- Research areas: Artificial Intelligence Assurance, Intelligent Water Systems, Cyberbiosecurity, Context and Causality, AI for Agricultural Policy
M.Sc., Computer Engineering, University of Central Florida, 2007
Ph.D., Computer Engineering, University of Central Florida, 2011
Pg.C., Project Leadership, Cornell University, 2016
JM, Law, George Mason University, 2022
ECE 5994/7994: Graduate Research (VT) Fall 2021, Spring 2022.
CDS 302: Scientific Data and Databases (GMU) Fall 2020.
ANLY 503: Scientific and Analytical Visualization (Georgetown U) Fall 2019.
ANLY 501: Introduction to Data Analytics (Georgetown U) Fall 2019.
DATA 601: Introduction to Data Science (UMBC) Fall 2018, Spring 2019.
CDS 301/501: Scientific Information and Data Visualization (GMU) Fall 2017, 2018.
CSCI 6461: Computer Architecture Design (GWU) Spring 2017.
SWE 632: User Interface Design and Development (GMU) Spring/Fall 2016, 2017, 2019.
My research spans the areas of artificial intelligence (AI) and cyberbiosecurity for water systems and smart agriculture. My team and I develop AI applications and assurance algorithms to address persisting water security and agricultural public policy challenges, such as: analyzing international ag trade, protecting water supply systems, optimizing smart-farming and precision agriculture, and understanding the economic effects of outlier events on biological systems (such as rivers and watersheds) using data-driven methods. However, throughout these AI deployments, serious show-stopper problems are persistent, such as: AI explainability, security, causality, and trustworthiness; as well as data bias and incompleteness, data democracy, and dark data. My research is at the intersection of these issues.
[Book] Batarseh, F., and Freeman, L., “AI Assurance: Towards Valid, Explainable, Fair, and Ethical AI” Upcoming with Elsevier's Academic Press, October 2022. Link
[Book] Batarseh, F., and Yang, R., “Data Democracy: At the Nexus of Artificial Intelligence, Software Development, and Knowledge Engineering”, Published by Elsevier's Academic Press, ISBN: 9780128183663, Jan 2020. Link
[Book] Batarseh, F., and Yang, R., “Federal Data Science: Transforming Government and Agricultural Policy using Artificial Intelligence”, Published by Elsevier's Academic Press, ISBN: 9780128124437, Oct 2017. Link