Welcome! I am a tenure-track assistant professor in the Department of Computer Science at Rensselaer Polytechnic Institute (RPI).
My research interests mainly focus on the intersections between Theoretical Computer Science and Machine Learning. In particular, I am interested in the theoretical foundations of practical learning problems and the design of algorithms with rigorous guarantees therein. Topics under this umbrella include learning in sublinear models, learning with uncertainty and partial information, and machine learning applications with provable guarantees. More broadly, I am also interested in streaming algorithms and lower bounds, graph algorithms, statistical learning theory, and data processing privacy.
Prior to my current role, I was a postdoc researcher hosted jointly by Vladimir (Vova) Braverman at Rice University and Samson Zhou at Texas A&M University. I obtained my Ph.D. at Rutgers University, where I was extremely fortunate to be advised by Sepehr Assadi. Even before, I received my MSc degree from University College London (UCL), England. I got my B.Eng. degree from Northwestern Polytechnical University, China. I also spent a semester at Shih Hsin University, Taiwan, and briefly worked at Sichuan University, China. Outside academia, I have research experience at Google Research, where I was an intern mentored by Rajesh Jayaram.
Email:
wangc33[at]rpi.edu
chen.wang.research[at]gmail.com
Office: MRC 310
I'm looking for motivated Ph.D. students with strong backgrounds in mathematics, algorithm design, and machine learning. If you are interested in working with me, please read this.
If you are interested in working as a postdoc with me, please send me an email with your research interests and publication record.