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.

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 Private Machine Learning and Large Language Models (LLMs). Currently, I'm exploring two exciting frontiers: enhancing the Quality-of-Experience (QoE) in LLM serving systems and developing systems for extremely large-scale LLM training.

To contribute to the research community, I maintain comprehensive paper collections on Private Machine Learning 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!

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.

Publications 📃

• User-Centric Machine Learning Systems, PhD Dissertation 2025.
  Jiachen Liu
  Paper Blog

• EXP-Bench: Can AI Conduct AI Research Experiments?, Arxiv 2025.
  Patrick Tser Jern Kon*, Jiachen Liu*, Xinyi Zhu, Qiuyi Ding, Jingjia Peng, Jiarong Xing, Yibo Huang, Yiming Qiu, Jayanth Srinivasa, Myungjin Lee, Mosharaf Chowdhury, Matei Zaharia, Ang Chen (* Equal contribution).
  Paper Blog Dataset

• The ML.ENERGY Benchmark: Toward Automated Inference Energy Measurement and Optimization, Arxiv 2025.
  Jae-Won Chung, Jiachen Liu, Jeff Ma, Ruofan Wu, Oh Jun Kweon, Yuxuan Xia, Zhiyu Wu, Mosharaf Chowdhury
  Demo Paper

• 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

• Evaluation Framework for AI Systems in "the Wild", Arxiv 2025.
  Sarah Jabbour, Trenton Chang, Anindya Das Antar, Joseph Peper, Insu Jang, Jiachen Liu, Jae-Won Chung, Shiqi He, Michael Wellman, Bryan Goodman, Elizabeth Bondi-Kelly, Kevin Samy, Rada Mihalcea, Mosharaf Chowdhury, David Jurgens, Lu Wang
  Paper

• 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 for Collaborative 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