IEEE Awards Booklet - 2020 - 12


IEEE Jack S. Kilby Signal
Processing Medal

IEEE Jun-ichi Nishizawa Medal
Sponsored by the Federation of
Electric Power Companies, Japan

Sponsored by Texas Instruments, Inc.

Ramalingam Chellappa

Paul Daniel Dapkus

For contributions to image and video
processing, especially applications to
face recognition

For the development of metal organic
chemical vapor deposition and quantum
well lasers

A pioneer in developing image, video, and multidimensional signal processing theory and methods for solving image processing,
computer vision, and pattern recognition problems, Ramalingam
Chellappa has profoundly affected the development of systems
for face recognition and verification, image and video synthesis
and analytics, real-time action detection, and active authentication. During the 1980s, Chellappa developed groundbreaking parameter estimation and neighborhood selection rules for Markov
random field (MRF) models and developed algorithms for image restoration, texture analysis, and segmentation using MRFs.
His linear discriminant analysis-based algorithm developed during the 1990s pioneered discriminative methods for training face
recognition systems. Chellappa has also been active in creating
tools for 3D recovery from one or more images using discrete and
continuous methods. The Frankot-Chellappa algorithm was developed for extracting integrable 3D surfaces from a single image.
He pioneered the area of video-based 3D modeling algorithms
using batch and recursive estimation methods. He was also an early contributor to neural networks for image processing and computer vision applications. His recent work in this area includes
deep-learning-based face, object, and activity recognition systems
and methods that combat attacks against classification systems.
Specifically, he has developed deep convolution neural network
(DCNN)-based algorithms to help overcome the problems of
aging, pose, and illumination, affecting accurate face recognition
and providing results that rivaled human performance. His work
on the HyperFace and UltraFace algorithms resulted in programs
that perform not only face detection and classification but also
gender recognition and age and pose estimation.The end-to-end
system built by his group has been used for child exploitation/
crime prevention and other U.S. homeland security applications.
An IEEE Life Fellow and recipient of the 2012 K.S. Fu Prize
from the International Association for Pattern Recognition,
Chellappa is a Distinguished University Professor with the Electrical and Computer Engineering Department at the University
of Maryland, College Park, MD, USA.

Paul Daniel Dapkus' pioneering efforts in realizing metal organic
chemical vapor deposition (MOCVD) as a viable fabrication process and using it to develop quantum well (QW) lasers have resulted
in the most efficient light sources for applications ranging from
telecommunications and optical data storage to high-power industrial processes. MOCVD was developed in 1967, but no devices
were created with it until after Dapkus and his team at the Rockwell International Electronics Research Center demonstrated that
MOCVD growth technology was capable of producing high-quality layered semiconductor material in 1977.This was at a time when
MOCVD was shunned as being not useful compared to molecular
beam epitaxy (MBE) or liquid phase epitaxy (LPE). However, his
group demonstrated high-performance solar cells and lasers, including ultrathin active regions that led to the first electrically driven
QW lasers. MOCVD has since become the dominant technique
for production of laser diodes and LEDs as well as photonic devices
used in fiber-optic communications systems. His development of
strained QW ultralow threshold semiconductor lasers, particularly
his work on vertical cavity QW lasers, has led to their very rapid
adoption in fiber-optic systems, often as the light source of choice
for making low-cost data links. In 1982, Dapkus established a research group at the University of Southern California, where he has
continued leading research on advancing the technology of QW
devices through MOCVD. His research focuses on high-efficiency,
low-threshold lasers; vertical cavity surface emitting lasers; and indium phosphide-based QW lasers at 1330 and 1550 nm wavelengths.
Dapkus' contributions have also been implemented as key products
in the diode-pumped fiber laser industry where CO2 lasers used
for cutting and welding steel and aluminum have been replaced by
MOCVD-grown diode lasers.
An IEEE Fellow, a member of the National Academy of Engineering and recipient of both the IEEE David Sarnoff Award (2001)
and the John Tyndall Award(2015), Dapkus is the William M. Keck
Distinguished Professor of Engineering and professor of electrical
engineering and physics and astronomy at the University of Southern California, Los Angeles, CA, USA.

Scope: For outstanding achievements in signal processing.

Scope: For outstanding contributions to material and device science and technology, including practical application.



IEEE Awards Booklet - 2020

Table of Contents for the Digital Edition of IEEE Awards Booklet - 2020

Table of Contents
IEEE Awards Booklet - 2020 - Cover1
IEEE Awards Booklet - 2020 - Cover2
IEEE Awards Booklet - 2020 - 1
IEEE Awards Booklet - 2020 - 2
IEEE Awards Booklet - 2020 - 3
IEEE Awards Booklet - 2020 - 4
IEEE Awards Booklet - 2020 - Table of Contents
IEEE Awards Booklet - 2020 - 6
IEEE Awards Booklet - 2020 - 7
IEEE Awards Booklet - 2020 - 8
IEEE Awards Booklet - 2020 - 9
IEEE Awards Booklet - 2020 - 10
IEEE Awards Booklet - 2020 - 11
IEEE Awards Booklet - 2020 - 12
IEEE Awards Booklet - 2020 - 13
IEEE Awards Booklet - 2020 - 14
IEEE Awards Booklet - 2020 - 15
IEEE Awards Booklet - 2020 - 16
IEEE Awards Booklet - 2020 - 17
IEEE Awards Booklet - 2020 - 18
IEEE Awards Booklet - 2020 - 19
IEEE Awards Booklet - 2020 - 20
IEEE Awards Booklet - 2020 - 21
IEEE Awards Booklet - 2020 - 22
IEEE Awards Booklet - 2020 - 23
IEEE Awards Booklet - 2020 - 24
IEEE Awards Booklet - 2020 - 25
IEEE Awards Booklet - 2020 - 26
IEEE Awards Booklet - 2020 - 27
IEEE Awards Booklet - 2020 - 28
IEEE Awards Booklet - 2020 - 29
IEEE Awards Booklet - 2020 - 30
IEEE Awards Booklet - 2020 - 31
IEEE Awards Booklet - 2020 - 32
IEEE Awards Booklet - 2020 - Cover3
IEEE Awards Booklet - 2020 - Cover4