Madeleine Udell

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

    • low rank and structured optimization,

    • missing value imputation,

    • automated machine learning,

    • fair and interpretable machine learning,

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

  • Cornell 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.

  • Students at other universities: If you'd like to work with me, please apply to a PhD program at Cornell! I advise students in many different PhD programs: ORIE, Stats, CS, ECE, and CAM. Take a look at the core course requirements and faculty research profiles for each and see which one fits your interests best. 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

PhD students:

  • Lijun Ding, PhD student in ORIE. (Co-advised with Yudong Chen.) Semidefinite programming.

  • Chengrun Yang, PhD student in ECE. Automated machine learning.

  • Xiaojie Mao, PhD student in Statistics. (Co-advised with Nathan Kallus.) Reliable machine learning with observational data.

  • Yuxuan Zhao, PhD student in Statistics. Imputing missing data.

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

  • Miaolan Xie, PhD student in ORIE. Optimal experiment design.

  • Zachary Frangella, PhD student in CAM. Randomized numerical linear algebra.

Undergraduate students:

  • Kathy (Ja Young) Byun, undergraduate in ORIE. 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.

Masters students:

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

  • Nandini Nayar, MEng in ORIE. Resource allocation in AutoML.

  • Mi Zhou, MEng in CS. Neural PDEs.

  • Ziyang Wu, MS in CS. Low precision AutoML.

Other research affiliates:


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

Cornell PhD students:

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

Cornell undergraduates:

  • 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). 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:

  • 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:

  • Iddo Drori, visiting associate professor (MIT CS).

  • Yuqian Zhang, postdoctoral fellow (Rutgers ECE).

  • Jicong Fan, postdoctoral associate (CUHK Shenzhen Data and Decision Analytics).