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Navid NaderiAlizadeh

Assistant Research Professor of Biostatistics & Bioinformatics
Biostatistics & Bioinformatics, Division of Integrative Genomics
2424 Erwin Road, 2721, Durham, NC 27705
2424 Erwin Road, 2721, Durham, NC 27705

Overview


Navid NaderiAlizadeh is an Assistant Research Professor in the Department of Biostatistics and Bioinformatics at Duke University. Prior to that, he was a Postdoctoral Researcher %in the Department of Electrical and Systems Engineering at the University of Pennsylvania. Navid’s current research interests span the foundations of machine learning, artificial intelligence, and signal processing and their applications in developing novel methods for analyzing biological data. Navid received the B.S. degree in electrical engineering from Sharif University of Technology, Tehran, Iran, in 2011, the M.S. degree in electrical and computer engineering from Cornell University, Ithaca, NY, USA, in 2014, and the Ph.D. degree in electrical engineering from the University of Southern California, Los Angeles, CA, USA, in 2016. Upon graduating with his Ph.D., he spent four years as a Research Scientist at Intel Labs and HRL Laboratories.

Current Appointments & Affiliations


Assistant Research Professor of Biostatistics & Bioinformatics · 2023 - Present Biostatistics & Bioinformatics, Division of Integrative Genomics, Biostatistics & Bioinformatics

Recent Publications


Black-box Optimization of CT Acquisition and Reconstruction Parameters: A Reinforcement Learning Approach.

Journal Article Proc SPIE Int Soc Opt Eng · February 2025 Protocol optimization is critical in Computed Tomography (CT) for achieving desired diagnostic image quality while minimizing radiation dose. Due to the inter-effect of influencing CT parameters, traditional optimization methods rely on the testing of exha ... Full text Link to item Cite

Learning State-Augmented Policies for Information Routing in Communication Networks

Journal Article IEEE Transactions on Signal Processing · January 1, 2025 This paper examines the problem of information routing in a large-scale communication network, which can be formulated as a constrained statistical learning problem having access to only local information. We delineate a novel State Augmentation (SA) strat ... Full text Cite
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Education, Training & Certifications


University of Southern California · 2016 Ph.D.
Cornell University · 2014 M.S.E.E.
Sharif University of Technology (Iran) · 2011 B.S.E.E.