Neal Crawford Evans, Jr.'s Professional & Home Page
About
Neal Evans, Ph.D., serves as the Chief Technology and Innovation Officer at Help Lightning, where he melds his
role as an AI Theorist with practical leadership. His work, deeply rooted in computational physics and
exemplified by his groundbreaking research on genetic algorithms in the '90s, has established him as a
front-runner in machine learning theory and application.
As an AI Theorist, Neal is dedicated to exploring the frontiers of AI, particularly the potential of quantum
machine learning, while ensuring the real-world application of AI/ML solutions are ethically aligned and
technologically innovative. His immediate focus lies in deploying AI to address complex, real-world challenges,
leveraging his extensive theoretical knowledge to produce practical, impactful results.
Beyond the realm of technology, Neal enjoys a pastoral lifestyle on his smallholding farm with his wife, Finley,
two dogs, and their flock of 13 chickens, embodying a harmonious balance between high-tech advancements and
natural simplicity.
"Optimization-Based Designs", Alexander Laskin,
D. L. Shealy, and
N. C.
Evans, Chapter 7 of
Laser Beam Shaping: Theory and Techniques, Second Edition,
edited by Fred M. Dickey (CRC Press, Boca Raton, FL, 2014).
Google
BooksAmazon
Artificial
Intelligence, Machine Learning and Their Application
to HealthCare IT
- 3/17/2011
presentation
Interview with David Karabinos on ClearCast: Conversations with
Technology Innovators and Entrepreneurs - 2007
podcast
Design of a Gradient-Index Beam Shaping System via a Genetic Algorithm Optimization Method, N. C. Evans and
D. L. Shealy. SPIE 10.1117/12.405265 (2000).
pdf
"Optimization-Based Techniques for Laser Shaping Optics", N. C.
Evans and
D. L. Shealy,
Chapter 5
of Laser Beam Shaping: Theory and Techniques, edited by
Fred M. Dickey and Scott C. Holswade (Marcel Dekker, Inc., New York,
2000).
Google
BooksAmazon
Genetic Algorithm Optimization Methods in Geometrical
Optics, N. C. Evans (Univ. of Ala. at Birmingham, Birmingham, 1999).
pdfscribd
Design and optimization of an irradiance profile shaping system
with genetic algorithm method, N. C. Evans and D. L. Shealy, Applied Optics 37.22 (1998).
Design of three-mirror telescopes via a differential equation
method, S. H. Chao, N. C. Evans,
D. L. Shealy
and R. B. Johnson, Proc. SPIE 2863-35 (1996).
pdf
SPIE '96 Denver, CO "Design of three-mirror telescopes via a
differential equation method"
SESAPS '95 Tallahassee, FL "Calculation of Irradiance Profiles for
Laser Reshaping Systems Using CODE V"
This GitHub repository contains the 'machine-learning-ga164-code-v' project, showcasing the integration of machine learning
through a genetic algorithm with CODE V for optical design optimization. The project exemplifies the use
of genetic algorithms, a key technique in machine learning, to solve complex problems in geometrical optics.