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Professor Al Bovik (HonFRPS) is is the Provost's Chair Professor in the Department of Electrical, Computerm, and Energy Engineering (ECEE) at the 91ɫ��, where he is Director of Colorado's Laboratory for Image and Video Engineering (LIVE).  His research interests include digital television, digital photography, visual perception, social media, and image and video processing.

His work broadly focuses on creating new theories and algorithms that allow for the perceptually optimized streaming and sharing of visual media. The outcomes of his work have the benefits of ensuring the visual satisfaction of billions of viewers worldwide, while substantially reducing global bandwidth consumption.

He has published over 1,000 technical articles in these areas and holds many U.S. patents. His publications have been cited nearly 200,000 times in the literature, his H-index is above 140, and he is listed as a Highly-Cited Researcher by The Web of Science Group. His several books include the The Handbook of Image and Video Processing (Academic Press, 2000, 2005), Modern Image Quality Assessment (2006), and the companion volumes The Essential Guides to Image and Video Processing (Academic Press, 2009).

Prof. Bovik is  "for contributions to the development of tools for image and video quality assessment." He is also a member of the , an , and a member of the .

Dr. Bovik has received a number of major international awards. These include:

• The 2024 for “foundational contributions to the theoretical and engineering aspects of perceptual picture and video quality prediction, leading to systems that ensure optimized visual quality for hundreds of millions of viewers daily.” Since 1902 the John Fritz Medal is presented each year for scientific or industrial achievement in any field of pure or applied science.
• The "for pioneering high-impact scientific and engineering contributions leading to the perceptually optimized global streaming and sharing of visual media.” The Edison Medal is given "for a career of meritorious achievement in electrical science, electrical engineering, or the electrical arts." It is the oldest and most prestigious medal in this field of engineering, having been presented since 1909.
• A for the "development of perceptual metrics for video encoding optimization." This award, which is Television’s highest honor, is only bestowed upon an individual, company or organization for developments in engineering that are either “so extensive an improvement on existing methods, or so innovative in nature, that they materially affect the transmission, recording or reception of television.”
• "in recognition of any invention, research, publication or other contribution which has resulted in an important advance in the scientific or technological development of photography or imaging in the widest sense." The Progress Medal is the oldest and most prestigious honor in the field of photography, having been given annually since 1878.
• The  “For seminal contributions and high-impact innovations to the theory and application of perception-based image and video processing.” This Technical Field Award and medal is one of the highest honors accorded by the 423,000-member IEEE.
• The “For substantially shaping the direction and advancement of modern perceptual image quality theory, and for energetically engaging industry to transform his ideas into global practice.”
• A (The Television Academy) in October 2015, for his work on the development of video quality prediction models which have become standard tools in broadcast and post-production houses throughout the television industry. This award, which is Television’s highest honor, is only bestowed upon an individual, company or organization for developments in engineering that are either “so extensive an improvement on existing methods, or so innovative in nature, that they materially affect the transmission, recording or reception of television.”

He has also received a number of other major awards from the IEEE Signal Processing Society, including the Norbert Wiener Society Award, ICIP Pioneer Award, the Sustained Impact Award, the Claude Shannon-Harry Nyquist Technical Achievement Award, the Carl Friedrich Gauss Education Award, and the Leo L. Beranek Meritorious Service Award. He has also received about 10 Best Journal Paper Awards from the IEEE and EURASIP.

He is a Life Fellow of the IEEE, a Fellow of the Optical Society of America (OSA) and the Society of Photo-Optical and Instrumentation Engineers (SPIE), and is an Honorary Fellow of the Royal Photographic Society (HonFRPS). He is a voting member of the Television Academy (ATAS) and a member of the National Academy of Television Arts and Sciences (NATAS). He co-founded and was the longest-serving Editor-in-Chief of the IEEE Transactions on Image Processing (1996-2002), and created and served as the first General Chair of the IEEE International Conference on Image Processing, held in Austin, Texas, in November, 1994.

We develop theory and invent technologies for intelligent wireless communications. Recent research interests:

• Machine Learning for Intelligent Communications
• Optimization of (massive) MIMO interference networks;
• Information theory and coding;
• Synchronization algorithms;
• Machine learning aided wireless communication;
• Software defined radio (SDR) to transfer our research to real world systems;
• Characterization of random networks using stochastic geometry;
• Performance analysis of communication systems with feedback.

Peter Mathys and his group work at the intersection of communication and coding theory and practical implementations using software-defined radio (SDR), digital signal processing (DSP), and machine learning (ML). Of particular interest is the combination of SDRs and ML to create intelligent radio networks that are capable of sharing the radio frequency (RF) spectrum, which is a finite natural resource, in novel and more efficient ways. Another more interdisciplinary application of wireless communications, SDR and DSP for medical purposes is the design and implementation of passive implants that are powered by RF energy while at the same time receiving and transmitting bio-sensing data wirelessly.

Mahesh Varanasi and his group work in the areas of information theory, wireless communications and detection/estimation theory. Their focus at this time is on developing fundamental understanding of, and methods for, efficient and reliable transmission of data over networks. Of particular interest are networks that incorporate protocols to enable advanced features such as multiple-antenna terminals, cooperation and relays, cognition, spectrum sensing, simultaneous multiple groupcasting, security, privacy and feedback. Network topologies include small-to-large-scale single-cell, multi-cell, interference and relay networks, multihop-multiflow networks and cache networks. Information theoretic limits of such networks as well as the development of optimal and near-optimal methods are of interest as is the study of combinatorial and other structure of solutions and algorithms for their efficient computation.