Associate Professor

Institute of Software, 

Chinese Academy of Sciences (ISCAS)

Research Areas

My main research interests have been along three lines: (1) building high-performance and scalable systems for large-scale analytics; (2) exploring emerging software-hardware co-design technologies on new architectures; (3) coping with modern computing challenges that arise in data center, AI, intelligent edge and new HPC environments. These work for new system and software techniques include, not only implementing system-level optimizations (e.g., accelerated frameworks on GPUs, storage and memory management, and computation evolution), but also designing adaptive parallel paradigms for the different behaviors of algorithms and applications. In addition, I have taken on several projects in designing traditional software stacks, building high-performance libraries and systems, developing one-stop big-data platforms.

Currently, I'm working on high-performance OS on heterogeneous architectures (GPU, DPU, FPGA), distributed machine learning frameworks, robotic operating system and persistent memory techniques.

Previously, I got my PhD Degree from Institute of Software, Chinese Academy of Sciences in Jan. 2018.


  • Sept. 2012 – Mar. 2018  Institute of Software, Chinese Academy of Sciences, Beijing, China 

            Ph.D student in Computer Software and Theory

  • Sept. 2008 – Jun. 2012  Northeastern University

            B.S. in Computer Software Engineering


Work Experience

May 2018 – Now, Institute of Software, Chinese Academy of Sciences (ISCAS), Beijing, China 

Associate Research Professor, focus on high perofmance computing / systems / machine learning



[1] Heng Zhang, Lingda Li, Hang Liu, Dongling Zhuang, Rui Liu, Chengyin Huan, Charles He, Yongchao Liu, Shuang Song, Dingwen Tao, Yanjun Wu, Shuaiwen Song. Bring Orders into Uncertainty: Enabling Efficient Uncertain  Graph Processing via Novel Path Sampling on Multi-Accelerator System [C]. ACM International Conference on Supercomputing (ICS), 2022. ICS’22.

[2] Chengying Huan, Shuaiwen Leon Song, Yongchao Liu, Heng Zhang, Hang Liu, Charles He, Kang Chen, Jinlei Jiang, Yongwei Wu. T-GCN: A Sampling Based Streaming Graph Neural Network System With Hybrid Architecture [C]. 31st International Conference on Parallel Architectures and Compilation Techniques (PACT 2022).

[3] Heng Zhang, Lingda Li, Dongling Zhuang, Rui Liu, Shuang Song, Dingwen Tao, Yanjun Wu, Shuaiwen Song. An Efficient Uncertain Graph Processing Framework for Heterogeneous Architectures[C]. ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2021. PPoPP’21.

[4] Pengpeng Hou, Heng Zhang, Yanjun Wu, Jiageng You, Yang He, Yuxia Miao. FindCmd: A Personalized Command Retrieval Tool[J]. IET Software, 2021.

[5] Hongjun Zhang, Heng Zhang, Libo Zhang, Yanjun Wu. FastUDP: A highly scalable user-level UDP framework in multi-core systems for fast packet I/O[J]. The Journal of Supercomputing, 2020, 11(3). 

[6] Hongjun Zhang, Yanjun Wu, Heng Zhang, Libo Zhang. Hybrid access cache indexing framework adapted to GPU. International Journal of Software and Informatics, 2021, 11(2)

[7] Heng Zhang, Libo Zhang, Da Cheng, Yanjun Wu, Chen Zhao. EpCom: A parallel community detection approach for epidemic diffusion over social networks[C]. 2017 IEEE International Conference on Bioinformatics and Biomedicine. IEEE, 2017: 1607-1614. BIBM 2017.

[8] Heng Zhang, Haibo Hou, Libo Zhang, Hongjun Zhang, Yanjun Wu. Accelerating Core Decomposition in Large Temporal Networks Using GPUs[C]. International Conference on Neural Information Processing. Springer, Cham, 2017: 893-903. ICONIP’17.

[9] Heng Zhang, Chunliang Hao, Yanjun Wu, Mingshu Li. Towards a scalable and energy-efficient resource manager for coupling cluster computing with distributed embedded computing[J]. Cluster Computing, 2017, 20(4): 3707-3720. Cluster Computing, 2017.

[10] Heng Zhang, Chunliang Hao, Yanjun Wu, Mingshu Li. Macaca: a scalable and energy-efficient platform for coupling cloud computing with distributed embedded computing[C]. IEEE Parallel and Distributed Processing Symposium Workshops. IEEE, 2016: 1785-1788. IPDRM’16, IPDPS 2016 Workshop.

[11] Chunliang Hao, Jie Shen, Celia Chen, Heng Zhang, Yanjun Wu, Mingshu Li. PCSsampler: Sample-based, Private-state Cluster Scheduling[C]. Proceedings of the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing. IEEE Press, 2017: 599-608. CCGrid 2017.

[12] Chunliang Hao, Jie Shen, Heng Zhang, Xiao Zhang, Yanjun Wu and Mingshu Li. Tiresias: low-overhead sample based scheduling with task hopping[C]. IEEE International Conference on Cluster Computing. IEEE, 2016: 251-254. IEEE Cluster 2016. 

[13] Chunliang Hao, Jie Shen, Heng Zhang, Xiao Zhang, Yanjun Wu and Mingshu Li. Sparkle: adaptive sample based scheduling for cluster computing[C]. Proceedings of the 5th International Workshop on Cloud Data and Platforms. ACM, 2015: 5. CloudDP 2015, Eurosys 2015

[14] Kai Wang, Heng Zhang, Yanjun Wu, Chen Zhao, Mingshu Li. Frog: A Distributed Graph Processing Engine from Sequential Subgraph Blocks. Work-in-Progress, ACM SOSP 2013.

[15] Yanjun Wu, Mingshu Li, Heng Zhang, Chunliang Hao. DataOS: A Data-centric Operating System for Future Data Center. Poster in EuroSys 2016.

Research Interests

High Performance Computing

Operating System

Distributed and Parallel System

Machine Learning


Jan. 2021-Jan. 2022, University of Sydney, Austrilia

Research Visting Scholar, FSA Lab (Professor Shuaiwen Leon Song), University of Sydney, Austrilia

• Work on high performance system building and big-data analytics.

Nov. 2014 – Jun. 2015, Intel Lab China, Beijing

Research Internship, Data Infrastructure Laboratory (DIL) in Intel Lab China, Intel Inc.

• Work on distributed communication framework optimization, e.g., Petuum system, Memcached, etc.

Nov. 2011 – Apr. 2012, Baidu Inc., Beijing

Software Engineering Internship, Baidu Map Team 

• Responsible for launching webmap 2.0 online with team and webmap API v1.3 maintenance.



代培元  硕士研究生  085405-软件工程  

董岩松  硕士研究生  085405-软件工程  

王上  硕士研究生  085405-软件工程