Women in Computational Intelligence

ALICE E. SMITH is the Joe W. Forehand/Accenture Distinguished Professor of the Industrial and Systems Engineering Department at Auburn University, where she served as Department Chair from 1999-2011.  She also has a joint appointment with the Department of Computer Science and Software Engineering.  Previously, she was on the faculty of the Department of Industrial Engineering at the University of Pittsburgh from 1991-99, which she joined after industrial experience with Southwestern Bell Corporation.  Dr. Smith has degrees from Rice University, Saint Louis University, and Missouri University of Science and Technology.  Dr. Smith’s research focus is analysis, modeling, and optimization of complex systems with emphasis on computation inspired by natural systems.  She holds one U.S. patent and several international patents and has authored more than 200 publications which have garnered over nearly 13,000 citations and an H Index of 47 (Google Scholar) and nearly 5,000 citations and an H Index of 29 (Web of Science).  Dr. Smith is the Editor in Chief of INFORMS Journal on Computing and an Area Editor of Computers & Operations Research.  Dr. Smith has been a principal investigator on over $10 million of sponsored research with funding by NASA, U.S. Department of Defense, Missile Defense Agency, National Security Agency, NIST, U.S. Department of Transportation, Lockheed Martin, Adtranz (now Bombardier Transportation), the Ben Franklin Technology Center of Western Pennsylvania, and U.S. National Science Foundation, from which she has been awarded 18 distinct grants including a CAREER grant in 1995 and an ADVANCE Leadership grant in 2001.  In 2017, she received the inaugural Auburn University 100 Women Strong Leadership in Diversity Faculty Award.  Dr. Smith was awarded the Wellington Award in 2016, the IIE Albert G. Holzman Distinguished Educator Award in 2012, and the INFORMS WORMS Award for the Advancement of Womenin OR/MS in 2009.  Dr. Smith is a fellow of the Institute of Industrial and Systems Engineers (IISE), a fellow of the Institute of Electrical and Electronics Engineers (IEEE), a senior member of the Society of Women Engineers, a member of Tau Beta Pi and the Institute for Operations Research and Management Science (INFORMS), and a Registered Professional Engineer in Alabama and Pennsylvania.  She served as associate editor for two IEEE journals and is currently an IEEE Computational Intelligence Society Distinguished Lecturer and an INFORMS Official Speaker.  She was named a 2020 Yellowhammer Women of Impact (20 women are honored each year in the State of Alabama https://alabamawomen.org/#2020 ) and was named an INFORMS Diversity, Equity, and Inclusion Ambassador in 2021.

• Chapter 1. Amazing Grace – Computer Pioneer Admiral Grace Murray Hopper.- Chapter 2. XAI: A Natural Application Domain for Fuzzy Set Theory .- Chapter 3. Adaptive Physiological Profiling from Non-verbal Behaviour – Why Ethics are Just Not Enough to Build Trust.- Chapter 4. Conversational Intelligent Tutoring Systems - The State of the Art.- Chapter 5. Design and Validation of a Mini-game for Player Motive Profiling.- Chapter 6. When AI Meets Digital Pathology.- Chapter 7. Linguistic Intelligence as a Root for Computing Reasoning.- Chapter 8. Intrusion Detection: Deep Neural Networks versus Super Learning.- Chapter 9. Life-Long Learning Machines: Towards Developing Optimisation Methods That Continually Learn.- Chapter 10. Reinforcement Learning Control by Direct Heuristic Dynamic Programming.- Chapter 11. Distributed Machine Learning for Energy Management and Control in Smart Grid.- Chapter 12. Fuzzy Multilayer Perceptrons for Fuzzy Vector Regression.- Chapter 13. Generalisation in Genetic Programming for Symbolic Regression: Challenges and Future Directions.- Chapter 14. Neuro-evolutionary Models based on Quantum-Inspired Evolutionary Algorithms.- Chapter 15. Weightless Neural Models: An Overview.- Chapter 16. Challenges of Applying Dynamic Multi-objective Optimization to Real-world Problems.- Chapter 17. Computational Intelligence Methodologies for Multi-Objective Optimization and Decision-Making in Autonomous Systems.- Chapter 18. A Framework-Based Approach for Flexible Evaluation of Swarm-Intelligent Algorithms.- Chapter 19. An Improved Bat Algorithm with a Dimension-based Best for Numerical Optimization.