Current Students and Postdocs

• Daniel Zhang: Online Boosting

• Mengjie Shi: Mobile Health

• Jonathan (Jack) Goetz: Active learning, Interactive Learning, Machine Learning in Chemistry (in close collaboration with Prof. Paul Zimmerman)
• Young Hun Jung: Online Boosting, Boosting with Complex Label Spaces, Bandit Problems
• Baekjin Kim: Perturbations based Methods in Bandit Problems
• Aditya Modi 🌟: Reinforcement Learning, Transfer/Multitask Learning (co-advised with Prof. Satinder Singh)
• Laura Niss: Sequential Decision Making, Fairness, Learning Analytics
• Yitong Sun: Scalable Kernel Methods, Connections with Neural Networks (co-advised with Prof. Anna Gilbert)

Alumni

• Mingyuan (William) Zhang (2017-2018): Settling the Minimax Regret in Online Learning to Rank with Top-k Feedback (link to thesis coming soon!). Next Step: Ph.D. in Computer Science at University of Pennsylvania
• Haoyu Chen (2016-2018): Kernel Methods for Activation Energy Prediction. Next Step: MSE in Data Science at University of Pennsylvania
• Zifan Li (2015-2017), Outstanding Undergraduate Major Class of 2017: Perturbation Algorithms for Adversarial Online Learning. Next Step: Ph.D. in Statistics at Yale University
• Xinyan Han (2014-2015): An Empirical Comparison of Various Online Binary Classification Algorithms. Next Step: MS in Computational Science and Engineering at Harvard University

• Michael Kovalcik (2015-2017): Mobile Health (co-mentored with Prof. Susan Murphy)
• Joshua Song (2016): NIDA challenge "Addiction Research: There's an app for that" (co-mentored with Prof. Predrag Klasnja, Prof. Susan Murphy, and Prof. Maureen Walton)
• Steven Zheng (2016): NIDA challenge "Addiction Research: There's an app for that" (co-mentored with Prof. Predrag Klasnja, Prof. Susan Murphy, and Prof. Maureen Walton)
• Cyrus Anderson (2014-2015): Development of HeartSteps, a mobile phone app for encouraging physical activity (co-mentored with Prof. Predrag Klasnja)
• Ning Niu (2015): Improving importance weighted active learning (co-mentored with Prof. Barzan Mozafari)
• Scott Bommarito (2013-2014): Development of a pilot version of an Android app for mobile health; Simulations with bandit learning algorithms
• Bingjie Xu (2013): Development of a pilot version of an Android app for mobile health

• Jin Seok (Andy) Lee (2014-2017): HeartSteps and NIDA challenge "Addiction Research: There's an app for that" (co-mentored with Profs. Predrag Klasnja and Susan Murphy)
• Anurag Beniwal (2015-2016): Learning Analytics
• Vatshank Chaturvedi (2014-2015): Matching Algorithms on Random Graphs

• Chansoo Lee, Ph.D. 2018: Analysis of Perturbation Techniques in Online Learning (co-advised with Prof. Jacob Abernethy). Software Engineer, Google, Pittsburgh.
• Kam Chung Wong, Ph.D. 2017. Thesis: Lasso Guarantees for Dependent Data. Advisory Services Senior, Ernst and Young, New York City.
• Mohamad Kazem Shirani Faradonbeh, Ph.D. 2017. Thesis: Non-asymptotic Adaptive Control of Linear-Quadratic Systems (co-advised with Prof. George Michailidis). Postdoctoral Fellow, Informatics Institute, University of Florida.
• Huitian (Emmy) Lei, Ph.D. 2016. Thesis: An Online Actor Critic Algorithm and a Statistical Decision Procedure for Personalizing Intervention (co-advised with Prof. Susan Murphy). Research Scientist, Amazon Alexa, Cambridge, MA.
• Sougata Chaudhuri, Ph.D. 2016. Thesis: Learning to Rank: Online Learning, Statistical Theory and Applications. Data Science Engineer, A9.com, Palo Alto.

• Harish Guruprasad Ramaswamy (2015): Weakly Supervised Learning (jointly mentored with Prof. Clayton Scott). Assistant Professor, Department of Computer Science and Engineering, IIT Madras.
• Kristjan Greenewald (2016-2017): Bandit Algorithms in Mobile Health (jointly mentored with Prof. Susan Murphy). Research Staff Member, MIT-IBM Watson AI Lab, Cambridge, MA.