Dr. Marjorie Darrah is Professor of Mathematics at WVU. She has 25 years experience teaching at the university level, and has led three National Science Foundation projects connecting students and teachers to cutting edge technology and making a smooth pathway to IT careers. She also had funding from the US Department of Education, SBIR program to develop new products incorporating haptic touch technology that allows a person to touch and interact with a virtual object.
Her research also includes the development and implementation of biologically inspired algorithms (Artificial Neural Networks and Genetic Algorithms). She has been involved in the development, implementation and field testing of genetic algorithms that coordinate missions using multiple unmanned aerial vehicles (UAVs). In this area she has had funding from both Army Research Labs and Air Force Research Labs. She is currently working on a NASA project using Neural Networks to do health monitoring of UAV systems to avoid system degradation or failure. She was named on a patent for this system INTELLIGENT ELECTRONIC SPEED CONTROLLER (IESC), Publication number: 20180307231. She has also conducted over 20 project evaluations, specializing in evaluation of educational technologies and educational programs.
WEST VIRGINIA UNIVERSITY
1995 PH. D. MATHEMATICS
1991 M.S. MATHEMATICS
Graduated summa cum laude
FAIRMONT STATE COLLEGE
1989 B.S. MATHEMATICS
1988 B.A. Education, Comprehensive Mathematics 7-12
Graduated summa cum laude
Courses offered at WVU:
- Math 150 Applied Calculus
- Math 153/154 Calculus with Pre-Calculus
- Math 375 Applied Modern Algebra
- Math 283 Introduction to Concepts of Mathematics
- Math 593 Neural Network Rule Extraction
- Artificial Neural Networks
- Neural Network Rule Extraction and Rule Insertion
- Genetic Algorithms
- Haptic Technology for Education
- Program and Project Evaluation
Darrah, M., Sorton, E., Wathen,
M. and Mera Trujillo, M. (2016). Real-time Tasking and
Retasking of Multiple Coordinated UAVs. Defense Systems Information Analysis Center Journal, 3(4) pp. 21-26.
Rahem, M. A., Darrah, M. (2018).
Using a Computational Approach for Generalizing
a Consensus Measure to Likert Scales of Any
Size n. International Journal of
Mathematics and Mathematical Sciences. Volume 2018, Article ID 5726436. https://doi.org/10.1155/2018/5726436
Darrah, M., Rubenstein, A., Sorton, E. and DeRoos, B. (2018). On-board Health-state Awareness to Detect Degradation in Multirotor Systems. In Proceedings of 2018 International Conference on Unmanned Aircraft Systems (ICUAS), Dallas, TX, USA, 2018.
Elsarrar, O., Darrah, M. and Devin, C. (2019). Analysis of Forest Fire Data using Neural Network Rule Extraction with Human Understandable Rules. In Proceedings of IEEE/ICMLA 18th International Conference on Machine Learning and Applications, Boca Raton, FL, USA, 2019.
Darrah, M., Trujillo, M. M.,
Speransky, K. and Wathen, M. (2017). Optimized 3D mapping of a large area with structures
using multiple multirotors. In Proceedings
of 2017 International Conference on Unmanned Aircraft Systems (ICUAS),
Miami, FL, USA, 2017,pp. 716-722. doi:
Dr. Darrah's CV