About Me
I am a Machine Learning Engineer at the Tesla Optimus Team. I received my PhD in Computer Science at the University of Illinois Urbana-Champaign, advised by Prof. Indranil Gupta. My interests are primarily in Machine Learning Systems, Machine Learning, and Robotics. I have worked with IBM Research, Nokia Bell Labs, and Google in the US, and Somansa in South Korea. I obtained a B.S. degree in Computer Science and Engineering from Seoul National University.
Work Experiences
Education
Research Experiences
Publications
- Beomyeol Jeon, Yongjoo Park, Indranil Gupta. Automating Resource Allocation for Graph Neural Network Training on Serverless Frameworks. Currently Under Preparation, 2024.
- Beomyeol Jeon, Machine learning systems in constrained environments. PhD Dissertation, University of Illinois Urbana-Champaign, 2024. [link]
- Beomyeol Jeon, Chen Wang, Diana Arroyo, Alaa Youssef, Indranil Gupta. A House United Within Itself: SLO-Awareness for On-Premises Containerized ML Inference Clusters via Faro. The 20th European Conference on Computer Systems (EuroSys 2025), March 2025 [arXiv, code].
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Beomyeol Jeon*, S M Ferdous*, Muntasir Raihan Rahman, Anwar Walid.
Privacy-preserving Decentralized Aggregation for Federated Learning.
The 1st International Workshop on Distributed Machine Learning and Fog Network (FOGML 2021) (co-located with INFOCOM 2021), May 2021 [link, extended version].
*: equal contributions - Beomyeol Jeon, Linda Cai, Pallavi Srivastava, Jintao Jiang, Xiaolan Ke, Yitao Meng, Cong Xie, Indranil Gupta. Baechi: Fast Device Placement of Machine Learning Graphs. ACM Symposium on Cloud Computing 2020 (SoCC 2020), October 2020 [link, extended version].
- Woo-Yeon Lee, Yunseong Lee, Joo Seong Jeong, Gyeong-In Yu, Joo Yeon Kim, Ho Jin Park, Beomyeol Jeon, Wonwook Song, Gunhee Kim, Markus Weimer, Brian Cho, Byung-Gon Chun. Automating System Configuration of Distributed Machine Learning. The 39th International Conference on Distributed Computing Systems (ICDCS 2019), July 2019 [link].
- Byung-Gon Chun, Tyson Condie, Yingda Chen, Brian Cho, Andrew Chung, Carlo Curino, Chris Douglas, Matteo Interlandi, Beomyeol Jeon, Joo Seong Jeong, Gye-Won Lee, Yunseong Lee, Tony Majestro, Dahlia Malkhi, Sergiy Matusevych, Brandon Myers, Mariia Mykhailova, Shravan Narayanamurthy, Joseph Noor, Raghu Ramakrishnan, Sriram Rao, Russell Sears, Beysim Sezgin, Tae-Geon Um, Julia Wang, Markus Weimer, Youngseok Yang. Apache REEF: Retainable Evaluator Execution Framework. ACM Transactions on Computer Systems (TOCS), Volumne 35 Issue 2, October 2017 [link].
- Byung-Gon Chun, Brian Cho, Beomyeol Jeon, Joo Seong Jeong, Gunhee Kim, Joo Yeon Kim, Woo-Yeon Lee, Yun Seong Lee, Markus Weimer, Gyeong-In Yu. Dolphin: Runtime Optimization for Distributed Machine Learning. ICML ML Sys ’16 workshop, June 2016 [link]
Awards & Honors
Academic Services
Program Committee ACM/IFIP Middleware 2025, SYSTOR 2025
Reviewer IEEE TCC 2019, IEEE TC 2021
Subreviewer IEEE ISSRE 2019