Peiyan Dong

Research Abstract:

My research area is the intersection of Software-Hardware Co-design, Efficient AI, Hardware Architecture, SuperConducting Logic: 1. Hardware and Software Co-design for DNN Architecture 2. Inference-Efficient/Energy-Efficient Artificial Intelligence Systems 3. Efficient Deep Learning on Superconducting Devices 4. Emerging Deep Learning Systems Summary: There are 16 first/co-first author publications ranging from: (I) EDA, solid-state circuit, and system conferences such as DAC, ICCAD, ISSCC, ASP-DAC, RTAS, MLSys. (II) Architecture and computer system conferences such as MICRO, HPCA, ICS. (III) Machine learning algorithm conferences such as NeurIPS, ICML, CVPR, AAAI, ECCV, IJCAI, AAAI. (IV) Journal publications including TCAD, Advanced Intelligent Systems, TCASI, TECS, TPAMI.

Bio:

Peiyan (Peggie) Dong is currently pursuing the Ph.D. degree under Professor Yanzhi Wang in Northeastern University, Boston, MA, U.S. Her research interests mainly focus on Hardware Co-design on Deep Learning, Efficient Deep Learning, Placement and Routing on Superconducting Devices and Quantum Machine Learning. She also likes travel, eating food, especially hot pot! Now she is pursuing academic careers in computer engineering, electrical engineering and computer science. Welcome to contact her!