Mohamed Akrout
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Assistant Professor
Office: Min H. Kao Building |
About me
I am an Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee. I received my PhD in Electrical and Computer Engineering in 2024 from the University of Manitoba. I received my BE in Computer Engineering from Ecole Polytechnique de Montreal and Telecom ParisTech, and my MS in Applied Computer from the University of Toronto. After my PhD, I spent a year visiting the Technical University of Munich (TUM) and the University of California San Diego (UCSD). I was awarded the doctoral scholarship and the postdoctoral fellowship from the Natural Sciences and Engineering Research Council of Canada (NSERC), in 2022 and 2024, respectively.
Research interests
My research interests include sensing, antennas, and signal processing for inverse problems. My research focuses on application of principles and tools in optimization and control to the study of requirement-driven machine decision-making. I am particularly interested in how constraints, arising from system requirements, shape intelligent decision-making in future sensing and communication systems. My current research interests include:
Contactless sensing for precision health: I design high-resolution wireless sensing systems for precision health and continuous monitoring of patients and animals. Using mmWave and sub-THz radar, I reconstruct granular physiological biomarkers (e.g., respiratory waveforms) without invasive or contact-based wearables. I combine classical radar signal processing with deep learning techniques by employing neural networks as targeted function approximators to enhance estimation accuracy.
Scaling beyond 5G (B5G) communication systems: I study MIMO communication under physical constraints. The major difficulty of this research is that the performance criterion of interest (i.e., the achievable rate) emanates from communication theory while the physical constraints (i.e., antenna size and mutual coupling) arise from antenna theory. In other words, optimizing the achievable rate of MIMO systems while accounting for their physical constraints is a problem that lies at the interface of communication and antenna theories. For this reason, I am interested in combining Shannon and Maxwell theories using circuit-based physically consistent models which connect the physics of antennas with the mathematics of communication systems.
Artificial intelligence for healthcare: I am particularly interested in optimizing the patient-clinician cycle using artificial intelligence, where agents are designed to deliver accurate second-opinion diagnoses for doctors and optimize their precious time to provide a prescription. In this context, I helped creating AIP Labs, a digital health & AI company in Europe focused on dermatology at which I still advise from time to time. By visiting the AIP digital clinic, you can get a dermatology diagnosis, a treatment plan, and a prescription within a few hours or less, all reviewed by both a EU certified dermatologist.
For prospective students
Unfortunately, I am currently not recruiting for open positions anymore for this admission cycle. Good luck with your search! If you are still interested, you can apply to our department here.