Biography

Welcome! I’m a research scientist/engineer at Adobe Research, working on efficient generative models. I received my Ph.D. degree from the Department of Electrical and Computer Engineering at Northeastern University, supervised by Prof. Yanzhi Wang in 2024. My research vision is in general artificial intelligence systems to facilitate deep learning implementation on various edge devices and bridge the gap between algorithm innovations and hardware performance optimizations. It includes energy-efficient deep learning and artificial intelligence systems and accelerations of deep neural networks such as large-scale models for AI-generated content. My works (first-authored) have been published in top-tier conferences and journals including ICML, ICLR, NeurIPS, ICCV, ECCV, DAC, ICCAD, and TODAES. I’m honored to be selected as the 2024 Rising Star in EECS and the 2024 Machine Learning and Systems Rising Star. I also won first place at the DAC Ph.D. forum and received the College of Engineering’s Outstanding Graduate Student award and Dean’s fellowship from Northeastern University.

I am looking for motivated summer interns to work with me on efficient generative models, please feel free to contact me if you are interested!

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Research Interests

• Accelerations of Emerging Large-Scale Models for AIGC
• Hardware and Software Co-Design for Artificial Intelligence Accelerations
• Energy-Efficient Deep Learning and Artificial Intelligence Systems
• Model Compression
• Efficient and Robust Deep Learning

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News and Updates

• Sep 2024: We get three papers accepted in NeurIPS’24!
• Sep 2024: We get one paper accepted in the main track of EMNLP’24!
• Aug 2024: Honored to be selected as the 2024 MIT EECS Rising Stars!
• July 2024: Received Northeastern PhD Network Travel Award. Thanks to Northeastern!
• July 2024: Our paper “Efficient Training with Denoised Neural Weights” is accepted in ECCV’24.
• June 2024: I won First Place at DAC Ph.D. Forum !
• June 2024: Our paper “AyE-Edge: Automated Deployment Space Search Empowering Accuracy yet Efficient Real-Time Object Detection on the Edge” is accepted in ICCAD’24.
• May 2024: Honored to be selected as the 2024 MLCommons ML and Systems Rising Stars held in NVIDIA HQ.
• May 2024: I have been selected to attend the DAC Ph.D. Forum.
• May 2024: Our paper “E^2GAN: Efficient Training of Efficient GANs for Image-to-Image Translation” is accepted in ICML’24. Thank you, team!
• April 2024: Grateful to receive the travel grant from CVPR’24.
• April 2024: Selected as DAC Young Fellow.
• March 2024: Our research paper titled “Reverse Engineering Deceptions in Machine- and Human-Centric Attacks” has been officially published in Foundations and Trends® (FnT) in Privacy and Security.
• Feb 2024: Our paper “Lotus: learning-based online thermal and latency variation management for two-stage detectors on edge devices” is accepted in DAC’24!

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Professional Experiences