Research

A3 Research in the News

AI for Water (ACWA): Video & News Article

ACWA Lab Featured in the WE&T Magazine: News Article

AI Assurance Book Featured in the Guardian Newspaper: News Article

AlexRenew Partnership: News Article

Government Market News: Article on A3 Lab

AI in AR Research: Video

A3 is a Founding Member and Partner with the Ag-ISAC: Announcement

Tech on Tap Event: Video

Cyber Bootcamp: Video

DC Water Partnership: Video

Selected Publications

1. Books

2. Conference & Journal Papers

• Kulkarni, A., Wang, Y., Munisamy, G., Sobien, D., Rahman, A., and Batarseh, F., “A Review of Cybersecurity Incidents in the Food and Agriculture Sector”, arXiv, doi: 2403.08036, pre-print Apr 2024. Link
• Jeong, S., Munisamy, G.C, Kulkarni, A.P, and Batarseh, F., “Deploying Machine Learning Methods to Predict Global Trade Patterns: The Case of Beef”, Journal of the ASABE, In collection: Cyberbiosecurity: Securing Water and Agricultural Systems, 2023, doi.org/10.13031/ja.15619. Link
• Adeoye, S.G, Batarseh, F., Brown, A., Kaufman, E. C & G, “Understanding the Landscape of Cyberbiosecurity for Integrative Educational Programming”, Journal of the ASABE, In collection: Cyberbiosecurity: Securing Water and Agricultural Systems, 2023, doi.org/10.13031/ja.15597. Link
• Khadka, S., Gopinath, M., and Batarseh, F., “Anomalies in agricultural trade: A Bayesian classifier approach”, Journal of the Agricultural and Applied Economics Association, Vol. 2, Issue 3, doi: 10.1002/jaa2.69, 2023, pp. 402-427. Link
• Kaufman, E., Adeoye, S., and Batarseh, F., “Leadership for CyberBioSecurity: The Case of Oldsmar Water”, A case narrative pre-printed in Vtech Works, 2023. Link
• Huang, C-H., Mohandas, N., Raj, A., Howard, S., and Batarseh, F. “Data-driven healthcare indicators via precision gaming: With application to India”, Data & Policy, 2024; 6:e22. doi:10.1017/dap.2024.16. Link
• Khadka, S., Gopinath, M., and Batarseh, F., “Shifting Alliances – Friendshoring in Agricultural Trade”, Proceedings of the International Agricultural Trade Research Consortium’s (IATRC’s) 2023 Annual Meeting, Clearwater Beach, FL, Dec 2023. Link
• Lin, J., Sreng, C., Oare, E., and Batarseh, F., "NeuralFlood: an AI-driven flood susceptibility index", Front. Water, Sec. Water and Artificial Intelligence, Vol. 5, 2023. Link
  
• Sobien, D., Yardimci, M., Nguyen, M., Mao W., Fordham, V., Rahman, A., Duncan, S. and Batarseh, F. "AI for Cyberbiosecurity in Water Systems—A Survey", Springer - In: Greenbaum, D. (eds) Cyberbiosecurity, 2023. Link
• Adeoye, S., Kaufman, E., Brown, A. and Batarseh, F. "Mapping the Landscape of Cyberbiosecurity Education", VTechWorks, 2023. Link
• Nikkhah, A., Rohani, A., Zarei, M., Kulkarni, A., Batarseh, F., Blackstone, N. and Ovissipour, R., "Toward sustainable culture media: Using artificial intelligence to optimize reduced-serum formulations for cultivated meat", Elsevier Science of The Total Environment, 2023. Link
• Kulkarni, A., Yardimci, M., Kabir, N. and Batarseh, F., "P2O: AI-Driven Framework for Managing and Securing Wastewater Treatment Plants", American Society of Civil Engineers, 2023. Link
• Batarseh, F., Kulkarni, A., Sreng, C., Lin, J. and Maksud, S., "ACWA: An AI-driven Cyber-Physical Testbed for Intelligent Water Systems", VTechWorks, 2023. Link
• Gurrapu, S., Kulkarni, A., Huang, L., Lourentzou, I. and Batarseh, F., "Rationalization for explainable NLP: a survey", Frontiers in Artificial Intelligence, 2023. Link
• Adeoye, S., Bagby, B., Batarseh, F., Brown, A., Kaufman, E. and Lindberg, H., "Pathways for Cyberbiosecurity Workforce Preparation: Integrating Insights from Both Cybersecurity and Biosecurity", VTechWorks, 2023. Link
• Batarseh, F., and Kulkarni, A., “AI for Water”, IEEE’s Computer Society, 2023. Link
• Wilchek, M., Hanley, W., Lim, K., Luther, K., and Batarseh, F., “Human-in-the-Loop for Computer Vision Assurance: A Survey”, Elsevier’s Journal of Engineering Applications of Artificial Intelligence, 2023. Link
• Kabir Sikder, N., Nguyen, M., Elliott, D., and Batarseh, F., “DeepH2O: Cyber Attacks Detection in Water Distribution Systems Using Deep Learning”, Elsevier’s Journal of Water Resources and Industry, 2023. Link
• Y. Wang, J. Chandrasekaran, F. Haberkorn, Y. Dong, M. Gopinath and F. A. Batarseh, "DeepFarm: AI-Driven Management of Farm Production using Explainable Causality," 2022 IEEE 29th Annual Software Technology Conference (STC), 2022, pp. 27-36, doi: 10.1109/STC55697.2022.00013. Link
  
