William Wong

Some companies I have worked at:

Google DeepMind
- Worked on the Gemini large language model.
- Researched reinforcement learning to optimize Google's industrial air cooling systems.
Amazon - added intelligence to the first Amazon Asto home robot.
Google - created a pipeline that processes and surfaces millions of rows of data daily.
Proteus Digital Health - automated backend infrastructure resulting in 60x speedup.
Vectorspace AI - applied machine learning for stock trading, head of blockchain development.

Check out my resume for a full summary of my experience.

At Google DeepMind, my research focus has been on Large Language Models and Reinforcement Learning.

Gemini 2.5 Technical Report 2025: Gemini 2.5: Pushing the frontier with advanced reasoning, multimodality, long context, and next generation agentic capabilities [Paper]
Gemini 1.5 Technical Report 2024: Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context [Paper]
Gemini 1.0 Technical Report 2023: Gemini: a family of highly capable multimodal models [Paper]
NeurIPS 2022 Reinforcement Learning for Real Life Workshop: Optimizing Industrial HVAC Systems with Hierarchical Reinforcement Learning [Paper]
- William Wong, Praneet Dutta, Octavian Voicu, Yuri Chervonyi, Cosmin Paduraru, Jerry Luo.

With Professor Zach Lipton, I investigated risk sensitive learning and optimization methods to improve continual learning.

ICML 2022 Responsible Decision Making in Dynamic Environments: RiskyZoo: A Library for Risk-Sensitive Supervised Learning [Paper] [Code]
- William Wong, Audrey Huang, Liu Leqi, Kamyar Azizzadenesheli, Zachary C Lipton.

I explored the application of deep learning in sustainable agriculture at BAIR under Professor Ken Goldberg.

IEEE T-ASE 2022 Journal: Simulating Polyculture Farming to Tune Automation Policies for Plant Diversity and Precision Irrigation [Paper (IEEE)] [Code]
- Yahav Avigal, William Wong, Mark Presten, Mark Theis, Shrey Aeron, Anna Deza, Satvik Sharma, Rishi Parikh, Sebastian Oeheme, Stefano Carpin, Joshua H. Viers, Stavros Vougioukas, Ken Goldberg.
IEEE ICRA 2021: Learning Seed Placement and Automation Policies For Polyculture Farming with Companion Plants [Paper (IEEE)] [Paper (GDrive)] [Video] [Code]
- Yahav Avigal, Anna Deza, William Wong, Sebastian Oehme, Mark Presten, Mark Theis, Jackson Chui, Paul Shao, Huang Huang, Atsunobu Kotani, Satvik Sharma, Michael Luo, Stefano Carpin, Joshua H. Viers, Stavros Vougioukas, Ken Goldberg.
IEEE CASE 2020 Best Student Paper Winner: Simulating Polyculture Farming to Tune Automation Policies for Plant Diversity and Precision Irrigation [Paper (IEEE)] [Paper (GDrive)] [Video] [Code]
- Yahav Avigal, Jensen Gao, William Wong, Kevin Li, Mark Theis, Mark Preston, Grady Pierroz, Fang Shuo Deng, Ken Goldberg.

I also studied imitation learning through robot workbench decluttering, created an AI art exhibition in New York and wrote an earthquake visualization art piece Mori by Goldberg et. al.