Dr. Dariush Ebrahimi

Assistant Professor

Department: 
Email: 
debrahim@lakeheadu.ca
Phone Number: 
+1 (807) 346-7788
Office Location: 
CB4056B
Office Hours: 
Tuesday and Thursday 3:00 to 4:00 pm or by appointment  
Academic Qualifications: 

Ph.D., Computer Science, Concordia University, Quebec, Canada, 2016

Post-Doctoral, Computer Science, Universite du Quebec a Montreal (UQAM), 2017

Post-Doctoral, Electrical and Computer Engineering, University of Waterloo, 2018- 2019

Date joined Lakehead: 
August 2019
Previous Teaching/Work: 
  • Algorithm
  • Data Base
  • Operating System
  • Security
  • Programming Language for Engineers (C++)
  • Laboratory for Programming Language for Engineers
Research Interests: 
  • Internet of Things
  • Wireless Communications
  • Wireless Sensor Networks
  • Algorithm Design
  • Optimization
  • Mobile and Vehicular Edge Computing
  • Reinforcement Learning (Machine Learning)

News

Manuscript titled “Minimizing the Age of Information in Intelligent Transportation Systems” has been accepted to appear in the IEEE International Conference on Cloud Networking (IEEE CloudNet 2020).

Manuscript titled “Age of Information Aware Trajectory Planning of UAVs in Intelligent Transportation Systems: A Deep Learning Approach” has been accepted to appear in the IEEE Transactions on Vehicular Technology (2020).

Manuscript titled “UAV-assisted Content Delivery in Intelligent Transportation Systems - Joint Trajectory Planing and Cache Management” has been accepted to appear in the IEEE Transactions on Intelligent Transportation Systems (2020).

Manuscript titled “Cooperative Content Delivery in UAV-RSU Assisted Vehicular Networks” has been accepted to appear in the 2nd Workshop on Drone Assisted Wireless Communications for 5G and Beyond - co-located with ACM MobiCom 2020 (DroneCom 2020)

Manuscript titled “An Infrastructure-Assisted Workload Scheduling for Computational Resources Exploitation in Fog-Enabled Vehicular Network” has been published in the IEEE Internet of Things Journal (2020).

Manuscript titled “Leveraging UAVs for Coverage in Cell-Free Vehicular Networks: A Deep Reinforcement Learning Approach” has been published in the IEEE Transactions on Mobile Computing (2020).

Manuscript titled “Autonomous UAV Trajectory for Localizing Ground Objects: A Reinforcement Learning Approach” has been published in the IEEE Transactions on Mobile Computing (2020).

Manuscript titled "Trajectory Planning of Multiple Dronecells in Vehicular Networks: A Reinforcement Learning Approach” has been published in the IEEE Networking Letters 2, no. 1 (2020): 14-18(2020).

Manuscript titled “An Infrastructure-Assisted Workload Scheduling for Computational Resources Exploitation in Fog-Enabled Vehicular Network” has been published in the IEEE Internet of Things Journal (2020).

Manuscript titled "Revenue-driven video delivery in vehicular networks with optimal resource scheduling" has been published in the Elsevier Vehicular Communications 23 (2020): 100215.

Manuscript titled "Workload Scheduling in Vehicular Networks with Edge Cloud Capabilities" has been published in the IEEE Transactions on Vehicular Technology, vol. 68, no. 9, pp. 8472 - 8486, Sep. 2019.

Manuscript titled "On Leveraging the Computational Potential of Fog-Enabled Vehicular Networks" has been published in the Proceedings of the 9th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications ( MSWIM 2019 ), pp. 9-16. 2019.

 

Are you interested in Graduate Studies?

Currently, I am looking for enthusiastic and talented graduate students (master level) who are interested in any of the research areas posted here. There are funding opportunities for domestic research students. If you are interested, please send me an email with your CV and academic transcript.