Tianyi Peng

Tianyi Peng 

Tianyi Peng
Assistant Professor at Columbia University
Decision, Risk, and Operations Division
Data Science Institute
Email: tianyi.peng [at] columbia [dot] edu
[CV] [GitHub] [linkedin]

About Me

I am broadly interested in AI for decision-making and envision a future where AI agents coexist with humans to enable complex task automation and decision support. My research themes include:

  • Ensuring the safe and reliable deployment of AI agents in real-world applications, with continuous alignment and adaptation to business and societal objectives.

  • Reducing the operational costs of AI systems to enable scalable, low-latency deployment across diverse environments.

  • Leveraging AI to simulate human and system behavior (known as “digital twin”), enabling cost-effective, scalable experimentation and testing.

  • Optimizing large-scale decision-making systems through AI and reinforcement learning.

I am a founding member of Cimulate.AI, developing Customer-GPT for e-commerce. We are hiring!

I've collaborated with organizations like Anheuser-Busch InBev, TikTok, and Liberty Mutual. My work with Anheuser-Busch InBev on developing an innovative experimentation platform earned the Daniel H. Wagner Prize in 2022 (INFORMS news). My research has also received the APS Best Student Paper Prize and RMP Jeff McGill Student Paper Award.

I hold a Ph.D. from MIT and a Bachelor's in Computer Science from Tsinghua University (Yao Class).

Publications

  • ADSO: Adaptive Data Mixture & Scale Optimization. A Multi-Scale Multi-Fidelity Bayesian Optimization Approach
    Tzu-Ching Yen, Andrew Wei Tung Siah, Haozhe Chen, C. Daniel Guetta, Tianyi Peng, Hongseok Namkoong

  • LLM Generated Persona is a Promise with a Catch
    Ang Li, Haozhe Chen, Hongseok Namkoong, Tianyi Peng

  • Markovian Interference in Experiments
    With Vivek F. Farias, Andrew A. Li, and Andrew Zheng
    Under review in Management Science

    • Winner, Applied Probability Socity (APS) Best Student Paper Prize 2022

    • Winner, Jeff McGill Student Paper Award 2022

    • NeurIPS 2022, Oral (~2%), [Video in Chinese]

  • The Limits to Learning a Diffusion Model
    With Jackie Baek, Vivek F. Farias, Andreea Georgescu, Retsef Levi, Deeksha Sinha, Joshua Wilde, and Andrew Zheng
    Accepted by Management Science

    • Finalist, Post-Pandemic Supply Chain and Healthcare Management Best Paper

    • EC 2021

Publications in Quantum (A previous life..)

  • Quantum Queuing Delay
    Wenhan Dai, Tianyi Peng, Moe Win
    IEEE Journal on Selected Areas in Communications (IEEE-JSAC), vol. 38, no. 3, pp. 605-618, 2020
    [link], [pdf]

    • Preliminary version: Queuing Delay for Quantum Networks
      International Conference on Computing, Networking and Communications (ICNC 2020)

  • Optimal Remote Entanglement Distribution
    Wenhan Dai, Tianyi Peng, Moe Win
    IEEE Journal on Selected Areas in Communications (IEEE-JSAC), vol. 38, no. 3, pp. 540-556, 2020
    [link], [pdf]

    • Preliminary version: Optimal Protocols for Entanglement Swapping and Distribution
      Best Paper Award, International Conference on Computing, Networking and Communications (ICNC 2020)

  • Simulating Large Quantum Circuits on a Small Quantum Computer
    Tianyi Peng, Maris Ozols, Aram Harrow, Xiaodi Wu
    Physical Review Letters 125, 150504 (2020) (PRL)
    [link] [arxiv]

  • Efficient and Robust Physical Layer Key Generation
    Tianyi Peng, Wenhan Dai, Moe Win
    Military Communications Conference 2019 (MILCOM 2019)
    [link]

  • Remote State Preparation for Multiple Parties
    Wenhan Dai, Tianyi Peng, Moe Win
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2019), Invited Paper
    [pdf], [link]

  • Quantum Uncertainty Relation of Coherence
    Xiao Yuan, Ge Bai, Tianyi Peng, Xiongfeng Ma
    Physical Review A 96 (3), 032313 (2017)
    [link] [arxiv]

  • Tight Detection Efficiency Bounds of Bell Tests In No-signaling Theories
    Zhu Cao, Tianyi Peng (co-first author)
    Physical Review A 94, 042126 (2016)
    [link] [arxiv]