Joel Alter Greenberg

Greenberg

Associate Research Professor in the Department of Electrical and Computer Engineering

Dr. Greenberg's research is in the area of computational imaging with a focus on physics-based modeling and system-level design from fundamental science through algorithm implementation.  His work spans the electromagnetic spectrum, with a focus on X-ray and visible imaging and detection systems for security and medical applications.  

Appointments and Affiliations

  • Associate Research Professor in the Department of Electrical and Computer Engineering

Contact Information

  • Office Location: Box 90291, Dept of Ece, Durham, NC 27708
  • Office Phone: (919) 660-0183
  • Email Address: joel.greenberg@duke.edu
  • Websites:

Education

  • Ph.D. Duke University, 2012

Research Interests

Computational sensing with a focus on novel, physics-based measurement techniques for practical applications.  Primarily focused in the electromagnetic/optical spectrum ranging from ELF through visible and hard X-rays, with applications to security, non-destructive testing, and medical imaging.  Investigations range from basic science (e.g. fundamental studies in material science, optics, and information science) to applied and transitional work (e.g. design and implementation of architectures at the system level targeted at particular, real-world problems) 

Courses Taught

  • ECE 391: Projects in Electrical and Computer Engineering
  • ECE 493: Projects in Electrical and Computer Engineering
  • ECE 494: Projects in Electrical and Computer Engineering
  • ECE 899: Special Readings in Electrical Engineering

In the News

Representative Publications

  • Li, X; Greenberg, JA; Gehm, ME, Single-shot multispectral imaging through a thin scatterer, Optica, vol 6 no. 7 (2019), pp. 864-871 [10.1364/OPTICA.6.000864] [abs].
  • Gong, Q; Greenberg, JA; Stoian, RI; Coccarelli, D; Vera, E; Gehm, ME, Rapid simulation of X-ray scatter measurements for threat detection via GPU-based ray-tracing, Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions With Materials and Atoms, vol 449 (2019), pp. 86-93 [10.1016/j.nimb.2019.03.006] [abs].
  • Coccarelli, D; Hurlock, A; Royse, C; Carpenter, JH; Greenberg, JA; Johnson, E; Bosch, C; Gehm, ME, Modeling real world system geometry and detector response within a high-throughput X-ray simulation framework, Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics, vol 10999 (2019) [10.1117/12.2518870] [abs].
  • Brumbaugh, K; Royse, C; Gregory, C; Roe, K; Greenberg, JA; Diallo, SO, Material classification using convolution neural network (CNN) for X-ray based coded aperture diffraction system, Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics, vol 10999 (2019) [10.1117/12.2519983] [abs].
  • Royse, C; Wolter, S; Greenberg, JA, Emergence and distinction of classes in XRD data via machine learning, Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics, vol 10999 (2019) [10.1117/12.2519500] [abs].