• About

The Information Processing and Algorithms Laboratory (iPAL) is directed by Prof. Vishal Monga. Graduate research in iPAL broadly encompasses signal and image processing theory and applications with a particular focus on capturing practical real-world constraints via convex optimization theory and algorithms. Active areas include: a.) image analysis and classification esp. for medical images, b.) computational imaging and vision, c.) robust signal (time-series) hashing, and d.) radar signal processing. Please click on tabs above for more information about iPAL members and current research.

Key Recent Research Collaborators:

  • Academia:
    Prof. Trac Tran (Johns Hopkins University).
  • Government Labs: Dr. Muralidhar Rangaswamy (US Air Force Research Laboratory), Dr. Nasser Nasrabadi (US Army Research Laboratory, now West Virginia University)
  • Industry: Dr. Raja Bala (Xerox PARC).

Research Sponsorship

We are thankful to industry as well as federal sponsors for their support: NSF (including the CAREER award), NIH, ONR, AFOSR, ARO, Xerox Corporation, Nokia Corporation, Lockheed Martin, Pennsylvania Department of Agriculture.

If you're an industrial lab/group looking to partner with my group, I invite you to contact me via phone/email and be aware of Penn State's flexibility in IP policies to enable greater mutual success.

  • Quick Links:
Department of Electrical Engineering
Pennsylvania State University
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This book discusses recent developments in imaging science and provides tools for solving image processing and computer vision problems using convex optimization methods. Throughout the handbook, the authors introduce topics on the most key aspects of image acquisition and processing that are based on the formulation and solution of novel optimization problems.

Recent projects include Regularized Deep Networks which strengthen deep networks with domain knowledge.

Prof. Monga with iPAL student members, October 2016
  • Address:
104 Electrical Engineering East,
University Park, PA 16802, USA
  • Lab Phone:

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