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Dr Wenjie Ruan

Lecturer

Wenjie Ruan

B51, Floor B, InfoLab21

School of Computing and Communications, Lancaster University

LA1 4WA

Lancaster

Web: http://wenjieruan.com

PhD supervision

I am always looking for talented potential PhD students worldwide. If you are interested in my research, please do not hesitate to contact me via Email: wenjie.ruan AT lancaster.ac.uk. Topics: Machine Learning for Healthcare, Ubiquitous Computing, Robustness of Deep Neural Networks, Data Analytics. Requirements: Solid Math Background, Strong Programming Skills. Funding: Multiple Ph.D. studentships available in the school [Deadline: the end of June each year]. Research students and visiting scientists with their own fundings are strongly welcome to visit us. Undergraduates and postgraduates who want to do their projects with me are also very welcome.

Profile

Currently, I am a Lecturer (Assistant Professor) in the School of Computing and Communications at Lancaster University. From 2017 to 2019, I have worked as a Postdoctoral Researcher in the Department of Computer Science at University of Oxford, funded by the EPSRC Project - Mobile Robotics: Enabling a Pervasive Technology of the Future. I received my Ph.D. degree from the School of Computer Science at The University of Adelaide, Australia. I also did a six-month research intern in the Internet of Things Tech Centre (GreenOrbs), Tsinghua University. Before my Ph.D., I worked as a Control System Engineer in Institutes of Optics and Electronics at Chinese Academy of Sciences. I obtained my Master degree in Control Science and Engineering and my Bachelor degree in Automation. More information can be found on my personal homepage: lancaster.ac.uk/staff/ruanw.

 

My research interests:

  • Ubiquitous and Mobile Computing
  • Machine Learning and Its Applications in Human-Centered Computing and Sensor Data Analytics
  • Safety and Robustness of Deep Neural Networks

 

Funded PhD Opportunities:

  • Topics: Machine Learning for Healthcare, Ubiquitous Computing, Robustness of Deep Neural Networks, Data Analytics
  • Requirements: Solid Math Background, Strong Programming Skills
  • Funding: Multiple Ph.D. studentships available in the school [Deadline: the end of June each year]

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