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Alireza Tavakkoli

Professor and Director of BRAIN Core, Computer Science and Engineering

Open to new collaborations

Research interests

Dr. Alireza Tavakkoli received his BSc (Electronics) and MSc (Electronics) from Sharif University of Technology in 2001 and 2004, respectively. He received his MSc and Ph.D. in Computer Science and Engineering from the University of Nevada, Reno in 2006, and 2009, respectively. Dr. Tavakkoli is currently an Associate Professor of Computer Science and Engineering at the University of Nevada, Reno, where he teaches courses in computer vision, digital interactive gaming and robotics. He has a broad background in machine learning and visual computing, with specific training and expertise in computer vision, virtual reality, computer graphics and artificial intelligence. Dr. Tavakkoli's research includes investigating mathematical and computational frameworks to extract high-level salient information from basic imagery with applications to robotics, visualization and assistive technologies. He has been the recipient of several research grants from the industry and federal agencies for his teaching and research.

Recent publications

The ten most recent from their Google Scholar profile, newest first.

  1. Risk prediction in spine surgery: a scoping review of traditional models, artificial intelligence, and the challenge of clinical translation

    S Salman, R Phadke, R Kumar, A Momin, A Tavakkoli. Spine Deformity, 1-13 , 2026. 2026

    18 citations

  2. Digital twins and multimodal artificial intelligence in spine care: a scoping review of concepts, evidence, and translational barriers

    SG Salman, R Phadke, R Kumar, N Zaman, A Tavakkoli. Spine Deformity, 1-10 , 2026. 2026

    14 citations

  3. Ophthalmic image synthesis and analysis with generative adversarial network artificial intelligence

    M Masalkhi, K Sporn, R Kumar, J Ong, T Nguyen, E Waisberg, N Zaman, .... Journal of Imaging Informatics in Medicine 39 (1), 732-754 , 2026. 2026

    13 citations

  4. Dynamic spine stabilization through mechanically tuned constructs and embedded biomechanical feedback systems: a narrative review

    R Kumar, A Bouras, R Phadke, S Salman, H Kaur, K Sporn, A Damian, .... Discover Sensors 2 (1), 26 , 2026. 2026

    5 citations

  5. Response to: Comment on ‘Risk prediction in spine surgery: a scoping review of traditional models, artificial intelligence, and the challenge of clinical translation’

    SG Salman, R Phadke, R Kumar, A Momin, A Tavakkoli. Spine Deformity, 1-2 , 2026. 2026

    5 citations

  6. Perioperative ischemic optic neuropathy: a comprehensive review of anesthetic implications, hemodynamic pathophysiology, and risk stratification

    A Surya, S Salman, R Phadke, K Sporn, L Yaldo, R Kumar, P Paladugu, .... International Ophthalmology 46 (1), 155 , 2026. 2026

    4 citations

  7. Personalized treatment of chronic tendinopathy using ultrasound and neuroimmune markers: a narrative review

    R Phadke, S Salman, K Patel, J Wardeh, A Marupudi, R Kumar, A Momin, .... Discover Neuroscience 21 (1), 31 , 2026. 2026

    4 citations

  8. Deep Learning-Based Multi-Class Pediatric Wrist Fracture Subtype Classification: A Pilot Study Comparing Convolutional Neural Network Architectures

    RA Phadke, SG Salman, ZG Salman, SM Yedupati, J Ong, A Tavakkoli, .... Journal of Imaging 12 (7), 307 , 2026. 2026

    3 citations

  9. Ordinal deep learning for lumbar foraminal stenosis grading on sagittal MRI

    RA Phadke, SG Salman, ZG Salman, A Marupudi, K Patel, J Ong, .... Journal of Imaging 12 (8), 388 , 2026. 2026

    3 citations

  10. Fire-vlm: A vision-language-driven reinforcement learning framework for uav wildfire tracking in a physics-grounded fire digital twin

    C Webb, M Habibpour, MH Raha, AR Tavakkoli, J Coen, F Afghah. Proceedings of the IEEE/CVF Winter Conference on Applications of Computer … , 2026. 2026

    2 citations

All publications on Google Scholar