Ke Fan
Assistant professor, Computer Science
Temple University
About me
I am an Assistant Professor in the Department of Computer Science at Temple University, beginning in Fall 2025. I earned my Ph.D. in Computer Science at the University of Illinois Chicago under the guidance of Sidharth Kumar. My research lies in high-performance computing (HPC), emphasizing three key areas: optimizing the performance of MPI collectives, enhancing the performance of irregular parallel I/O operations, and improving the scalability of performance introspection frameworks.
Throughout my Ph.D. journey, I have made significant contributions to the field of high-performance computing, as evidenced by my publications in top-tier HPC conferences such as HPDC, HiPC, and ISC. My poster presentation at SC 2023 was recognized as the best poster finalist. I am also exploring new research areas, including GPU-aware collectives, auto performance tuning for collectives using ML, and ensemble performance visualization tools.
Excited to announce that I am recruiting PhD students! Please get in touch if you’d like to join.
Selected Publications
GPU-Accelerated Maximal Quasi-Clique Mining
Michael Greenbaum, Ke Fan, Wajid Manzoor, and Guimu Guo
2025 IEEE International Conference on Big Data (Bigdata 2025)
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Machine Learning Driven Auto-tuning for Non-uniform All-to-All Collectives
Kunting Qi, Ke Fan, Jens Domke, Seydou Ba, Venkatram Vishwanath, Michael Papka, Sidharth Kumar
IEEE Conference On High Performance Computing, Data, and Analytics (HiPC 2025)
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Parameterized Algorithms for Non-uniform All-to-all
Ke Fan, Jens Domke, Seydou Ba, Sidharth Kumar
International Symposium on High-Performance Parallel and Distributed Computing (HPDC 2025)
Acceptance rate: 19%
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p21, ccng1, foxo3b, and fbxw7 contribute to p53-dependent cell cycle arrest
Jun Wang, Zhang Li, Holly R Thomas, Ke Fan, Robert G Thompson, Yongjie Ma, David Crossman, Bradley K Yoder, John M Parant
iScience, 2025
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Configurable Algorithms for All-to-all Collectives
Ke Fan, Steve Petruzza, Thomas Gilray, Sidharth Kumar
The International Supercomputing Conference (ISC 2024)
Acceptance rate: 29%
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TinyProf: Towards Continuous Performance Introspection through Scalable Parallel I/O.
Ke Fan, Suraj Kesavan, Steve Petruzza, Sidharth Kumar
The International Supercomputing Conference (ISC 2024)
Acceptance rate: 29%
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Investigating Data Movement Strategies for Distribution of Repartitioned Data.
John-Paul Robinson, Ke Fan, Steve Petruzza, Thomas Gilray, Sidharth Kumar.
Practice and Experience in Advanced Research Computing 2024: Human Powered Computing. (PEARC 2024)
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Bruck Algorithm Performance Analysis for Multi-GPU All-to-All Communication.
Andres Sewell, Ke Fan, Ahmedur Rahman Shovon, Landon Dyken, Sidharth Kumar, Steve Petruzza.
2024 International Conference on High-Performance Computing in Asia-Pacific Region (HPC Asia 2024)
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Optimizing the Bruck Algorithm for Non-uniform All-to-all Communication.
Ke Fan, Thomas Gilray, Valerio Pascucci, Xuan Huang, Kristopher Micinski, Sidharth Kumar
International Symposium on High-Performance Parallel and Distributed Computing (HPDC 2022)
Acceptance rate: 19%
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Load-balancing Parallel I/O of Compressed Hierarchical Layouts.
Ke Fan, Duong Hoang, Steve Petruzza, Thomas Gilray, Valerio Pascucci, Sidharth Kumar.
IEEE Conference On High Performance Computing, Data, and Analytics (HiPC 2021)
Acceptance rate: 23%
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Exploring MPI Collective I/O and File-per-process I/O for Checkpointing a Logical Inference task.
Ke Fan, Kristopher Micinski, Thomas Gilray, Sidharth Kumar.
IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW 2021)
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