Aresh Dadlani

Assistant Professor

Office: B 113B
Calgary, AB, Canada T3E 6K6
E-mail: adadlani[AT]mtroyal.ca

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NEWS

News Jul.'24: Joined MRU.
News Feb.'22: Joined U of A.
News Feb.'21: Elevated to SMIEEE.

Aresh is an Assistant Professor in the Department of Mathematics & Computing at Mount Royal University (MRU), where he leads the INtelligent COmmunications and DEcision Networks Research (INCODER) Lab. The INCODER Lab explores research at the intersection of data-driven decision-making and the stochastic modeling and control of large-scale communication networks. Our work combines mathematical rigor with real-world relevance to address emerging challenges in networked systems. Current research areas include:

  • Modeling and Performance Evaluation
  • Machine Learning for Emerging Communication Networks
  • Projection and Control of Spreading Processes over Complex Networks
  • Learning-Based Resource Allocation in Cyber-Physical Systems
  • Semantic Communications

Prior to MRU, Aresh was a Postdoctoral Fellow at the Department of Computing Science, University of Alberta. From 2017 to 2022, he was an Assistant Professor at the Department of ECE, Nazarbayev University (NU), where he led the Complex Networks and Systems Laboratory (CNSL). He earned the Ph.D. in Information and Communications from Gwangju Institute of Science and Technology (GIST) in South Korea, under the supervision of Kiseon Kim and Khosrow Sohraby, and M.Sc. and B.Sc. both in Computer Engineering from the University of Tehran in Iran.

** Looking for motivated students with a passion for research. E-mail me if interested.


Recent Publications: (Full List)

  • Age of Information in Unreliable Tandem Queues
    IEEE Communications Letters, July 2025. [Impact factor: 4.4]

  • Age Analysis of Correlated Information in Multi-Source Updating Systems with MAP Arrivals
    IEEE Communications Letters, May 2024. [Impact factor: 4.1]

  • Cost-Effective Activity Control of Asymptomatic Carriers in Layered Temporal Social Networks
    IEEE Transactions on Computational Social Systems, April 2024. [Impact factor: 5]