About me

I'm a 5th year PhD student in Operations Research and Information Engineering at Cornell University. I'm fortunate to be advised by Ziv Scully and closely working with Peter Frazier and Alexander Terenin. I work at the intersection of probabilistic machine learning and operations research, with a focus on decision-making under uncertainty. My research explores data-driven approaches for optimal information acquisition and learning, including Bayesian optimization, Bayesian experiment design, LLM-as-agent, and reinforcement learning, informed by theoretical insights from Gittins index theory (e.g., Pandora's box problem, Markovian bandits) and applied probability (e.g., dynamic programming, MDPs). I obtained my MS degree from NYU, under the supervision of Li Jin, focusing on queuing control for network systems. Prior to that, I earned a B.Eng. degree in computer science from Yao Class, Institute of Interdisciplinary Information Sciences at Tsinghua University.

I'm on the 2025–2026 academic job market, open to tenure-track faculty, research faculty, postdoctoral, and research scientist positions. Please feel free to reach out if you’d like to discuss my work or potential opportunities.

Education

Cornell University
PhD in Operations Research
2021 - 2026 (expected)

New York University
MS in Transporation
2019 - 2021

Tsinghua University
B.Eng. in Computer Science
2015 - 2019

News

[2025/12/07] I'm going to present a poster at the NeurIPS 2025 LAW Workshop.

[2025/10/27] I'm going to give a talk at the INFORMS Annual Meeting 2025 Job Market Showcase Dynamic Programming and Reinforcement Learning Session.

[2025/09/09] I'm going to give a 2-min pitch and present two posters at AutoML poster sessions.

[2025/07/10] I'm going to present a poster with Linda Cai at EC workshop.

Publications and preprints

(*: Equal contribution, †: Project lead / Corresponding author)

Data-driven Sequential Decision-making Under Uncertainty

LLM-Driven Composite Neural Architecture Search for Multi-Source RL State Encoding.
Yu Yu, Qian Xie†, Li Jin.
Preliminary version accepted by NeurIPS 2025 Workshop on Bridging Language, Agent, and World Models for Reasoning and Planning (LAW).
[Paper] [Presentation]

Cost-aware Stopping for Bayesian Optimization.
Qian Xie*†, Linda Cai*, Alexander Terenin, Peter I. Frazier, Ziv Scully.
Under review.
Preliminary version accepted by AutoML 2025 Non-archival Track.
[Paper] [Presentation] [Poster @EC workshop] [Poster @AutoML] [Code]

Cost-aware Bayesian optimization via the Pandora’s box Gittins index.
Qian Xie, Raul Astudillo, Peter I. Frazier, Ziv Scully, Alexander Terenin.
Advances in Neural Information Processing Systems (NeurIPS 2024).
Finalist of 2024 INFORMS Annual Meeting Data Mining Society Best Paper Competition (General Track).
[Paper] [Presentation] [Poster] [Code] [Page] [5-min Video @NeurIPS] [45-min Talk @BDU-seminar]

Smooth Non-Stationary Bandits.
Su Jia, Qian Xie, Nathan Kallus, Peter I. Frazier.
International Conference on Machine Learning (ICML 2023).
Major revision in Operations Research.
[Paper] [Presentation] [Code]

Stochastic Control

Cost-aware Defense for Parallel Server Systems against Reliability and Security Failures.
Qian Xie, Jiayi Wang, Li Jin.
Automatica (2024).
[Paper] [Presentation] [Poster]

Stabilizing Queuing Networks with Model Data-Independent Control.
Qian Xie, Li Jin.
IEEE Transactions on Control of Network Systems (2022).
[Paper] [Presentation]

Minimax Least-Square Policy Iteration for Cost-Aware Defense of Traffic Routing against Unknown Threats.
Yuzhen Zhan, Yule Zhang, Qian Xie, Li Jin.
Chinese Control Conference (CCC 2025).

Resilience of Dynamic Routing in the Face of Recurrent and Random Sensing Faults.
Qian Xie, Li Jin.
American Control Conference (ACC 2020).
[Paper] [Presentation]

Miscellaneous

Subspace GRPO: Scalable Outcome-Based Reinforcement Learning for Rectangle Packing.
Qinbo Bai, Qian Xie, Ning Yan, Masood S. Mortazavi
Under review.

