About Me

I'm Zhenlin Wang. You can call me Criss as well. I'm currently an MS student at Machine Learning Department @ Carnegie Mellon University. I have a strong passion for machine learning and AI-powered softwares. Recently I'm drawn to performance optimization of deep learning systems and AI tools. In particular, I've been studying and playing around with distributed systems, MLOps and CUDA-based parallel computing.

Before coming to the US, I graduate with First Class Honor from National University of Singapore (NUS) with a B.S. double major in Applied Mathematics and Computer Science. There I was fortunate enough to work with Prof. Jonathan Scarlett and Bryan Low on multi-arm bandit, bayesian optimization and high-dimensional statistics. I also worked with Prof. Kevin Jamieson and his Phd Andrew Wagenmaker on bandit and Reinforcement Learning problems.

Engineering is an integral part of my life since my 15. I built an event-driven signal generation system at J.P. Morgan Securities LLC for its securitzed product trading using Python and C++. I also led the design, implementation, deployment and monitoring of an ML-based price suggestion tool for eyos.one an IT-startup based in Singapore. At NUS, I've collaborated with MOH Office for Healthcare Transformation to develop Schizophrenia relapses forecasting models with ML workflow covering data prep, model experimentation, finetuning, artifact storage, inference service implemenetation and orchestration and distributed deployment.

About the blogs

I started maintaining this website from my sophomore year in NUS. The original version used a minimal-mistake style and I've migrated into the hexo-icarus style on Aug 2022.

The blogs here covers various topics in DS/AI/ML and software engineering are written here. The mathematical/technical details are presented. I often included some discussion about the pros/cons of the methodologies outlined in these blogs. Nonetheless, I don't think that any blog post can be mark "DONE" as new perspectives on these topics can always supplement what's on the posts. Thus, I consistently update these posts whenever I learn some new knowledge about the topics discussed in these posts.

Disclaimer: I try my best to give credit for all sources I made referenecs to. If you found some parts in my post that were referenced from your work without credit, please kindly contact me so I can immediately correct my mistakes and make apology.

Special thanks

In retrospect, I have to thank @Lei Mao for the inspiration to build a website from scratch. I followed him since 2018 when I read his motivating background story. When trying to customizing the pages, I learnt from @iMaeGoo, @Xinyu Liu and @Pengyuan Li, and I thank them for their great tutorials on website styling.