Biography

Welcome! Yifan (Evelyn) Gong is a fifth-year PhD candidate in the Department of Electrical and Computer Engineering at Northeastern University, supervised by Prof. Yanzhi Wang. She received the B.S. degree (with the highest honor) in Telecommunications Engineering from Xidian University in 2017 and the M.A.Sc. degree (with fellowship) in Computer Engineering from the University of Toronto in 2019. Her 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 by a hardware and software co-design approach. 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. Yifan’s works (first-authored) have been published in top-tier conferences and journals including ICML, ICLR, ICCV, ECCV, DAC, ICCAD, and TODAES.

Yifan is on the 2024 job market, please feel free to contact if you are interested!

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Research Interests

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

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News and Updates

• May 2024: One first-authored paper “E$^2$GAN: 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® in Privacy and Security.
• Feb 2024: One first-authored paper “Lotus: learning-based online thermal and latency variation management for two-stage detectors on edge devices” is accepted in DAC’24!
• Sep 2023: Glad to receive ICCAD Student Scholar Grant.
• Sep 2023: One paper “HotBEV: Hardware-oriented Transformer-based Multi-View 3D Detector for BEV Perception” is accepted in NeurIPS’23.
• July 2023: One co-first-authored paper “MOC: Multi-Objective Mobile CPU-GPU Co-optimization for Power-efficient DNN Inference” is accepted in ICCAD’23.
• May 2023: Glad to receive the College of Engineering Outstanding TA award.
• April 2023: One paper “DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning” is accepted in ICML’23.
• Feb 2023: One first-authored paper “Condense: A Framework for Device and Frequency Adaptive Neural Network Models on the Edge” is accepted in DAC’23.

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Professional Experiences