenhouses Challenge
- Microsoft Asia News Center describes our indoor vertical farming research
- Project FarmBeats highlighted by Satya Nadella as one of 10 projects that inspired him in 2017
- Image Captioning Service starts to serve Microsoft Office users – Word and PowerPoint will use AI to automatically write photo descriptions – more on Office blogs, The Verge, VentureBeat.
- CaptionBot.ai has received millions of requests for captioning. Lots of fun stories are shared at Business Insider, TechCrunch, Engadget, The Washington Post, Forbes, CNN, Gizmodo, BBC, The Telegraph, Daily Mail, The Guardian, Mashable, and more (tech summarized here).