About Me

I am Zhiqi Bu (卜至祺), a.k.a. Woody. I am an Applied Research Scientist at Amazon AI. 

I obtained my Ph.D. in the Applied Maths and Computational Science program (AMCS) at University of Pennsylvania in 2021, under Benjamin Franklin Fellowship. I also obtained M.A. in Statistics from Wharton School at Penn. I was advised by Weijie Su in the Department of Statistics, Wharton School and by Qi Long in the Department of Biostatistics, Perelman School of Medicine. 

Originally from China, I completed my B.A. (Honors) in Mathematics at the University of Cambridge and my M.A. in Mathematics at Columbia University. After that, I spent half a year as a visiting scholar at KAUST in Extreme Computing Research Center, advised by Prof. David Keyes. In 2018, I joined United Nations as a data scientist intern. In 2020 summer, I became a research scientist intern at Microsoft Research,  hosted by Janardhan Kulkarni and Sergey Yekhanin. In 2021, I joined Amazon AWS AI as a research scientist intern, hosted by Yu-Xiang Wang and Zha Sheng.

My research focuses on understanding and improving the optimization of deep learning models, which includes optimization algorithms (e.g. differential privacy and distributed learning), algorithmic efficiency (e.g. computation, communication, hyper-parameter tuning), and large language/vision models (1-100B). 

I’m looking for highly motivated collaborators all the time. Please contact me through this form if you’re interested.

Random Things

• Admitted to Cambridge in 2012, graduated in 2015, with a B.A. in Maths.

• Admitted to Columbia in 2015, graduated in 2016, with a M.A. in Maths.

• Spent 6 months researching in KAUST, Saudi Arabia.

• Admitted to University of Pennsylvania Ph.D. in 2017, with a scholarship.

• Interned at United Nations (New York, 2018).

• Got my first conference paper at  NeurIPS in 2019/09! 7 months maths. Worth it.

• Attended my first workshop SAMSI at Duke University, 2019/08.

• Presented my first poster in WHOA-PSI at WUSTL, 2019/08.  

• Gave my first talk at ICSA International Conference in Hangzhou, 2019/12.

• Code for my differential privacy paper merged to Tensorflow!

• Reviewing journal paper the first time for IMAIAI, 2020.

• Interned at Microsoft Research, Algorithm Group, 2020.

• Got my first NeurIPS spotlight paper in 2020.

• Got my first journal paper at IEEE Transactions on Information Theory in 2020.

• Received my M.A. from Cambridge (not a degree), 2020

• Reviewing conference paper the first time for AISTATS 2021.

• Received my Wharton M.A. in Statistics, 2021

• Interned at Baidu USA lab and Amazon AWS, 2021.

• Defended my Ph.D. dissertation thesis, 2021 Nov!

• Joined Amazon AWS/AGI as Applied Scientist, 2022.

• World's most efficient DP system -- Fast Differential Privacy is now public! 

• Trained Amazon LLM foundation models (Amazon's ChatGPT) Nova and Titan

• 7 NeurIPS/ICLR/ICML papers in 2024

• ...

For more information, see my LinkedIn.

For codes, see my Github.

For papers, see my Google Scholar.