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Tuorui "v1ncent19" Peng

En voyage dans l'espace de Hilbert.

经历

学术履历的网页版。正式且最新的 CV 请以 PDF 为准——如需完整论文/引用列表欢迎来信索取。

下载 CV(PDF)PDF · 133 KB
资料
@v1ncent19

Tuorui Peng

统计学博士生

  • 现在统计学博士生 — Northwestern University
  • 来自Shenzhen, Guangdong, China
  • RouteSZSHS · 2013 → Tsinghua · 2019 → Northwestern · 2023

研究兴趣

重尾与形状约束下的统计理论——高维中的稳健、极小极大与无分布方法。

  • Robust statistics
  • Heavy-tailed minimax theory
  • High-dimensional statistical inference
  • Distribution-free & conformal inference
  • Statistical learning theory

关于

个人介绍与一些 fun facts。

教育

SECT · 01
Sep 2023 — Present

Ph.D. in Statistics

Northwestern University

Department of Statistics and Data Science. Advisor: Prof. Matey Neykov.

Sep 2023 – Jun 2025

M.S. in Statistics

Northwestern University

Department of Statistics and Data Science.

Sep 2019 – Jun 2023

B.S. in Mathematics and Physics

Tsinghua University

Department of Physics.

Mar 2021 – Jun 2023

B.S. (minor) in Statistics

Tsinghua University

Department of Industrial Engineering.

研究经历

SECT · 02
  • Graduate Researcher

    Jan 2025 — Present

    Northwestern University

    • Project: Robust inference under shape constraints with heavy-tailed noise.
    • Formulated a novel framework for robust mean estimation under star-shaped constraints, explicitly addressing non-Gaussian and heavy-tailed noise structures.
    • Derived optimal minimax error bounds and established theoretical guarantees for estimators under non-convex and non-smooth geometric constraints.
    • Presented the findings in a comprehensive research paper.
  • Undergraduate Dissertation

    Dec 2022 – May 2023

    Tsinghua University

    • Project: Distribution-free inference and neural-network modeling for gene expression.
    • Applied Mixture Density Networks (MDN) to model complex, multi-modal conditional distributions for high-dimensional genetic data.
    • Extended the Conformal Prediction framework to construct distribution-free conformal bands for conditional distribution functions.
    • Programmed the entire pipeline in Python, achieving predictive coverage guarantees without relying on strong distributional assumptions.
  • Undergraduate Researcher & RA

    Dec 2021 – Jul 2022

    Tsinghua University

    • Project: Large-scale medical-record dataset.
    • Developed a scalable data pipeline to crawl, parse, and structure case-report articles from PubMed OA.
    • Formed a large-scale public dataset of patient summaries and their links (160k patient summaries, 293k similarity annotations).
    • Fine-tuned large language models (LLMs) to automate text mining and medical entity extraction from unstructured biomedical literature.
    • Published the open-source dataset on Nature Scientific Data.

发表论文

SECT · 03
  1. Robust mean estimation under star-shaped constraints with heavy-tailed noise

    Peng, T., Prasadan, A., & Neykov, M. · arXiv preprint arXiv:2604.05063 · 2026

  2. A large-scale dataset of patient summaries for retrieval-based clinical decision support systems

    Zhao, Z., Jin, Q., Chen, F., Peng, T., & Yu, S. · Scientific Data, 10(1), 909 · 2023

获奖与荣誉

SECT · 04
  • Five-star Zijing Volunteer

    五星级紫荆志愿者 · Tsinghua University Volunteer Association

    2023
  • Honorable Mention — MCM/ICM

    Mathematical Contest in Modeling (COMAP), track A

    2022
  • Ma Yuehan Cup — Shooting

    第64届马约翰杯 · 10 m air rifle 4th & air gun 5th

    2021

笔记与作品

SECT · 05

§学术履历网页版——正式且最新的完整记录以 PDF 为准。