LLMs Fail to Recognize Mathematical Unsolvability.
Huaibo Chen, Yixiao Lin, Pengcheng Chen, Nuohao Liu, Zihan Zhao, Yue Hu, Qian Xie, Qinbo Bai, Masood S. Mortazavi, Ning Yan, KAMAL YOUCEF-TOUMI
Preliminary version accepted by AAAI 2026 Workshop of Deployable AI (DAI).

Empirical Validation of Network Learning with Taxi GPS Data from Wuhan, China.
Susan Jia Xu, Qian Xie, Joseph Y.J. Chow, Xintao Liu.
IEEE Intelligent Transportation Systems Magazine.
[Paper] [Presentation] [Poster] [Code]

Student cluster competition 2017, team Tsinghua University: Reproducing vectorization of the tersoff multi-body potential on the Intel Skylake and NVIDIA Volta architectures.
Ka Cheong Jason Lau, Yuxuan Li, Lei Xie, Qian Xie, Beichen Li, Yu Chen, Guanyu Feng, Jiping Yu, Xinjian Yu, Miao Wang, Wentao Han, Jidong Zhai.
Parallel Computing.

A Game-based Data Collecting Framework for the Recommendation of Kids Second Language Learning.
Weizhi Ma, Min Zhang, Chenyu Zhang, Yixin Chen, Qian Xie, Weiyue Sun, Yiqun Liu, Shaoping Ma.
International Workshop on Children & Recommender Systems (KidRec 2017).
Chinese National Conference on Computational Linguistics (CCL 2017).
[Paper] [Poster]

Master's thesis

Robust and Secure Feedback Control For Queuing Networks. [Presentation]

Teaching (TA) experience

[Head TA] ORIE 3510/5510 & STSCI 3510 Introduction to Engineering Stochastic Processes I (Instructor: Ziv Scully, Spring 2024)

ORIE 3120 Practical Tools for Operations Research, Machine Learning and Data Science (Instructor: Peter I. Frazier, Spring 2023)

ENGRD 2700 Basic Engineering Probability and Statistics (Instructor: Jamol Pender, Fall 2022)

ORIE 5582 Monte Carlo Methods in Financial Engineering (Instructor: Sid Banerjee, Spring 2022)

ORIE 3510/5510 & STSCI 3510 Introduction to Engineering Stochastic Process I (Instructor: Jim Dai, Spring 2025, 2022)

Internship experience

Research scientist intern @Amazon Web Services (AWS) (Summer 2021)

Service

Reviewer of ICLR 2026, NeurIPS 2025 workshop MATH-AI, NeurIPS 2025, AISTATS 2025, NeurIPS 2024 Workshop BDU, NeurIPS 2024, AISTATS 2024, SIAM SIMODS, Transportation Science, The IEEE Transactions on Control of Network Systems (TCNS)

Online talks organizer (直播部部长) @ORAI China (运筹OR帷幄)

Women in ORIE Officer and Activity Planner @Cornell University ORGA (Operations Research Graduate Association)

Selected awards

AISTATS Best Reviewer Award, 2025

INFORMS Annual Meeting Data Mining Society Best Paper Competition (General Track) finalist, 2024

ACM STOC TCS for All student travel award, 2023

ACM SIGMETRICS student travel award, 2023

Cornell University McMullen Fellowship, 2021

ACC student travel award, 2020

Silver medal in China Mathematical Olympiad (CMO), 2014

Gold medal (rank 6) in China Girls Mathematical Olympiad (CGMO), 2014

First prize (rank 9 in Guangdong Province) in China Mathematical Olympiad in Senior, 2011, 2013

Mischallenous

My hobbies include table tennis, traveling, and blogging. As a penholder, I won first places in the 2023 and the 2024 Cornell ORIE Table Tennis Tournament and the third place in the 2022 Cornell CSSA Women's Table Tennis Tournament! I am also a foodie. Feel free to ask me for recommendations on restaurants and attractions in the places I have been to!