About Me

Education

I am a fifth year Ph.D candidate in Computer Engineering at University of Southern California under professor Viktor K. Prasanna. I am looking for a full-time research or engineering position in GNN or general AI acceleration, located in California (or remote).

a photo with professor Viktor K. Prasanna (left) and me (Right)

Research Interests

I am interested in the acceleration of computational intensive algorithm and its real-world applications. I am currently working on the efficient training and inferencing of (Dynamic) Graph Neural Network.

Publications

Zhou, Hongkuan*; Deng, Gangda*; Zeng, Hanqing; Xia, Yinglong; Leung, Christopher; Li, Jianbo; Kannan, Rajgopal; Prasanna, Viktor, Model-Architecture Co-Design for High Performance Temporal GNN Inference on FPGA, 36rd International Parallel and Distributed Processing Symposium (IPDPS), 2024 (*: Equal Contribution)

Deng, Gangda*; Akgul, Omer Faruk*; Zhou, Hongkuan; Zeng, Hanqing; Xia, Yinglong; Li, Jianbo; Prasanna, Viktor, An Efficient Distributed Graph Engine for Deep Learning on Graphs, Workshop on Machine Learning with Graphs in High Performance Computing Environments in the International Conference for High Performance Computing, Networking, Storage, and Analysis, 2023 (*: Equal Contribution)

Zhou, Hongkuan; Zheng, Da; Song, Xiang; Karypis, George; Prasanna, Viktor, DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC), 2023

Zhou, Hongkuan; Kannan, Rajgopal; Swami, Ananthram, Prasanna, Viktor, HTNet: Dynamic WLAN Performance Prediction using Heterogenous Temporal GNN, IEEE International Conference on Computer Communications (InfoCom), 2023

Wang, Ta-Yang; Zhou, Hongkuan; Kannan, Rajgopal; Swami, Ananthram, Prasanna, Viktor, Throughput Optimization in Heterogeneous MIMO Networks: A GNN-based Approach, Proceedings of the 1st International Workshop on Graph Neural Networking (GNNet), 2023

Zhou, Hongkuan; Zheng, Da; Nisa, Israt; Ioannidis, Vasileios; Song, Xiang; Karypis, George, TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs, Proceedings of the VLDB Endowment (PVLDB), 2022

Zhou, Hongkuan*; Zhang, Bingyi*; Kannan, Rajgopal; Prasanna, Viktor; Busart, Carl, Model-Architecture Co-Design for High Performance Temporal GNN Inference on FPGA, 36rd International Parallel and Distributed Processing Symposium (IPDPS), 2022 (*: Equal Contribution)

Zhou, Hongkuan; James Orme-Rogers; Kannan, Rajgopal; Prasanna, Viktor, SeDyT: A General Framework for Multi-Step Event Forecasting via Sequence Modeling on Dynamic Entity Embeddings, 30th ACM International Conference on Information and Knowledge Management (CIKM), 2021

Zhou, Hongkuan; Srivastava, Ajitesh; Hanqing Zeng; Kannan, Rajgopal; Prasanna, Viktor, Accelerating Large Scale Real-Time GNN Inference using Channel Pruning, Proceedings of the VLDB Endowment (PVLDB), 2021

Zeng, Hanqing*; Zhou, Hongkuan*; Srivastava, Ajitesh; Kannan, Rajgopal; Prasanna, Viktor, Accurate, Efficient and Scalable Graph Embedding, Journal of Parallel and Distributed Computing (JPDC), 2020 (*: Equal Contribution)

Zeng, Hanqing*; Zhou, Hongkuan*; Srivastava, Ajitesh; Kannan, Rajgopal; Prasanna, Viktor, GraphSAINT: Graph sampling based inductive learning method, International Conference on Learning Representations (ICLR), 2020 (*: Equal Contribution)

Zhou, Hongkuan; Srivastava, Ajitesh; Kannan, Rajgopal; Prasanna, Viktor, Design and Implementation of Knowledge Base for Runtime Management of Software Defined Hardware, IEEE High Performance Extreme Computing Conference (HPEC), 2019 (Best Student Paper Nominee)

Zeng, Hanqing*; Zhou, Hongkuan*; Srivastava, Ajitesh; Kannan, Rajgopal; Prasanna, Viktor, Accurate, Efficient and Scalable Graph Embedding, 33rd International Parallel and Distributed Processing Symposium (IPDPS), pp. 1–10, 2019 (*: Equal Contribution)

Personal Interests

I am interested in photography and outdoor activities such as hiking, fishing and camping. I shoot landscape photography, wildlife (bird) photography, milky way & star photography. I am also a beginner of vlogging. You can check out my channel ZHKhaha on Bilibili. Please contact me through tedzhouhk@gmail.com if you need a photographer.