Research Interests
Theoretical, computational, and experimental investigation of electromagnetic metamaterials and metasurfaces, with a focus on artificial intelligence, deep / machine learning, with application to spectroscopy, computational…
Theoretical, computational, and experimental investigation of electromagnetic metamaterials and metasurfaces, with a focus on artificial intelligence, deep / machine learning, with application to spectroscopy, computational…
Director of Master's Studies, Professor in the Department of ECE
Design and analysis of autonomous cyber-physical systems (CPS), and in particular, embedded systems, AI, learning and controls, CPS security and high-assurance autonomy, with various application…
Assistant Professor of the Practice in the Department of Electrical and Computer Engineering
Software Engineering and Data ManagementArtificial IntelligenceMachine LearningPrivacy in MLCybersecurityComputer Engineering Education
Information theory, communications, probabilistic graphical models, machine learning, and deep neural networks
Assistant Professor of the Practice in the Department of Electrical and Computer Engineering
Compilers, High-Performance Computing, Compute Clusters, Distributed Systems, Data Center Networks
Associate Professor in the Department of Electrical and Computer Engineering
Information theory, high-dimensional statistical inference, statistical signal processing, compressed sensing, machine learning
Prof. Reiter's research interests include all areas of computer and communications security, fault-tolerant distributed computing, and applied cryptography.
Professor in the Department of Electrical and Computer Engineering
Adjunct Assistant Professor in the Department of Electrical and Computer Engineering
Energy-efficient electronicsTwo-dimensional materialsNeuromorphic ComputingOptoelectronicsWide bandgap materialsHigh power electronicsRadiation effects and reliability
Gilbert, Louis, and Edward Lehrman Distinguished Professor
VP/GM, Data Analytics, Google
Reed and Martha Rice Distinguished Professor of Radiology
Dr. Samei’s scientific expertise includes x-ray imaging, theoretical imaging models, simulation methods, and experimental techniques in medical image formation, quantification, and perception. His research aims…
James B. Duke Distinguished Professor Emeritus of Electrical and Computer Engineering
Image and video processing, computer vision, computer graphics, computational vision, biomedical imaging, brain imaging, cryo-tomography of viruses, computational tools in cryo-tomography, computational tools in early…
Cosmology, Supernova.
Director of Software Engineering, Garmin
Drug discoveries have been instrumental in improving global health over the last century, but the median drug now takes about 10 years to bring to…
James B. Duke Distinguished Professor of Electrical and Computer Engineering
Theory, simulation and demonstration of novel electromagnetic metamaterials across the spectrum, from microwave through optical. Applications of metamaterials for antennas and imaging devices, with a…
Computer architecture, designing microarchitectures so that they are easier to verify, improving computer system fault tolerance, developing memory systems for multicore processors, and designing special-purpose…
Visiting Professor in the Department of Electrical and Computer Engineering
Duke MS/PhD '09
President & CEO, Kyma Technologies
Associate Dean for Community-Based Innovation, Professor of ECE
Thin-film deposition, MAPLE, hybrid perovskites, hybrid nanocomposites, organic thin films
Research Professor in the Department of Electrical and Computer Engineering
Bell-Rhodes Professor of the Practice of Electrical and Computer Engineering
Physics-based statistical signal processing • Context-aware machine learning • Domain-informed data scienceExplainable/interpretable machine learning • Privacy-aware machine learning • Bias in machine learningNeuroscience-informed teaching •…
Rhodes Family Distinguished Professor of Electrical and Computer Engineering
Foundations of AI, Foundations of Signal Processing, Learning Representations, Transfer Learning, Meta-Learning, Physics Infused Learning, Extreme Value Theory, Dependence Modeling, Hypothesis Testing, Sequential Analysis.