Caleb Ju

  • Program Year: 3
  • Academic Institution: Georgia Institute of Technology
  • Field of Study: Operations Research
  • Academic Advisor: Guanghui (George) Lan
  • Practicum(s):
    National Renewable Energy Laboratory (2022)
  • Degree(s):
    B.S. Mathematics and Computer Science, University of Illinois at Urbana-Champaign, 2020
  • Personal URL:

Summary of Research

I am interested in developing fast and scalable optimization algorithms for challenging problems arising in machine learning and computational science.


- Ji Gao, Abigael Whalen, Caleb Ju, Yongsheng Chen, Guanghui Lan, Zhaohui Tong. Reinforcement Learning-Based Control for Waste Biorefining Processes Under Uncertainty. Submitted, Jul 2023
- Caleb Ju and Guanghui Lan. Dual dynamic programming for stochastic programs over an infinite horizon. arXiv, Mar 2023
- Caleb Ju, Georgios Kotsalis, Guanghui Lan. A model-free first-order method for linear quadratic regulator with ilde{O}(varepsilon^{-1}) sampling complexity. Submitted, Dec 2022
- Caleb Ju, Serif Yesil, Mengyuan Sun, Chandra Chekuri, Edgar Solomonik. Efficient parallel implementation of the multiplicative weight update method for graph-based linear programs. arXiv, Aug 2021
- Yan Li, Caleb Ju, Ethan X. Fang, Tuo Zhao. Implicit regularization of Bregman proximal point algorithm and mirror descent on separable data. arXiv, Aug 2021
- Caleb Ju, Yifan Zhang, and Edgar Solomonik. Communication lower bounds for nested bilinear algorithms. Foundations of Computational Mathematics. Nov 2023 (
- Caleb Ju and Edgar Solomonik. "Derivation and analysis of fast bilinear algorithms for convolution". SIAM Review. Nov 2020 (


- 2023 INFORMS Annual Meeting Best Poster Finalist
- MOPTA 2023 Best Poster Award
- OP21 Travel Award
- Illinois Summer Research Poster: Best Research Presentation Award (Illinois)
- Franz Hohn and J.P. Nash Scholarship (Illinois)
- Dean's List, Fall 2017 (Illinois)