Shih-Hao Hung

Adjunct Professor of Computer Science

Research Interests

Professor Hung loves building high-performance, intelligent, and secure computers. His research interests lie widely in high-performance computing (HPC) systems, artificial intelligence (AI), information security, privacy-enhancing technologies, and quantum computing. His research team aims to develop methodologies to help characterize complex computing systems to empower hardware-software co-design for emerging applications.

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Prior to joining MBZUAI, Professor Hung has been with the National Taiwan University (NTU) since 2005, where he served as the Chair of the Department of Computer Science and Information Engineering during 2020–2023. Recently, he has led his research teams to design high-performance GPU clusters and collaborate with domain experts in analyzing gigapixel medical images, training large language models (LLMs), and simulating large-scale quantum computing systems.

He also currently works as a researcher for the National Center for High-Performance Computing (NCHC), where he served as the Deputy Director General during 2020–2022, when he has played an instrumental role to establish national supercomputing infrastructures to enable HPC and AI research. During the past five years, the NCHC has established three top-notch supercomputer services, including one that delivered nine petaFLOPS to be ranked 20th in the world. Professor Hung also likes to put his research works in practice and collaborate with industry partners. Before joining NTU, he worked as a staff engineer for Sun Microsystems Inc. in Menlo Park, California, during 2000–2004, where he led a team effort to achieve a performance record for a single secure webserver with crypto acceleration.

During his tenure in NTU, he has collaborated with worldwide system/chip vendors such as IBM, HPE, Qualcomm, ARM, Intel, NVIDIA, and AMD, as well as top-tier Taiwanese tech companies, including MediaTek, QNAP Systems, Foxconn, Inventec, Wistron, Adlink, Asus Cloud, etc. He was the recipient of the IBM Faculty Open Collaborative Research Award in 2012 and 2013, Best Paper Awards from ACM RACS Conference in 2014 and 2017, and Future Tech Award from the National Science and Technology Council in 2022.

  • Ph.D. in computer science and engineering from the University of Michigan, USA.
  • Master of Science in computer science and engineering from the University of Michigan, USA.
  • Bachelor of Science in electrical engineering from the National Taiwan University, Taiwan.
  • Future Tech Award, National Science And Technology Council, 2022.
  • Best Paper Award, ICS 2021.
  • Best Paper Award, ACM Conference on Research in Adaptive and Convergent Systems (RACS), 2014, 2017.
  • Best Paper Award Candidate, ACM International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS), 2012.
  • IBM Open Collaboration Award, 2012, 2013.

  • Shih-Chiang Huang, Chi-Chung Chen, Jui Lan, Tsan-Yu Hsieh, Huei-Chieh Chuang, Meng-Yao Chien, Tao-Sheng Ou, Kuang-Hua Chen, Ren-Chin Wu, Yu-Jen Liu, Chi-Tung Cheng, Yu-Jen Huang, Liang-Wei Tao, An-Fong Hwu, I-Chieh Lin, Shih-Hao Hung, Chao-Yuan Yeh, Tse-Ching Chen (2022, Jun). Deep neural network trained on gigapixel images improves lymph node metastasis detection in clinical settings. Nature Communications, 13, 3347 (2022).
  • Cheng-Han Lu, Shih-Hao Hung (2022, Dec). FEZ: a Flexible and Efficient Zoom-in Method for Ultra-large Image Classification. 2022 IEEE International Conference on Big Data (IEEE BigData 2022), Osaka, Japan.
  • Chuan-Chi Wang, Chun-Yen Ho, Chia-Heng Tu, Shih-Hao Hung (2022, Apr). cuPSO: GPU parallelization for particle swarm optimization algorithms. SAC '22: The 37th ACM/SIGAPP Symposium on Applied Computing: 1183-1189.
  • Yi-Hua Chung, Cheng-Jhih Shih, Shih-Hao Hung (2022, May). Accelerating Simulated Quantum Annealing with GPU and Tensor Cores. ISC High Performance 2022 (ISC 2022), Hamburg, Germany. 174-191
  • Chuan-Chi Wang, Ying-Chiao Liao, Ming-Chang Kao, Wen-Yew Liang, Shih-Hao Hung (2021, Jul). Toward accurate platform-aware performance modelling for deep neural networks. ACM SIGAPP Applied Computing Review, 21(1), 50-61.
  • Min‐Yu Tsai, Zhen Tian, Nan Qin, Congchong Yan, Youfang Lai, Shih‐Hao Hung, Yujie Chi, Xun Jia (2020, Apr). A new open‐source GPU‐based microscopic Monte Carlo simulation tool for the calculations of DNA damages caused by ionizing radiation‐‐‐Part I: Core algorithm and validation. Medical physics, 47(4), 1958-1970.

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