Hello! I am now an Applied Scientist in Amazon Rufus (Palo Alto, US).

I got a Ph.D. from School of Information, University of Michigan, advised by Prof. VG Vinod Vydiswaran. I also worked with Prof. Qiaozhu Mei between 2015-2020, and Prof. Daniel M. Romero between 2018-2020.

Prior to UM, I received my honored bachelor degree in Computer Science from Chu Kochen Honors College, Zhejiang University in 2017. During my undergraduate period, I was supervised by Prof. Fei Wu.

I primarily working on Natural Language Processing and Machine Learning. My recent research focuses on below topics:

• LLM Pre-Training.

• LLM Post-Training (Instruction Fine-tuning & RLHF).

• LLM Reasoning & Thinking.

• Self-Supervised Representation Learning (e.g., contrastive learning).

• Robustness of ML models (backdoor attack and defense of LLMs).

• Diffusion Models for Non-Autoregressive Generation.

News

[May 2025] Our paper UniConv: Unifying Retrieval and Response Generation for Large Language Model in Conversation is accepted by ACL 2025.

[Sep 2024] Our paper Divide-or-Conquer? Which Part Should You Distill Your LLM? is accepted by EMNLP 2024.

[May 2024] Joined the Amazon Rufus team.

[May 2024] Got married and hosted our wedding!

[Apr 2024] Defended my thesis and left Ann Arbor, a city where I lived for over 8 years.

[Feb 2024] Our paper Divide-or-Conquer? Which Part Should You Distill Your LLM? is now available for public access.

[Oct 2023] Our paper HiCL: Hierarchical Contrastive Learning of Unsupervised Sentence Embeddings is accepted by EMNLP 2023.

[Sep 2023] Our paper PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model is accepted by NeurIPS 2023.

[Aug 2023] Finished my internship at Machine Learning Research at Apple.