Neal Crawford Evans, Jr.'s Professional & Home Page
About
Neal Crawford Evans, Jr. is an accomplished AI theorist with over 30 years of experience in machine learning, artificial intelligence, and computational physics. He has been at the forefront of integrating cutting-edge theoretical concepts with practical solutions since the early 1990s. With a strong foundation in computational physics, Evans has advanced the use of machine learning in solving highly complex problems in areas such as theoretical optics and systems design.
He holds a Ph.D. in physics with specialized research in geometrical optics and the application of genetic algorithms for optimization tasks, particularly in beam shaping and telescope design. His scholarly contributions span across numerous technical publications, conference presentations, book chapters, and software development projects.
Areas of Expertise
Theoretical Machine Learning: Development of robust algorithms grounded in rigorous mathematical foundations.
Quantum Computing: Investigating how quantum systems can accelerate AI computations and reshape algorithmic capabilities.
Ethical AI: Addressing critical questions surrounding the responsible design and deployment of AI technologies.
Applied Deep Learning: Delivering real-world AI implementations across domains including healthcare, optics, and enterprise systems.
Selected Presentations, Articles, Essays, and Books
"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.