Service Computing: service-oriented computing, context-aware service recommendation, and dynamic service composition and substitution
Cloud Computing: computing resource scheduling, hybrid cloud storage, and inter-cloud
Big Data: resilient storage for big data, high performance engine for big

2001: Ph.D, Department of CS, Northwestern Polytechnical University, China
1999: M.S., Department of CS, Northwestern Polytechnical University, China
1996: B.S., Department of CS, Hangzhou Institute of Electronical Engineering, China

2008.12-Present, Associate Professor, School of Software, Shanghai Jiao Tong University.
2009.12-2010.12, Visiting Scholar, School of Computing, Georgia Institute of Technology.
2004.3-2008.12, Lecturer, School of Software, Shanghai Jiao Tong University.
2002.3-2004.2, Postdoctor, School of Software, Shanghai Jiao Tong University.

Haopeng Chen is an Associate Prof. of School of Software, Shanghai Jiao Tong University. His research interest mainly focus on software architecture and development technique of distributed systems, including service computing, cloud computing and big data.
Service Computing is his first interest, he proposed an idea of describing, discovering, and managing service based on closed loop feedback on Internet and got a funding support from National High-Tech Research Development Program of China. His another research interest is Cloud Computing, in which he proposed a profit-driven dynamic computing resource scheduling framework and a hybrid cloud storage for IaaS. Recently, he also focuses on big data, including big data storage and processing, and big data applications, such as big data mining of MOOCs supported by MOE.

1) Shanghai Science and Technology Progress Award (Second Class), By Shanghai municipal government, 2013
2) IBM Faculty Award, By IBM, 2016

1) Web Application Development, for the sophomores majoring in Software Engineering
2) Architecture of Enterprise Applications, for the juniors majoring in Software Engineering

1) Wang H, Chen H, Du Z, et al. BeTL: MapReduce Checkpoint Tactics Beneath the Task Level[J]. IEEE Transactions on Services Computing, 2016, 9(1): 84-95.
2) Zhang Q, Chen H, Shen Y, et al. Optimization of virtual resource management for cloud applications to cope with traffic burst[J]. Future Generation Computer Systems, 2016, 58: 42-55.
3) Wang Z, Chen H, Fu Y, et al. Workload balancing and adaptive resource management for the swift storage system on cloud[J]. Future Generation Computer Systems, 2015, 51: 120-131.
4) Wang W, Chen H, Chen X. Towards Availability: A Dynamic Scaling Mechanism for Cloud Applications[J]. International Journal of Adaptive, Resilient and Autonomic Systems (IJARAS), 2014, 5(2): 23-39.
5) Sun J, Chen H, Yin Z. AERS: An Autonomic and Elastic Resource Scheduling Framework for Cloud Applications[C]//Services Computing (SCC), 2016 IEEE International Conference on. IEEE, 2016: 66-73.
6) Lingxuan S, Chen H, Ma S, et al. WHOBBS: An Object-Based Distributed Hybrid Storage Providing Block Storage for Virtual Machines[C]//High Performance Computing and Communications (HPCC), 2015 IEEE 17th International Conference on. IEEE, 2015: 160-165.
7) Dai W, Chen H, Wang W. Rahec: A mechanism of resource management for heterogeneous clouds[C]//High Performance Computing and Communications (HPCC), 2015 IEEE 17th International Conference on. IEEE, 2015: 40-45.
8) Fu Y, Chen H, Song F. STWM: A Solution to Self-adaptive Task-Worker Matching in Software Crowdsourcing[C]//International Conference on Algorithms and Architectures for Parallel Processing. Springer International Publishing, 2015: 383-398.
9) Song F, Chen H, Fu Y. An Approach to Rapid Worker Discovery in Software Crowdsourcing[C]//International Conference on Algorithms and Architectures for Parallel Processing. Springer International Publishing, 2015: 370-382.
10) Ma S, Chen H, Shen Y, et al. Providing hybrid block storage for virtual machines using object-based storage[C]// Parallel and Distributed Systems (ICPADS), 2014 IEEE 20th International Conference on. IEEE, 2014: 150-157.