About Me 👋

Hello! I'm Amber (Jiachen) Liu, a fifth-year Ph.D. candidate in Computer Science at the University of Michigan (Umich), where I'm fortunate to work under the guidance of Prof. Mosharaf Chowdhury. My academic journey has been enriched by wonderful collaborations with Prof. Sam Madden and Prof. Lei Cao at MIT, as well as Prof. Siqian Shen at Umich.

As an optimist and strong advocate of AGI, my research tries to build efficient systems that enable researchers to push the boundary of machine learning, particularly in Federated Learning (FL) and Large Language Models (LLMs). Currently, I'm exploring two exciting frontiers: enhancing the Quality-of-Experience (QoE) in LLM serving systems and developing infrastructure for extremely large-scale LLM training.

To contribute to the research community, I maintain comprehensive paper collections on FL Systems and LLM Systems. I also serve as a Teaching Assistant for Systems for Generative AI at Michigan, where I've developed educational materials on LLM Systems Fundamentals, LLM Fine-tuning, and Vector Databases.

I'm always eager to engage in meaningful discussions about research and explore potential academic collaborations. Feel free to reach out via email or schedule a meeting to connect!

Publications 📃

• Curie: Toward Rigorous and Automated Scientific Experimentation with AI Agents, Arxiv 2025.
  Patrick Tser Jern Kon*, Jiachen Liu*, Qiuyi Ding, Yiming Qiu, Zhenning Yang, Yibo Huang, Jayanth Srinivasa, Myungjin Lee, Mosharaf Chowdhury, Ang Chen (* Equal contribution).
  GitHub Paper Blog & Demo

• IaC-Eval: A code generation benchmark for Infrastructure-as-Code programs, NeurIPS 2024.
  Patrick Tser Jern Kon, Jiachen Liu, Yiming Qiu, Weijun Fan, Ting He, Lei Lin, Haoran Zhang, Owen M. Park, George Sajan Elengikal, Yuxin Kang, Ang Chen, Mosharaf Chowdhury, Myungjin Lee, Xinyu Wang
  GitHub Paper

• Andes: Defining and Enhancing Quality-of-Experience in LLM-Based Text Streaming Services, Arxiv 2024.
  Jiachen Liu, Zhiyu Wu, Jae-Won Chung, Fan Lai, Myungjin Lee, Mosharaf Chowdhury
  Blog Paper

• Venn: Resource Management Across Federated Learning Jobs, MLSys 2025.
  Jiachen Liu, Fan Lai, Ding Ding, Yiwen Zhang, Mosharaf Chowdhury.
  Paper

• Efficient Large Language Models: A Survey, TMLR 2024.
  Zhongwei Wan, Xin Wang, Che Liu, Samiul Alam, Yu Zheng, Jiachen Liu, Zhongnan Qu, Shen Yan, Yi Zhu, Quanlu Zhang, Mosharaf Chowdhury, Mi Zhang.
  Paper GitHub

• FedTrans: Efficient Federated Learning via Multi-Model Transformation, MLSys 2024.
  Yuxuan Zhu, Jiachen Liu, Mosharaf Chowdhury, Fan Lai
  Paper

• Auxo: Efficient Federated Learning via Scalable Cohort Identification, SoCC 2023.
  Jiachen Liu, Fan Lai, Yinwei Dai, Aditya Akella, Harsha Madhyastha, Mosharaf Chowdhury.
  GitHub Paper

• FedScale: Benchmarking Model and System Performance of Federated Learning at Scale, ICML 2022
  Fan Lai, Yinwei Dai, Sanjay S. Singapuram, Jiachen Liu, Xiangfeng Zhu, Harsha V. Madhyastha, Mosharaf Chowdhury.
  GitHub Paper

• Fluid: Resource-Aware Hyperparameter Tuning Engine, MLSys 2021
  Peifeng Yu*, Jiachen Liu*, Mosharaf Chowdhury (* Equal contribution).
  GitHub Paper Video

• Machine Learning and Systems Rising Stars 🌟 (Program of 2023)
• Shanghai (China) Outstanding Graduate 🎓 (Top 5%) 2020