• S. Gurrapu, L. Huang and F. A. Batarseh, "ExClaim: Explainable Neural Claim Verification Using Rationalization," 2022 IEEE 29th Annual Software Technology Conference (STC), 2022, pp. 19-26, doi: 10.1109/STC55697.2022.00012. Link
  
• N.K., Sikder, F. A. Batarseh, P. Wang and N. Gorentala, "Model-Agnostic Scoring Methods for Artificial Intelligence Assurance," 2022 IEEE 29th Annual Software Technology Conference (STC), 2022, pp. 9-18, doi: 10.1109/STC55697.2022.00011. Link
• Freeman, L., Batarseh, F., Kuhn, D., Raunak, M., Kacker, R., “The Path to a Consensus on Artificial Intelligence Assurance” in IEEE Computer, March 2022. Link
• Kabir Sikder, N., Batarseh, F., “Model-Agnostic AI Assurance Scoring Framework”, 2022 Symposium on Data Science and Statistics, American Statistical Association, June 2022. Link
• [Abstract Paper] Mao, W.-Y., M. Yardimci, M. Nguyen, D. Sobien, L. Freeman, F. A. Batarseh, A. Rahman, and V. Fordham. “Trustworthy AI Solutions for Cyberbiosecurity Challenges in Water Supply Systems”. The International FLAIRS Conference Proceedings, May 2022. Link
• [Tutorial] Chandrasekaran, J., F. A. Batarseh, L. Freeman, R. Kacker, M. S. Raunak, and R. Kuhn. “Enabling AI Adoption through Assurance”. The International FLAIRS Conference Proceedings, May 2022. Link  
• Batarseh, Feras A. "Cyber Threats Jurisdiction and Authority" SAO/NASA Astrophysics Data System, Jun 2022. Link
  
