Dr. Wei Shi

Full Professor

Associate Director, Undergraduate

  • CB4305
  • +1 (613) 520-2600 x5060
  • Personal Website

Dr. Wei Shi

Full Professor

Associate Director, Undergraduate

Dr. Wei Shi is a Professor in the School of Information Technology, cross-appointed to the Department of Systems and Computer Engineering in the Faculty of Engineering & Design at Carleton University. She specializes in algorithm design and analysis in distributed environments such as Data Centers, Clouds, Mobile Agents and Actuator systems and Wireless Sensor Networks. She has also been conducting research in data privacy and Big Data analytics. She holds a Bachelor of Computer Engineering from Harbin Institute of Technology in China and received her Master's and Ph.D. in Computer Science from Carleton University in Ottawa, Canada. Dr. Shi is also a Professional Engineer licensed in Ontario, Canada.


Research Areas

  • Big Data Analytics Acceleration
  • Cloud and Data Center Optimization
  • Algorithm Design in Distributed Systems
  • Data Privacy Preservation

Research Topics

  • Network Technology
  • Data Science
  • Computer Networks (Planning, Design, Architecture)
  • Cloud, Fog, and Edge Computing
  • Internet of Things (IoT)
  • Ad-hoc and Wireless Sensor Networks
  • Network security (Threat modelling, blockchain, usable security)
  • Cybersecurity
  • Data Privacy
  • Big Data Analytics

Activities

Technical Program Committees

  • The Fourth IEEE International Conference on Big Data Intelligence and Computing (DataCom 2018), 12-15 August 2018, Athens, Greece. TPC
  • The 4th IEEE International Conference on Smart Data (SmartData-2018), July 30th – August 03, 2018. Halifax, Canada. TPC.
  • The 3rd IEEE Conference on Cloud and Big Data Computing (CBDCom 2018), October 8-12, 2017. Guangzhou, P.R. China. Workshop Chair.
  • The 3rd IEEE Conference on Cloud and Big Data Computing (CBDCom 2017), August 4 -8, 2017. San Francisco Bay Area, USA. Publicity Chair.
  • The 5th International Workshop on Parallel and Distributed Computing for Large Scale Machine Learning and Big Data Analytics (ParLearning 2017), May 29, 2017. Orlando, Florida, USA