About

I am currently a Research Scientist at Adobe, developing efficient GenAI models with lower serving cost and optimizing deployment on Nvidia, Intel, AMD, and Apple devices. I obtained my PhD from Georgia Tech, advised by Prof. Yingyan (Celine) Lin. My research is dedicated to creating efficient ML systems through algorithm-hardware co-design. This involves addressing the challenge posed by the increasing complexity of advanced AI/ML models, such as large language models (LLMs) and large vision models (LVMs), against the constraints of both edge and cloud computing devices.

My research work has received recognition, including winning Gold Medal at the ACM Student Research Competition (SRC) at ICCAD'23, securing the Best Poster Award at the SCS Poster Competition of Georgia Tech, and being selected as an IEEE Micro's Top Pick of 2023. Additionally, I was named one of the Machine Learning and Systems Rising Stars of 2023, received the Outstanding Graduate Research Assistant Award, won first place in the University Best Demonstration at DAC'22, and our ViTCoD project was honored with the Meta Faculty Research Award of 2022.

Recruiting Information:

Looking for a summer 2026 intern on efficient GenAI at Adobe, please reach out if interested.

For prospective PhD students interested in working with me, please review my recent publications and email your CV, transcript, and a brief summary of prior research experiences.

Education

Industry Experience

Selected News

Services

Conference Reviewer

  • ICML: 2021, 2022, 2023, 2024
  • NeurIPS: 2021, 2022, 2023, 2024, 2025
  • ICLR: 2022, 2023, 2024, 2026
  • CVPR: 2022, 2023, 2024, 2025, 2026
  • ICCV: 2023
  • ECCV: 2022, 2024
  • AAAI: 2023, 2024

Journal Reviewer

Volunteering Service