I believe the future of AI is not replacing humans with machines, but better support humans with machines. Hence, my carrier goal is creating a "human in the loop" machine learning environment.

PhD Computer Science North Carolina State University Aug, 2015 - 2020 (expected)
MS Control Science and Egineering Shanghai Jiaotong University Sep, 2011 - Mar, 2014
BS Automation Shanghai Jiaotong University Sep, 2007 - Jun, 2011
Graduate Research Assistant, The SeBIG Lab, LexisNexis and NCSU. Aug, 2015 - Now

Member of a new lab, called “SeBig” (Software Engineering for Big Data), established as joint research collaboration between LexisNexis and NC State. Working with two other graduate students on validation methods for Big Data applications in large-scale industrial data, using Natural Language Processing, Deep Learning, and more.

PhD Scholar, The RAISE Lab, Department of Computer Science, NCSU. Aug, 2015 - Now

Working as a member of RAISE Lab, following the instruction of Dr. Menzies. My primary research is to apply machine learning algorithms to support human retrieve desired information from big data with less effort.

  • Developed a method called FASTREAD which reduces the effort by 90% in sacrifice of 10% recall.
  • A tool has been developed to implement FASTREAD, which can be found at https://github.com/ai-se/MAR.
Quantizing Investments of Stock Index Futures with Machine Learning, Shanghai Jiaotong University Mar, 2014 - Aug, 2014

Conducted several experiments on real life stock index futures data under the supervision of Dr. Yuan.

  • Established a feature selection scheme of Stock Index Futures with low-rank approximation and sparse representation.
  • Realized an online, quantizing investment algorithm with reinforcement learning.
Disturbance Observer Based Control on Multi-variable Plants, Shanghai Jiaotong University Feb, 2011 - Mar, 2014

Part of a project granted by National Natural Science Foundation of China. Working as a research assistant in the RCIR Lab. Directed by Dr. Su.

  • Established a sufficient condition for the closed-loop robust stability of a disturbance observer-based multi-variable control system.
  • Proposed a systematic design procedure of the multi-variable disturbance observer.
  • Validated the efficacy of control method through experiments on a quadrotor system.
The Design and Construction of a Plug-and-play Mobile Robot System, Shanghai Jiaotong University Mar, 2014 - Aug, 2014
  • Designed the operation interface of the robot system so that the control computer can operate a group of mobile robots simultaneously.
  • Established a multi-platform communication through socket programming to facilitate the plug-and-play.
Software Engineer, LexisNexis, Raleigh May, 2016 - Aug, 2016
  • Created a sandbox for prototyping new DiscoveryIQ features. (Python + JS + ElasticSearch)
  • Developed new feature, which is called "Open the blackbox", of DiscoveryIQ.
  • Incorporate new feature into current DiscoveryIQ product. (Scala + Spark)
Engineer, Technical Department of NEW BRP, Beijing Aug, 2014 - July, 2015
  • Finished the whole process of producing a motor control center, including assembling, wiring and debugging.
  • Took part in the project of improving motor control performance with disturbance observer.

  • Krishna, Rahul, Zhe Yu, Amritanshu Agrawal, Manuel Dominguez, and David Wolf. "The BigSE project: lessons learned from validating industrial text mining." In Proceedings of the 2nd International Workshop on BIG Data Software Engineering, pp. 65-71. ACM, 2016. link
  • Zhe Yu, Jianbo Su. ``Robust Disturbance Observer Based Control for Multi-variable Systems'', IFAC LSS 2013, July 7-9, 2013, Shanghai, China link
  • Zhe Yu, Lu Wang, Jianbo Su.``Disturbance Observer Based Control for Linear Multi-variable Systems with Uncertainties'', Acta Automatica Sinica, 2014, 40(11): 2643-2651.