He has taught AI and Data Science courses at multiple universities including George Mason University (GMU), University of Maryland, Baltimore County (UMBC), Georgetown University, and George Washington University (GWU).
[Oct 2021] Elevated to the grade of Senior Member of IEEE. https://www.ieee.org/
[Oct 2021] New accepted paper: Explainable Artificial Intelligence for Technology Policy Making Using Attribution Networks; Feras A. Batarseh, Dominick Perini, Qasim Wani, and Laura Freeman – accepted at AIxIA 2021
[Sep 2021] New accepted paper: DeepAg: Deep Learning Approach for Measuring the Effects of Outlier Events on Agricultural Production and Policy; Sai Gurrapu, Feras A. Batarseh, Pei Wang, Md Nazmul Kabir Sikder, Nitish Gorentala, and Gopinath Munisamy – accepted at: IEEE SSCI 2021
[Apr 2021] Batarseh, F., Freeman, L., and Huang, C., "A Survey on Artificial Intelligence Assurance", Springer's Journal of Big Data, 8, Article number: 60. https://rdcu.be/ckz4g
[Apr 2021] FLAIRS-34 new paper publication: Monken, A., Haberkorn, F., Gopinath, M., Freeman, L., & Batarseh, F. (2021). Graph Neural Networks for Modeling Causality in International Trade. The International FLAIRS Conference Proceedings, 34. https://doi.org/10.32473/flairs.v34i1.128485
[Apr 2021] FLAIRS-34 new abstract publication: https://journals.flvc.org/FLAIRS/article/view/128497
[Apr 2021] FLAIRS-34 new abstract publication: https://journals.flvc.org/FLAIRS/article/view/128499
[Dec 2020] Join us at the Health Gaming Analytics panel @ the Global Digital Health Forum: https://gdhf.conference.tc/2020/
[Nov 2020] Join us at AAAI's panel on AI for Policy: https://aaai.org/Symposia/Fall/fss20.php
[Sep 2020] Join us at Data for Policy: https://dataforpolicy.org/
My talk: Data-Driven Management of International Trade Policy during Outlier Events
[Aug 2020] Our new website is now live: http://turing.cos.gmu.edu/
[May 2020] Presentation at NBER: "Machine Learning in Gravity Models: An Application to Agricultural Trade".
[May 2020] "Pandemics and big data tyrannies", my latest LSE Business Review article:
[Feb 2020] "The use of robots and AI in war", our LSE Business Review article:
[Jan 2020] Invited talk: Trade/ML Seminar at The University of Georgia.
[Dec 2019] International Agricultural Trade Research Consortium (IATRC) - presentation: “Machine Learning in Gravity Models: An Application to Agricultural Trade”, Washington, D.C.
[Nov 2019] Invited talk and panel - NASA Data Science Days Panel, “Data Science for Government: Challenges and Best Practices”, Washington, D.C.
[Nov 2019] AAAI fall symposium series talk: "Applications of Machine Learning in Forecasting International Trade Trends", Arlington, VA - events page.
[Aug 2019] Our research group's webpage launched:
[May 2019] Attending and presenting two posters on Data Incompleteness, and the Global AI race at Florida's AI Research Society Conference (FLAIRS); Sarasota, Florida.
[May 2019] Attending and presenting a paper (on data bias and context) at the Evaluation and Experimental Design in Data Mining and Machine Learning (EDML) workshop - the SIAM conference. Calgary, Canada.
[Oct 2018] "The Unspoken Race for Artificial Intelligence"; my latest article with the London School of Economics (LSE):
[Oct 2018] Invited talk: "Government Machine Learning Applications and the Future of Data Openness", presented to the academic delegation visiting GMU from Zhejiang Province, China.
[Aug 2018] Data Science Session Chair at the Seventh International Conference on Agro-Geoinformatics, Hangzhou, China.
[May 2018] Invited talk at the University of Alaska Anchorage (CSE department): "Machine Learning and Data Science Solutions for Software Engineering Challenges".
[Feb 2018] My latest entries into Springer's Encyclopedia of Big Data. To explore the Encyclopedia:
[Jan 2018] If you believe that access to science is a human right (as I do!), Open Science is the direction that we all need to adopt. My latest with the London School of Economics:
[Dec 2017] My latest talk: An Open Mind on Open Science. The Dupont Summit:
[Dec 2017] My book: Federal Data Science - available now:
[Oct 2017] My interview with Predictive Analytics Times:
[Sep 2017] A new article about the future of AI (@London School of Econ (LSE) Business Review):
[Sep 2017] My Tedx talk (video coming soon):
[Aug 2017] Chairing a data science session at the international geo-informatics conference:
[Jun2017] A new paper published at: http://context17.lip6.fr/index.php
Context-Aware User Interfaces for Intelligent Emergency Applications
[Feb 2017] New paper published: Batarseh, F., Yang, R., and Deng, L., "A Comprehensive Model for Management and Validation of Federal Big Data Analytical Systems", Published at Springer's Journal of Big Data Analytics
 New poster paper presented at the AIC workshop in New York, NY, at the BICA Conference: http://www.di.unito.it/~lieto/AIC2016/index.html
Context-Driven Testing of Analytical Tools through Kansei Engineering
 My papers used at University of Waterloo (for a student project):
 New paper published at Elsevier's Journal of Big Data Research:
 Latest book chapter now available!
For further information on research grants, funding, student employment, campus service,
research projects, reviewing services, awards, memberships, and further affiliations, please contact me.
I invite you to explore my portfolio.
Thank you for your time, enjoy!
-Feras A. Batarseh