Ph.D. (2009)
Computer Science and Engineering
University of Nevada, Reno
College of Engineering - University of Nevada, Reno
Alireza Tavakkoli, Ph.D.
Professor of Computer Science and Engineering
I am a Professor at the department of Computer Science and Engineering at the University of Nevada, Reno, with a background spanning computer science, electrical, and electronics engineering. I hold a Ph.D. and M.Sc. in Computer Science and Engineering, as well as an M.Sc. and B.Sc. in Electrical and Electronics Engineering.
My research lies at the intersection of human–machine perception, artificial intelligence, and data-driven scientific discovery. I develop computational methods that transform complex sensory and imaging data into meaningful representations across multiple scales. This has led to interdisciplinary collaborations across biomedicine and neuroscience to large-scale environmental analysis, empowered by robust, interpretable, and human-centered AI that can translate data into actionable scientific insight.
Background
Academic Background
M.Sc. (2006)
Computer Science
University of Nevada, Reno
M.Sc. (2004)
Electrical and Electronics Engineering
Sharif University of Technology
B.Sc. (2001)
Electrical and Electronics Engineering
Sharif University of Technology
Research
Research Interests
Artificial Intelligence and Machine Learning
- Multi-modal AI
- Representation Learning
- Systems AI
Digital Twins
- Digital Twins for Fire Landscape
- Medical Digital Twins
Huma-Computer Interaction
- 3D User Interfaces
- Immersive Virtual/Augmented/Mixed Reality
Robotics
- Tele-exploration
- Teleoperation
Research community
Human Machine Perception Lab
The Human–Machine Perception Laboratory at UNR, under Dr. Tavakkoli’s direction, pioneers the integration of AI-driven medical imaging, wearable diagnostics, and digital twin technologies to enhance personalized healthcare, natural and environmental sciences, engineering, and biomedical fields. We have been investigating various computational frameworks for efficient and reliable integration of human and machine perception in interdisciplinary fields. Through a blend of immersive XR platforms, cutting‑edge machine learning, and real‑world sensing networks, the lab continues to push the boundaries of how machines perceive, interpret, and interact with complex biological and environmental systems.
Current Students
Adarsha Pandey
Current Students
Chase Carthen
Current Students
Joseph Tran
Current Students
Mayamin Raha
Updates
Latest news
August 7, 2026
Welcome!
Welcome to my new page. I will be sharing in the coming days.