About me

I am an experienced engineering leader with expertise in machine learning and recommendation system. I have a passion for applying machine learning and artificial intelligence technologies and building innovative products to solve challenging real-world problems.

Currently, I am a senior engineering manager and the single-threaded leader of Friending product at Snap. We build features to improve Friending experience, combat friending spam, and enhance machine learning systems to generate more relevant and timely friend recommendations for our users.

I have worked as a senior applied scientist and tech lead at Amazon, where I lead a team of scientists and engineers to forecast sales velocity for various promotions and rank recommendations on Seller Central homepage for selling partners. Before joining Amazon, I was a research tech lead at eBay where our team built machine learning solutions for the paid internet marketing on Google and Facebook. Our ML model optimizes the bidding strategies, provides personalized recommendations to maximizes the return-over-investment.

I also have a passion in teaching and helping more people into the field of machine learning and data science. Currently I teach several courses in the Foster School of Business at University of Washington, including Advanced ML, Deep Learning and Big Data, and Natural Language Processing.

I received my Ph.D in Computer Science from Oregon State University working with Dr. Weng-Keen Wong. During the Ph.D. study, my research focused on using probabilistic graphical models and crowdsourcing to predict species distribution using citizen science data and quantify the skill level of citizen scientists in the eBird project. Please refer to the publication page for details.