About

Chi Wang is a highly experienced research scientist with over 10 years of experience in systems and theory for data platforms and data science. He has worked extensively on automated machine learning, machine learning for systems, scalable solutions for data analytics and data science, and knowledge mining from text data and graph data. He has won the prestigious SIGKDD Data Science/Data Mining PhD Dissertation Award for his outstanding work in this field. Chi is currently working as a Software Engineer Intern at Facebook on the Ads Optimization team. He is working on a project that involves learning user-ad relevance in large-scale heterogeneous social networks. He is being mentored by Dr. Rajat Raina and is responsible for training on historical click data to learn a user-ad-cognitive-relevance feature on generic concept space for CTR prediction, to integrate concepts from heterogeneous sources. Prior to his current role, Chi worked as a Research Assistant at the University of Illinois at Urbana in the Data Mining Group, where he was advised by Prof. Jiawei Han. He has also worked as a Researcher at Microsoft. Chi holds a Ph.D. in Computer Science from the University of Illinois, where he completed his thesis on knowledge mining from text data and graph data. He also holds a B.E. in Computer Sciences and Technology from Tsinghua University and has completed additional coursework at the School of Sciences at Tsinghua University. Chi is highly skilled in a wide range of technologies, including ML, Python, web technologies, big data, hyperparameter tuning, data engineering, AI, NLP, neural networks, mobile development, information retrieval, search, and software engineering. With 8.7 years of relevant experience, he is a highly sought-after expert in the field of data science and machine learning. He is also the creator of FLAML, one of the best open source libraries for AutoML and tuning.