Bowen Yu 余博文 IPA: [y˧˥ po˧˥ wən˧˥]

Senior undergrad, MIT Physics & AI

I'm an undergraduate at MIT (Class of 2027), double-majoring in Physics (Course 8) and Artificial Intelligence (Course 6-4). Before MIT I spent a year studying physics at Peking University.

My research interests center around building intelligent systems that can efficiently learn and adapt in complex environments. I'm currently working with Prof. Yilun Du at the Embodied Minds Lab on the dynamics of multi-agent systems, supervised by Zhenting Qi. Previously, I worked with Prof. Mingda Li at the MIT Quantum Measurement Group on machine learning for condensed matter physics, materials discovery, and defect engineering, supervised by Mouyang Cheng.

Outside the lab, I enjoy long-distance running, classic films, linguistics (including learning all sorts of languages; I'm currently studying Japanese, Spanish and Cantonese!), rhythm games (Phigros, CHUNITHM), philosophy, vibe-coding projects, and Liu Cixin's novels.

Bowen Yu

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  1. DefectNet workflow demonstration

    A Foundation Model for Non-Destructive Defect Identification from Vibrational Spectra

    Mouyang Cheng†,*, Chu-Liang Fu†, Bowen Yu†, Eunbi Rha, Abhijatmedhi Chotrattanapituk, Douglas L. Abernathy, Yongqiang Cheng, and Mingda Li*

    † Equal contribution. * Corresponding author.

    Matter Published Mar 2026 · arXiv May 2025

    A non-destructive defect identification probe to predict the chemical identity and concentration of substitutional point defects directly from vibrational spectra

  2. Integrated workflow for XPCS, theory, and domain-adaptive machine learning in grain-boundary dynamics

    Probing Non-Equilibrium Grain Boundary Dynamics with XPCS and Domain-Adaptive Machine Learning

    Mouyang Cheng†,*, Bowen Yu†, Chu-Liang Fu, Nina Andrejevic, Matthias T. Agne, Riley Hanus, Qiwei Wan, Nathan C. Drucker, Thanh Nguyen, Andrei Fluerasu, Lutz Wiegart, Xiaoqian M Chen, Daniel Pajerowski, Yongqiang Cheng, Joshua J Turner, G. Jeffrey Snyder, and Mingda Li*

    † Equal contribution. * Corresponding author.

    In review arXiv May 2026

    Pairing X-ray photon correlation spectroscopy (XPCS) with semi-supervised domain adaptation to quantify slow, non-equilibrium grain-boundary dynamics in nanocrystalline silicon

  1. Jun 2026 — Aug 2026

    Miami, FL

    Citadel Securities

    Quantitative Research Analyst

    Systematic alpha research on equity factor return prediction with ML models.

  2. Aug 2025 — Sep 2025

    Beijing, China

    ByteDance

    Large Language Model Data Researcher

    Built a 500+ problem physics benchmark, identify the perception/reasoning badcases for frontier LLM within physics context, and a test-time scaling pipeline that achieved gold medal performance in IPhO 2025.

  3. Jun 2025 — Jul 2025

    Shanghai, China

    Intel Corporation

    AI Workload Deployment Intern

    Developed GPU memory-layout tutorials and CuTeDSL performance references for AI workloads.

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