Information Processing
& Algorithms Laboratory

everything can be optimized

ABOUT

The Information Processing and Algorithms Laboratory (iPAL) is directed by Prof. Vishal Monga. Graduate research in iPAL focuses on convex and non-convex optimization methods in learning, vision and signal processing. Our particular interest is in estimation frameworks where domain inspired prior knowledge is captured. This invariably leads to challenging optimization problems for which we develop new tractable solutions that facilitate a favorable performance-complexity trade-off.

NEWS

CVPR 2022!
GlideNet for Multi-Category Attributes Prediction

Attaching attributes (such as color, shape, state, action) to object categories is an important computer vision problem. Attribute prediction has seen exciting recent progress and is often formulated as a multi-label classification problem. Yet significant challenges remain in: 1) predicting a large number of attributes over multiple object categories, 2) modeling category-dependence of attributes, 3) methodically capturing both global and local scene context, and 4) robustly predicting attributes of objects with low pixel-count ... Read More

New tutorial at 2021 IEEE RadarCon

Convex Optimization for Adaptive Radar.
For more details about iPAL research in radar systems click here.

NEW! Feature Article in IEEE Signal Processing Magazine

Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing by V. Monga, Y. Li and Y. Eldar.
The article can be found here.

NEW! Handbook of Convex Optimization Methods in Imaging Science

This book discusses 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.

RESEARCH AREAS

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Medical & Computational Imaging
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Sparsity Constrained & Robust Time-series Signal Estimation
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Radar Signal Processing
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Regularized Deep Networks

KEY RESEARCH COLLABORATORS

Academia

Prof. Yonina Eldar (Weizmann Institute, Israel) and 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 (Prev. Xerox PARC, Now Amazon)

KEY RESEARCH SPONSORS

Email
ipal.psu@gmail.com

Address
104 Electrical Engineering East,
University Park, PA 16802, USA

Lab Phone:
814-863-7810
814-867-4564