PeopleofSuperintelligence

Researcher

Rujun Jiang

Also known as 江如俊

Rujun Jiang is an optimization researcher at Fudan University whose paper on the Stackelberg prediction game received an ICML Outstanding Paper Award in 2022. He earned a bachelor's degree in mathematics from the University of Science and Technology of China in 2012 and a PhD from The Chinese University of Hong Kong in 2016, then joined Fudan in 2017. With Jiali Wang, Xudong Li and others, he coauthored ICML papers in 2021 and 2022 that made a game between a learner and an attacker solvable orders of magnitude faster. Later papers covered simple bilevel optimization at NeurIPS in 2024, spectral risk minimization at ICLR in 2025 and adaptive Riemannian bilevel optimization at NeurIPS in 2025. He is a professor at Fudan's School of Data Science and an area chair for ICML and NeurIPS.

Timeline

  1. 2012–2016

    Mathematics degree and CUHK PhD

    He earns a bachelor's degree in mathematics from the University of Science and Technology of China in 2012. He receives a PhD from The Chinese University of Hong Kong in 2016.

  2. 2017

    Joining Fudan University

    After a year as a postdoctoral fellow at CUHK, he joins Fudan University in 2017. His research covers optimization and its applications in machine learning and financial engineering.

  3. 2021

    Faster Stackelberg prediction games

    In 2021, he coauthors an ICML paper with Jiali Wang, He Chen, Xudong Li and Zihao Li on the Stackelberg prediction game with least squares loss, a model of the interaction between a learner and a data provider. Their second order cone program reformulation runs up to 20,000+ times faster than the state of the art in numerical results on synthetic and real world datasets.

  4. 2022

    An ICML Outstanding Paper

    In 2022, he coauthors an ICML paper with Jiali Wang, Wen Huang, Xudong Li and Alex L. Wang that rewrites the Stackelberg prediction game with least squares loss as a spherically constrained least squares problem. The paper receives one of ten ICML 2022 Outstanding Paper Awards, and its numerical results show the problem solved orders of magnitude faster than the state of the art.

  5. 2024

    Penalty methods for bilevel problems

    In 2024, he coauthors a NeurIPS paper with Pengyu Chen, Xu Shi and Jiulin Wang on simple bilevel optimization, which minimizes an upper-level objective over the optimal solution set of a convex lower-level objective. The paper proposes a penalization framework for problems under Hölderian error bounds.

  6. 2025

    SOREL and adaptive bilevel methods

    In 2025, he and Yuze Ge publish SOREL at ICLR, the first stochastic gradient-based algorithm with convergence guarantees for spectral risks minimization. At NeurIPS 2025, he, Xu Shi and Rufeng Xiao publish AdaRHD, a fully adaptive step size method for Riemannian bilevel optimization.

  7. As of October 2026

    Professor at Fudan

    He is a professor at Fudan University's School of Data Science, where the courses he teaches include Optimization Theory and Methods and Numerical Optimization. He is an area chair for ICML in 2025 and 2026 and for NeurIPS in 2024 and 2025.

Career

  1. NowFudan UniversityProfessor
  2. Until 2017Chinese University of Hong KongPostdoctoral Fellow

Education

  1. 2016Chinese University of Hong KongPhD
  2. 2012University of Science and Technology of ChinaBachelor's degree in Mathematics

From the biography.

  1. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Rujun Jiang. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  2. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Fudan University. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  3. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes Fudan University. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  4. Universities keep AI researchers for a median of 6 years, compared with 2 years at frontier labsIncludes Chinese University of Hong Kong. Across 15,811 dated work stays (6,529 people), median role tenure runs from 6 years at universities to 2 years at frontier labs. We compare all five organization types, starting decades from the 1970s to the 2020s, and the organizations that keep people longest.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Rujun Jiang yet. Send us a free-licensed photo.

  1. Rujun Jiang rjjiang.github.io. Checked 22 October 2026.
  2. Fast Algorithms for Stackelberg Prediction Game with Least Squares Loss proceedings.mlr.press. Checked 22 October 2026.
  3. Solving Stackelberg Prediction Game with Least Squares Loss via Spherically Constrained Least Squares Reformulation proceedings.mlr.press. Checked 22 October 2026.
  4. ICML 2022 Awards icml.cc. Checked 22 October 2026.
  5. Congratulations to the #ICML2022 outstanding paper award winners aihub.org. Checked 22 October 2026.
  6. Penalty-based Methods for Simple Bilevel Optimization under Hölderian Error Bounds arxiv.org. Checked 22 October 2026.
  7. SOREL: A Stochastic Algorithm for Spectral Risks Minimization proceedings.iclr.cc. Checked 22 October 2026.
  8. An Adaptive Algorithm for Bilevel Optimization on Riemannian Manifolds papers.nips.cc. Checked 22 October 2026.