• Stanford PhD students: I will be taking on a few PhD students this year. Send me an email or drop by my office hours if you're interested in working with me. Potential projects include

    • low rank and structured optimization,

    • learning faster optimizers for combinatorial problems

    • causal, interpretable, and/or automated machine learning,

    • elegant solutions to practical data challenges: missing values, outliers, distribution shift, expensive objective functions

    • if you have your own project in mind, come tell me about it!

  • Stanford masters and undergraduate students: Get in touch if you've got a strong computational background, have taken or are taking one of my classes, are willing to work on research for at least ten hours a week for at least a year, and are interested in one of the problems above; and mention you've read this. Unfortunately I do not have funding for masters and undergraduate students.

  • Students at other universities: If you'd like to work with me, please apply to the MS&E or ICME PhD program at Stanford! I'm not able to reply individually to emails from prospective students, but I'm glad to chat once you're accepted.

Current Research Group

Stanford PhD students:

  • Zachary Frangella, PhD student in MS&E. Randomized numerical linear algebra.

  • Mike Van Ness, PhD student in MS&E. Automated machine learning.

  • Ali Teshnizi, PhD student in MS&E. Deep reinforcement learning for combinatorial optimization.

  • Pratik Rathore, PhD student in EE. Randomized algorithms for optimization.

Cornell PhD students:

  • Shipu Zhao, PhD student in Systems Engineering. Automated analysis of algorithms.

  • Miaolan Xie, PhD student in ORIE. (Co-advised with Katya Scheinberg.) Optimal experiment design.

Cornell undergraduate students:

  • Yingxi Li, undergraduate in ORIE. Deep reinforcement learning for combinatorial optimization.



(Parentheses below enclose first employer after degree, if known.)

Cornell PhD students:

  • Chengrun Yang, PhD student in ECE (Google Brain). Automated machine learning.

  • Yuxuan Zhao, PhD student in Statistics (Two Sigma). Imputing missing data.

  • Lijun Ding, PhD student in ORIE (Postdoctoral Fellow at UWUW). (Co-advised with Yudong Chen.) Large scale semidefinite programming: simplicity, conditioning, and an efficient algorithm./

  • Xiaojie Mao, PhD student in Statistics (Tsinghua). (Co-advised with Nathan Kallus.) Machine Learning Methods for Data-driven Decision Making: Contextual Optimization, Causal Inference, and Algorithmic Fairness.

  • Yiming Sun, PhD student in Statistics (Amazon). Co-advised with Sumanta Basu. High Dimensional Data Analysis with Dependency and Under Limited Memory.

Cornell undergraduates:

  • Kathy (Ja Young) Byun, undergraduate in ORIE (PhD at Chicago Booth). Population segmentation for health system management.

  • Raye Liu, undergraduate in Math. Population segmentation for health system management.

  • Eliot Shekhtman, undergraduate in CS. Clustering mixed data.

  • Kevin Cushing, undergraduate in CS. Distribution shift.

  • Aparna Calambur, undergraduate in CS (CNA Research). Interpretable clustering.

  • Chris Qian, undergraduate in Math (PhD in Statistics at UIUC). Fairness in ML.

  • Eric Landgrebe, undergraduate in Math and CS (Facebook). Imputing missing data.

  • Brian Liu, undergraduate in ORIE (Microsoft, PhD at MIT). Interpretable machine learning.

  • Nick Bagley, undergraduate in Applied Math (PhD in Applied Math at University of Arizona). Learning PDEs.

  • Yuji Akimoto, undergraduate in CS (LA Dodgers Analytics). Automatic machine learning.

  • Charlene Luo, undergraduate in ORIE (Masters in Data Science at Columbia). Tensor factorization.

  • Yang Guo, undergraduate in Statistics (PhD in CS at UW Madison). Tensor factorization.

  • Dae Won Kim, undergraduate and MEng student in ORIE (Munich Reinsurance). Automatic machine learning.

  • Ahaan Nachane, undergraduate in CS (Braze). Data Infrastructure for Distributed Machine Learning.

  • Anya Chopra, undergraduate in CS. Low rank modeling in Python.

  • Patrick Nicholson, undergraduate in CS. Identifying gerrymandering.

  • Mihir Paradkar, undergraduate in BEE (Yelp). Data imputation for health care.

  • Zachary Rosenof, undergraduate in ORIE (McKinsey). Designing urban transport systems.

Cornell masters students:

  • Haoyue Yang: MS student in Statistics. Feature importance in tree ensembles.

  • Jason (Zuhao) Hua, MEng student in Information Science (American Express). Learning PDEs.

  • Ziwei Gu, MS in CS (Lyft). Population segmentation for health system management.

  • Ziyang Wu, MS in CS (PhD in CS at UIUC). Automated machine learning.

  • Nandini Nayar, MS in CS. Resource allocation in AutoML.

  • Mi Zhou, MS in CS. Neural PDEs.

  • Murali Thimma Selvan Babu, Jibran Gilani, Patchara Suensilpong, Yi Yao, MEng students in ORIE. Consumer segmentation for financial marketing.

  • Brandon Kates, MEng student in CS. Learning combinatorial algorithms.

  • Jianqiu Liu, Kyle Wadell, Jamie Wong, Michael Yuan, MEng students in ORIE. Unsupervised learning for cybersecurity.

  • Vidita Gawade, Caroline Troude, Juan Felipe Gonzalez Rodriguez, Yikun Cai, MEng students in ORIE. Forecasting wine harvest volume.

  • Qin Lu, MEng student in ORIE (Amazon). Interpretable machine learning.

  • Fan Liu, MEng student in ORIE (Goldman Sachs). Interpretable machine learning.

  • Fan Liu, David Lee, Soo Hyun Lee, Junrui Ye, and Srishti Sarawat, MEng students in ORIE. Forecasting grape ripeness.

  • Ishaan Jain and Darpan Kalra, MS students in CS. Deep learning for image classification.

Google summer of code:

  • Ayush Pandey, undergraduate in Mathematics and CS at IIT Kharagpur (ZemantaOutbrain). Optimization with complex variables./

  • Ramchandran Muthukumar, Masters student in Mathematics and undergraduate in CS at BITS Pilani. Faster presolve for linear programming and beyond.

Exchange students:

  • Huichen Li, undergraduate in CS at Shanghai Jiao Tong University (PhD in CS at UIUC). Learning low-rank tensors.

  • Sam (Song) Zhou, undergraduate in mathematics at Tsinghua (PhD in ORIE at Cornell). Convex optimization over combinatorial structures.

  • Ramchandran Muthukumar, masters student in Math and undergraduate in CS at BITS Pilani (PhD in CS at Johns Hopkins). PDE-constrained optimization.

Postdocs and visitors: