linkedin-icon.png researchgate-icon.png googlescholar-icon.png orcid_16x16.png github_logo_icon.png codepen_01.png Matlab_Logo.png

VIVA Affiliation

  • Research Scientist (2014 - Present)
  • Graduate Research Assistant (2011 - 2014)

UVA Affiliation

  • Adjunct Instructor (2016 - Present)


  • Ph.D. Electrical Engineering, University of Virgina, 2014
  • Laurea Magistrale (M.Sc.) summa cum laude Physics, UniversitÓ degli Studi di Milano (Italy), 1996

Biographical Sketch (CV)

2016- . Adjunct Instructor at the Electrical and Computer Engineering Department - University of Virginia

2014- . Research Scientist at VIVA

2014 . Received his Ph.D. in Electrical Engineering from the University of Virginia with a dissertation titled "An Automated Image Analysis Framework for Model-Based Feature Detection in Sparse Data"

2011 . Joined the VIVA group at University of Virginia.

1998-2012 . Electronics Engineer at the National Radio Astronomy Observatory (NRAO). There he worked on the design, development and construction of the Atacama Large Millimeter Array (ALMA). In particular he was responsible for the design, development and production of the ALMA Front End embedded monitor and control system. He also worked on the development of the ALMA Central Local Oscillator Article (CLOA) and the design of coplanar, self-similar, log-periodic structures for quasi-optical injection of tunable reference signals up to 1THz.

1996-1998 . Research Assistant at the Relativistic Astrophysics and Cosmology Group at the Physics Department of the UniversitÓ degli Studi di Milano where his areas of research included the characterization of the magnetic behavior of SIS junctions and the design of quasi-optical mixer couplings for SIS receivers up to 345GHz.

1996 . Andrea received his M.Sc. in Physics (summa cum laude) from the UniversitÓ degli Studi di Milano with a thesis titled "Development of Superconductor-Insulator-Superconductor (SIS) Mixers for Astrophysical Observations".


Research Interests

My research focuses on model-based analysis of images, stack of images, videos, and spatiotemporal point cloud datasets. The fundamental goal of my work is to provide detection, tracking, and analysis of objects or events within these large datasets to both extract and analyze their salient features, and to achieve a better characterization and understanding of their behavior. I have successfully applied these techniques to remote sensing imagery and currently, I am extending this approach to biological, microscopy, civil engineering, and astronomical imagery. From a theoretical point of view, I am exploring how this type of analysis can be extended to the emerging field of graph signal processing to allow the detection and characterization of specific spatiotemporal behaviors within large datasets that benefit from being represented as graphs.


Projects related: InSAR

Please also refer to my Google scholar page


QR [vCard]


Topic revision: r33 - 21 Mar 2017, AndreaVaccari
©2017 University of Virginia. Privacy Statement
Virginia Image and Video Analysis - School of Engineering and Applied Science - University of Virginia
P.O. Box 400743 - Charlottesville, VA - 22904 - E-Mail