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Postdoctoral Researcher
Aram Vajdi
Postdoctoral Research Associate
School of Data Science
Aram Vajdi is a Postdoctoral Research Associate at the University of Virginia School of Data Science. His current research focuses on developing artificial intelligence and machine learning models for the early detection of diabetes, as well as advanced control algorithms for integration into automated insulin delivery systems, in collaboration with the UVA Center for Diabetes Technology.
Vajdi holds a Ph.D. in Electrical and Computer Engineering, a Master’s degree in Experimental Atomic, Molecular, and Optical (AMO) Physics, and a Master’s degree in Theoretical Physics. Before joining UVA, he served as a Postdoctoral Research Associate in the Department of Electrical and Computer Engineering at Kansas State University (2020–2025). There, he developed high-fidelity dynamical models and custom machine learning algorithms informed by experimental and real-world data to predict and control the spread of infectious diseases, including vector-borne diseases.
An interdisciplinary researcher, Vajdi has expertise in machine learning, data science, control theory, signal processing, estimation theory, and mathematical modeling of complex biological and dynamical systems. His background also includes extensive training in experimental AMO physics and theoretical physics. In addition, Vajdi is an experienced educator in physics, computer engineering, and network science.
Education
- Ph.D., Electrical and Computer Engineering, Kansas State University
- M.S., Experimental Atomic, Molecular, and Optical Physics, Kansas State University
- M.S., Theoretical Physics, University of Kurdistan
- B.S., Physics, Razi University
Selected Publications
- Vajdi, Aram, Lee W. Cohnstaedt, and Caterina M. Scoglio. Assessing Dengue Risk Globally Using Non-Markovian Models. Journal of Theoretical Biology 591 (2024): 111865.
- Vajdi, Aram, Lee W. Cohnstaedt, Leela E. Noronha, Dana N. Mitzel, William C. Wilson, and Caterina M. Scoglio. A non-markovian model to assess contact tracing for the containment of covid-19. IEEE Transactions on Network Science and Engineering 11, no. 1 (2023): 197-211.
- Yang, Qihui, Chunlin Yi, Aram Vajdi, Lee W. Cohnstaedt, Hongyu Wu, Xiaolong Guo, and Caterina M. Scoglio. Short-term forecasts and long-term mitigation evaluations for the COVID-19 epidemic in Hubei Province, China Infectious Disease Modelling 5 (2020): 563-574.
- Vajdi, Aram , David Juher, Joan Saldaña, and Caterina Scoglio. A multilayer temporal network model for STD spreading accounting for permanent and casual partners. Scientific reports 10, no. 1 (2020): 3846.
- Vajdi, Aram, and Caterina M. Scoglio. Identification of missing links using susceptible-infected-susceptible spreading traces IEEE Transactions on Network Science and Engineering 6, no. 4 (2018): 917-927.
- Sahneh, Faryad Darabi, Aram Vajdi, Joshua Melander, and Caterina M. Scoglio. Contact adaption during epidemics: A multilayer network formulation approach. IEEE Transactions on Network Science and Engineering 6, no. 1 (2017): 16-30.
- Rudenko, Artem, Varun Makhija, Aram Vajdi, Thorsten Ergler, Markus Schürholz, Rajesh K. Kushawaha, Joachim Ullrich, Robert Moshammer, and Vinod Kumarappan. Strong-field-induced wave packet dynamics in carbon dioxide molecule. Faraday Discussions 194 (2016): 463-478.
- Ren, Xiaoming, A. M. Summers, Aram Vajdi, Varun Makhija, C. W. Fehrenbach, Nora G. Kling, K. J. Betsch et al. Single-shot carrier-envelope-phase tagging using an f–2f interferometer and a phase meter: a comparison. Journal of Optics 19, no. 12 (2017): 124017.
- Saaidi, Kh, A. Vajdi, and A. Aghamohammadi. Static spherically symmetric solution of (𝑅±𝜇^4/𝑅) gravity. General Relativity and Gravitation 42, no. 10 (2010): 2421-2429.