Robert Calderbank
robert.calderbank@duke.eduCharles S. Sydnor Distinguished Professor of Computer Science
Charles S. Sydnor Distinguished Professor of Computer Science
Applied statistics and machine learning
Visiting Assistant Professor in the Department of Electrical and Computer Engineering
Physics-based machine learning algorithms for big data, including developing remediation strategies for the hearing impaired and sensor-based algorithms for the detection of hazardous buried objects
Director of Undergraduate Studies, Associate Professor of the Practice of ECE
Computational methods for image analysis and information extraction, discrete event simulations, curriculum development and deployment
Associate Dean of Undergraduate Education, Edmund T. Pratt, Jr. School Professor of the Practice of ECE
Engineering education, pedagogy and curriculum development, applications of statistical signal processing
Physics-based and statistical signal processing, sensor array processing, radar and sonar systems, pervasive distributed processing
Randolph K. Repass and Sally-Christine Rodgers University Distinguished Professor of Conservation Technology in Environment and Engineering
Marine mammal behavioral and acoustic ecologyOcean noiseOffshore renewable energy
Jeffrey N. Vinik Associate Professor of Electrical and Computer Engineering
Information theory, communications, probabilistic graphical models, machine learning, and deep neural networks
Associate Professor in the Department of Electrical and Computer Engineering
Information theory, high-dimensional statistical inference, statistical signal processing, compressed sensing, machine learning
Professor in the Department of Electrical and Computer Engineering
Gilbert, Louis, and Edward Lehrman Distinguished Professor
Bell-Rhodes Associate 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.