Bert Huang is an assistant professor in the Department of Computer Science and the Data Intensive Studies Center at Tufts University. He earned his PhD from Columbia University in 2011, was a postdoc at the University of Maryland, and previously was an assistant professor at Virginia Tech. His research addresses topics surrounding machine learning. He focuses on modeling complex phenomena, learning in settings with low-quality data, and making algorithms more fair. His papers appear at conferences including NeurIPS, ICML, UAI, and AISTATS. He is also an action editor for the Journal of Machine Learning Research.
- 2018: Excellence in Access and Inclusion Award, Office of Services for Students with Disabilities, Virginia Tech
- 2017: Best Paper Award, IEEE/ACM International Conference on Social Networks Analysis and Mining (ASONAM)
- 2017: Best Paper Award, NeurIPS Workshop on Learning with Limited Labeled Data
- 2015: Reviewer Award, International Conference on Machine Learning (ICML)
- 2015: Deployed Application Award, Conference on Innovated Applications of Artificial Intelligence (IAAI)
- 2010: Andrew P. Kosoresow Memorial Award for Excellence in Teaching and Service, Columbia University Department of Computer Science