In recent years, the field of computing has been revolutionized by the emergence of new paradigms such as cloud computing, multi-cores, mobile computing, big data, and new paths in machine learning. Algorithms play a key role in all these advances, and the interplay between system design and the use of sophisticated algorithms, optimizations, and protocols is becoming ever more complex and important. In the System Algorithms (SysAlgo) Research Group, we focus on problems at the intersection of algorithms and systems & networking research. Our goal is to study the fundamental principles and laws that govern the systems and networks that drive today's computing, and to devise state-of-the-art algorithms to optimize and improve these systems. Our research results have been published in numerous top conferences such as SIGCOMM, NSDI, ISCA, MobiSys, MobiCom, SODA, or PODC, and include multiple award-winning papers. At the same time, we maintain deep collaborations with various Microsoft product groups, and have applied our expertise in practice to contribute highly efficient, scalable, and robust solutions to their products.
- Qian Wang, Jiaxing Zhang, Sen Song, and Zheng Zhang, Attentional Neural Network: Feature Selection Using Cognitive Feedback, in NIPS 2014, Curran Associates, Inc., December 2014
- Bojun Huang and Thomas Moscibroda, Conflict Resolution and Membership Problem in Beeping Model, in International Symposium on Distributed Computing (DISC) 2013, October 2013
- Yuezhou Lv and Thomas Moscibroda, Fair and Resilient Incentive Tree Mechanisms, in 32nd Annual ACM Symposium on Principles of Distributed Computing (PODC), ACM, July 2013
- Fengyuan Xu, Yunxin Liu, Thomas Moscibroda, Ranveer Chandra, Long Jin, Yongguang Zhang, and Qun Li, Optimizing Background Email Sync on Smartphones, ACM International Conference in Mobile Systems, Applications, and Services (MobiSys), 25 June 2013
- Zhenyu Guo, Xuepeng Fan, Rishan Chen, Jiaxing Zhang, Hucheng Zhou, Sean McDirmid, Chang Liu, Wei Lin, Jingren Zhou, and Lidong Zhou, Spotting Code Optimizations in Data-Parallel Pipelines through PeriSCOPE, in OSDI, USENIX, 8 October 2012
- Jiaxing Zhang, Hucheng Zhou, Rishan Chen, Xuepeng Fan, Zhenyu Guo, Haoxiang Lin, Jack Y.Li, Wei Lin, Jingren Zhou, and Lidong Zhou, Optimizing Data Shuffling in Data-Parallel Computation by Understanding User-Defined Functions, in NSDI, USENIX, 25 April 2012
- Zhengping Qian, Xiuwei Chen, Nanxi Kang, Mingcheng Chen, Yuan Yu, Thomas Moscibroda, and Zheng Zhang, MadLINQ: Large-Scale Distributed Matrix Computation for the Cloud, in EuroSys 2012, ACM, April 2012