• Williams, M., Sikder, N., Wang, P., Gorentala, N., and Batarseh, F., “The Application of  Artificial Intelligence Assurance in Precision Farming and Agricultural Economics”, Chapter 15 in AI Assurance by Academic Press. Link
• Perini, D., Batarseh, F., Tolman, A., Anuga, A., Nguyen, M., “Bringing Dark Data to Light with AI for Evidence-Based Policymaking”, Chapter 16 in AI Assurance by Academic Press. Link
• Batarseh, F., Munisamy Gopinath, Anderson Monken, and Zhengrong Gu, "Public policymaking for international agricultural trade using association rules and ensemble machine learning". Machine Learning with Applications, May 2021. Link
• Batarseh, F., Freeman, L. and Huang, C., “A Survey on Artificial Intelligence Assurance”, Journal of Big Data 8, 60, Apr 2021. Link
• Freeman, L., Rahman, A., Batarseh, F., “Enabling Artificial Intelligence Adoption Through Assurance”, MDPI’s Journal of Social Sciences, Artificial Intelligence for Policy Analysis, Governance and Society (AI-PAGES), Sep 2021. Link
• Gurrapu, S., Batarseh, F., Wang, P., Sikder, N., Gorentala, N., Munisamy, G., “DeepAg: Deep Learning Approach for Measuring the Effects of Outlier Events on Agricultural Production and Policy”, IEEE’s Symposium Series on Computational Intelligence (IEEE SSCI 2021), Dec 2021, Orlando, FL. Link
• Batarseh, F., Perini, D., Wani, Q., and Freeman, L., “Explainable Artificial Intelligence for Technology Policy Making Using Attribution Networks”, 20th International Conference of the Italian Association for Artificial Intelligence (AIxIA), 2021, Milan, Italy. Link
• Gurrapu, S., Batarseh, F., Wang, P., Sikder, N., Gorentala, N., Munisamy, G., “DeepAg: Deep Learning Approach for Measuring the Effects of Outlier Events on Agricultural Production and Policy”, Proceedings of the Association for the Advancement of Artificial Intelligence (AAAI) Fall Symposium, Nov 2021, Arlington, VA. Link
• Monken, A., Haberkorn, F., Gopinath, M., Freeman, L., & Batarseh, F. A., “Graph Neural Networks for Modeling Causality in International Trade”, the International FLAIRS Conference Proceedings, 34, May 2021, Miami, FL. Link
• Gopinath, M., Batarseh, F., Beckman, J., Kulkarni, A., and Jeong, S., International Agricultural Trade Forecasting using Machine Learning, Cambridge’s Journal of Data & Policy, 3, E1, Jan 2021. Link
• Huang, C., Batarseh, F., Boueiz, A., Kulkarni, A., Su, P., Aman, J., “Measuring Outcomes in Healthcare Economics using Artificial Intelligence: with Application to Resource Management”, Cambridge’s Journal of Data & Policy, Nov 2021. Link 
• Batarseh, F., Munisamy, G., Monken, A., Gu, Z., “Public Policymaking for International Agricultural Trade using Association Rules and Ensemble Machine Learning”, Elsevier’s Machine Learning with Applications, Vol. 5, 100046, Sep 2021. Link
• [Abstract Paper] Gurrapu, S., Sikder, N., Wang, P., Gorentala, N., Williams, M., and Batarseh, F. A., “Applications of Machine Learning For Precision Agriculture and Smart Farming”, the International FLAIRS Conference Proceedings, 34, May 2021, Miami, FL. Link
• [Abstract Paper] Batarseh, F. A. and Huang, C., “Measuring Outcomes in Healthcare Economics using Artificial Intelligence: with Application to Resource Allocation”, the International FLAIRS Conference Proceedings, 34, May 2021, Miami, FL. Link
• [Abstract Paper] Anuga, A., Nguyen, M., Perini, D., Svetovidov, A., Tolman, A., Wani, Q., & Batarseh, F. A., “Technology Policy Recommendations Using Artificial Intelligence”, The International FLAIRS Conference Proceedings, 34, May 2021, Miami, FL. Link
• Munisamy, G., Batarseh, F., Kulkarni, A., and Beckman, J., “Machine Learning in Gravity Models: An Application to Agricultural Trade”, A working paper (#27151) at the Agricultural Markets and Trade Policy meeting at the National Bureau of Economic Research (NBER), Apr 2020. Link
• Batarseh, F., Munisamy, G., Monken, A., “Artificial Intelligence Methods for Evaluating International Trade Patterns”, International Finance Discussion Papers (IFDP) #1296, Board of Governors of the Federal Reserve System, Washington DC, Aug 2020. Link
• Batarseh, F., Munisamy, G., Yang, R., “Data–Driven Management of International Trade Policy during Outlier Events”, Proceedings of the 5^th International Data for Policy Conference, Sep 2020, Virtual. Link
• Batarseh, F., Munisamy, G., Nalluru, G., Beckman, J., “Application of Machine Learning in Forecasting International Trade Trends”, AAAI’s Fall Symposium Series, AI in Government and Public Sector, Nov 2019, Arlington, VA. Link
• Batarseh, F., and Kulkarni, A., “Context–Driven Predictions through Bias Removal and Data Incompleteness Mitigation”, Society for Industrial and Applied Mathematics (SIAM) – 1st Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning (EDML), May 2019, Calgary, Canada. Link