Ellen Vitercik
Assistant Professor of Management Sciences and Engineering and of Computer Science
Management Science and Engineering
Academic Appointments
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Assistant Professor, Management Science and Engineering
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Assistant Professor, Computer Science
2025-26 Courses
- AI for Algorithmic Reasoning and Optimization
CS 331X, MS&E 331 (Aut) - Design and Analysis of Algorithms
CS 161 (Win) - Introduction to Probability
MS&E 120 (Aut) -
Independent Studies (15)
- Advanced Reading and Research
CS 499 (Aut, Win, Spr, Sum) - Advanced Reading and Research
CS 499P (Aut, Win, Spr, Sum) - Curricular Practical Training
CS 390A (Aut, Win, Spr, Sum) - Curricular Practical Training
CS 390B (Aut, Win, Spr, Sum) - Curricular Practical Training
CS 390C (Aut, Win, Spr, Sum) - Directed Reading and Research
MS&E 408 (Aut, Win, Spr, Sum) - Independent Project
CS 399 (Aut, Win, Spr, Sum) - Independent Project
CS 399P (Aut, Win, Spr, Sum) - Independent Work
CS 199 (Aut, Win, Spr, Sum) - Independent Work
CS 199P (Aut, Win, Spr, Sum) - Part-time Curricular Practical Training
CS 390D (Aut) - Ph.D. Research
CME 400 (Aut, Win, Spr, Sum) - Senior Project
CS 191 (Aut, Win, Spr) - Supervised Undergraduate Research
CS 195 (Aut, Win, Spr, Sum) - Writing Intensive Senior Research Project
CS 191W (Aut, Win, Spr)
- Advanced Reading and Research
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Prior Year Courses
2024-25 Courses
- Beyond Worst-Case Analysis
CS 264, MS&E 215 (Spr) - Introduction to Probability
MS&E 120 (Aut)
2023-24 Courses
- Introduction to Probability
MS&E 120 (Aut) - Machine Learning for Discrete Optimization
CS 225, MS&E 236 (Spr)
2022-23 Courses
- Introduction to Probability
MS&E 120 (Aut) - Machine Learning for Algorithm Design
CS 331, MS&E 331 (Spr)
- Beyond Worst-Case Analysis
Stanford Advisees
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Doctoral Dissertation Reader (AC)
Samuel Akinwande, Shaun Datta -
Postdoctoral Faculty Sponsor
Nico Christianson, Connor Lawless, Xizhi Tan -
Doctoral Dissertation Advisor (AC)
Yingxi Li, Anders Wikum -
Master's Program Advisor
Kieran Barrett, Nikita Bhardwaj, Megha Bindiganavale, Pranshu Chaturvedi, David Chen, Ian Chen, Kevin Chen, Sohan Chunduru, Ethan Harianto, Jason Hu, Connor Huang Marsh, Viraj Jayam, Charles Joyner, Dilnaz Kamalova, Shreyas Kar, Chengnan Li, Wanning Lu, Auddithio Nag, Deonna Owens, Kun Peng, Ron Polonsky, Ryan Tan, Claire Tang, Aditi Tuli, Artemis Veizi -
Doctoral Dissertation Co-Advisor (AC)
Mika Jain, Ishani Karmarkar, Nikil Selvam -
Doctoral (Program)
Yu He, Senem Isik
All Publications
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LLMs for Cold-Start Cutting Plane Separator Configuration
edited by Tack, G.
SPRINGER INTERNATIONAL PUBLISHING AG. 2025: 51-69
View details for DOI 10.1007/978-3-031-95976-9_4
View details for Web of Science ID 001547302000004
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New Sequence-Independent Lifting Techniques for Cover Inequalities and When They Induce Facets
edited by Kwok, J.
IJCAI-INT JOINT CONF ARTIF INTELL. 2025: 2675-2683
View details for Web of Science ID 001595146400298
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How Much Data Is Sufficient to Learn High-Performing Algorithms?
JOURNAL OF THE ACM
2024; 71 (5)
View details for DOI 10.1145/3676278
View details for Web of Science ID 001366880900006
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Leveraging Reviews: Learning to Price with Buyer and Seller Uncertainty
ACM SIGECOM EXCHANGES
2024; 22 (1): 74-82
View details for Web of Science ID 001349692800003
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Learning to Branch: Generalization Guarantees and Limits of Data-Independent Discretization
JOURNAL OF THE ACM
2024; 71 (2)
View details for DOI 10.1145/3637840
View details for Web of Science ID 001208839800001
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Generalization Guarantees for Multi-Item Profit Maximization: Pricing, Auctions, and Randomized Mechanisms
OPERATIONS RESEARCH
2023
View details for DOI 10.1287/opre.2021.0026
View details for Web of Science ID 001125732800001
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No-Regret Learning in Partially-Informed Auctions
JMLR-JOURNAL MACHINE LEARNING RESEARCH. 2022
View details for Web of Science ID 000922378803003