About me

Greetings~~ My name is Amber (Jiachen) Liu, fifth year CS PhD student advised by Prof. Mosharaf Chowdhury. Before, I had a great time working with Prof. Sam Madden and Prof. Lei Cao at MIT and Prof. Siqian Shen at Umich, yay!

As an optimist and strong advocate of AGI, my research tries to build systems that push the boundary of large-scale machine learning for broader use cases: {FL, LLM}. Recently, I am looking into Quality-of-Experience (QoE) for LLM serving systems and extremely large-scale LLM training systems.

I maintain two paper lists for Federated Learning (FL) systems and Large Language Models (LLMs) systems. I served as the TA for Systems for Generative AI at Umich, where I create some tutorial about LLM systems basics, LLM Fine-tuning and Vector Database.

I am open to discussing research ideas and seeking academic collaborations. Drop me email or schedule a meeting if interested.

ML.Energy Leaderboard

The goal of the ML.ENERGY Leaderboard is to give people a sense of how much energy LLMs would consume. Try our Colosseum (online LLM serving) to check the energy consumption of LLM inference.

View Project

FedScale

A scalable and extensible federated learning engine and benchmark.

View Project

Publications

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

• 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.

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

• Venn: Resource Management Across Federated Learning Jobs, Arxiv, 2023.
  Jiachen Liu, Fan Lai, Ding Ding, Yiwen Zhang, Mosharaf Chowdhury.

• 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.

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

• 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

• IaC-Eval: A code generation benchmark for Infrastructure-as-Code programs, NeurIPS Datasets and Benchmarks Track 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