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Shah rokh Valaee


Nortel Chair in Network Architecture and Services

Department of Electrical and Computer Engineering
University of Toronto
10 King's College Road
Toronto, ON, Canada, M5S 3G4

UofT Crest



The research in our group is diverse. Our researchers are working in several interesting and challenging areas, such as machine learning, wireless communications, signal processing, and biomedical engineering. There are three main clusters of research in our group:

  • integrated sensing and communication (ISAC): The first cluster comprises the methods used to locate people and objects. Localization and sensing is a vibrant research area and is gaining tremendous interest both in academia and industry. With the inclusion in integrated sensing and communication and the new mmWave and subTeraHz spectrum the need for research in this area is in a rising trend.

  • Machine Learning (ML): The second cluster of students is working on the application of machine learning (ML) in health. One of the chief challenges in the application of ML in healthcare is the scarsity of data. Furthermore, such data are commonly imbalanced (small number of sample points for rare diseases), and may easily be missed by a professional practitioner. A main challenge is to find high performing ML techniques that can be applied to small data.

  • Beyond 5G Networks: With the 5G standards being ratified, the main focus of our research is now on the B5G/6G cellular systems. There will be several fundamental differences between 6G and its predecessors. 6G will move vertically by introducing drones and low orbit satellites into the cellular system. With the proliferation of autonomous vehicles, there will be a dire need to equip cars with communications and networking capabilities. Besides mobility, the network agility will also be increased by the introduction of Reconfigurable Intelligent Surfaces (RIS).

Samples of research topics our group has been working on:


We have a vibrant group that concentrates on tackling difficult engineering problems. Our researchers are among the best with strong technical background and great programming skills. We use advanced signal processing and wireless networking techniques to solve challenging problems with a focus on mixing theory and practice. Our analytical strengths span a wide range that includes machine learning, compressive sensing, and network coding. We implement our machine learning algorithms on GPU hardware, and our localization algorithms on the Android planform.