Stephan Xie

Hi! I’m Stephan, a third-year PhD student in the Machine Learning Department at Carnegie Mellon University advised by Ameet Talwalkar, and supported by the NSF GRFP. I also collaborate with Datadog AI Research on multimodal modeling and reinforcement learning.

I’m broadly interested in topics including reinforcement learning, reliable decision-making, and the translational impact of AI.

Previously, I did my undergrad at the University of Pennsylvania School of Engineering and Applied Sciences studying Computer Science and Mathematical Economics. At Penn I was fortunate to work with Aaron Roth on calibration and learning theory, Kevin He on social learning, as well as Yi Xing and Robert Wang at the Xing Lab on computational biology.

This semester I am running the CMU RL and Agents Seminar. Please reach out if you would like to give a talk!

Publications

ARFBench: Benchmarking Multimodal Time Series Reasoning for Software Incident Response

International Conference on Learning Representations (ICLR) Workshop on Time Series in the Age of Large Models (TSALM), 2026 · [Datadog AI Blog Post]· [MLD Blog Post]

Spotlight Presentation

Stephan Xie, Ben Cohen, Mononito Goswami, Junhong Shen, Emaad Khwaja, Chenghao Liu, David Asker, Othmane Abou-Amal, Ameet Talwalkar

This Time is Different: An Observability Perspective on Time Series Foundation Models

Neural Information Processing Systems (NeurIPS), 2025 · [Blog Post]

Ben Cohen, Emaad Khwaja, Youssef Doubli, Salahidine Lemaachi, Chris Lettieri, Charles Masson, Hugo Miccinilli, Elise Ramé, Qiqi Ren, Afshin Rostamizadeh, Jean Ogier du Terrail, Anna-Monica Toon, Kan Wang, Stephan Xie, Zongzhe Xu, Viktoriya Zhukova, David Asker, Ameet Talwalkar, Othmane Abou-Amal

High-Dimensional Prediction for Sequential Decision Making

International Conference on Machine Learning (ICML), 2025 · [Blog Post]

Oral Presentation

Georgy Noarov, Ramya Ramalingam, Aaron Roth, Stephan Xie

ESPRESSO: Robust discovery and quantification of transcript isoforms from error-prone long-read RNA-seq data

Science Advances, 2023

Yuan Gao, Feng Wang, Robert Wang, Eric Kutschera, Yang Xu, Stephan Xie, Yuanyuan Wang, Kathryn E. Kadash-Edmondson, Lan Lin, Yi Xing

Teaching

I’ve been a teaching assistant for the following classes: