113 citations · 238 across the 20 of their papers we have counts for
20 papers
HydroVision: Predicting Optically Active Parameters in Surface Water Using Computer Vision
Shubham Laxmikant Deshmukh, Matthew Wilchek, Feras A. Batarseh
Ongoing advancements in computer vision, particularly in pattern recognition and scene classification, have enabled new applications in environmental monitoring. Deep learning now…
KHAIT: K-9 Handler Artificial Intelligence Teaming for Collaborative Sensemaking
Matthew Wilchek, Linhan Wang, Sally Dickinson +3
In urban search and rescue (USAR) operations, communication between handlers and specially trained canines is crucial but often complicated by challenging environments and the spec…
A Review of Cybersecurity Incidents in the Food and Agriculture Sector
Ajay Kulkarni, Yingjie Wang, Munisamy Gopinath +3
The increasing utilization of emerging technologies in the Food & Agriculture (FA) sector has heightened the need for security to minimize cyber risks. Considering this aspect, thi…
ACWA: An AI-driven Cyber-Physical Testbed for Intelligent Water Systems
Feras A. Batarseh, Ajay Kulkarni, Chhayly Sreng +2
This manuscript presents a novel state-of-the-art cyber-physical water testbed, namely: The AI and Cyber for Water and Agriculture testbed (ACWA). ACWA is motivated by the need to…
Proceedings of AAAI 2022 Fall Symposium: The Role of AI in Responding to Climate Challenges
Feras A. Batarseh, Priya L. Donti, Ján Drgoňa +14
Climate change is one of the most pressing challenges of our time, requiring rapid action across society. As artificial intelligence tools (AI) are rapidly deployed, it is therefor…
ExClaim: Explainable Neural Claim Verification Using Rationalization
Sai Gurrapu, Lifu Huang, Feras A. Batarseh
With the advent of deep learning, text generation language models have improved dramatically, with text at a similar level as human-written text. This can lead to rampant misinform…
Rationalization for Explainable NLP: A Survey
Sai Gurrapu, Ajay Kulkarni, Lifu Huang +3
Recent advances in deep learning have improved the performance of many Natural Language Processing (NLP) tasks such as translation, question-answering, and text classification. How…
Cybersecurity Law: Legal Jurisdiction and Authority
Feras A. Batarseh
Cybersecurity threats affect all aspects of society; critical infrastructures (such as networks, corporate systems, water supply systems, and intelligent transportation systems) ar…
AI Assurance using Causal Inference: Application to Public Policy
Andrei Svetovidov, Abdul Rahman, Feras A. Batarseh
Developing and implementing AI-based solutions help state and federal government agencies, research institutions, and commercial companies enhance decision-making processes, automa…
Outlier Detection using AI: A Survey
Md Nazmul Kabir Sikder, Feras A. Batarseh
An outlier is an event or observation that is defined as an unusual activity, intrusion, or a suspicious data point that lies at an irregular distance from a population. The defini…
Public Policymaking for International Agricultural Trade using Association Rules and Ensemble Machine Learning
Feras A. Batarseh, Munisamy Gopinath, Anderson Monken +1
International economics has a long history of improving our understanding of factors causing trade, and the consequences of free flow of goods and services across countries. The re…
A Survey on AI Assurance
Feras A. Batarseh, Laura Freeman
Artificial Intelligence (AI) algorithms are increasingly providing decision making and operational support across multiple domains. AI includes a wide library of algorithms for dif…
Measuring Outcomes in Healthcare Economics using Artificial Intelligence: with Application to Resource Management
Chih-Hao Huang, Feras A. Batarseh, Adel Boueiz +3
The quality of service in healthcare is constantly challenged by outlier events such as pandemics (i.e. Covid-19) and natural disasters (such as hurricanes and earthquakes). In mos…
DeepAg: Deep Learning Approach for Measuring the Effects of Outlier Events on Agricultural Production and Policy
Sai Gurrapu, Feras A. Batarseh, Pei Wang +3
Quantitative metrics that measure the global economy's equilibrium have strong and interdependent relationships with the agricultural supply chain and international trade flows. Su…
The history and future prospects of open data and open source software
Feras A. Batarseh, Abhinav Kumar, Sam Eisenberg
Open data for all New Yorkers is the tagline on New York City's open data website. Open government is being promoted at most countries of the western world. Government transparency…
The application of artificial intelligence in software engineering: a review challenging conventional wisdom
Feras A. Batarseh, Rasika Mohod, Abhinav Kumar +1
The field of artificial intelligence (AI) is witnessing a recent upsurge in research, tools development, and deployment of applications. Multiple software companies are shifting th…
Foundations of data imbalance and solutions for a data democracy
Ajay Kulkarni, Deri Chong, Feras A. Batarseh
Dealing with imbalanced data is a prevalent problem while performing classification on the datasets. Many times, this problem contributes to bias while making decisions or implemen…
Panel: Economic Policy and Governance during Pandemics using AI
Feras A. Batarseh, Munisamy Gopinath
The global food supply chain (starting at farms and ending with consumers) has been seriously disrupted by many outlier events such as trade wars, the China demand shock, natural d…
Context-Driven Data Mining through Bias Removal and Data Incompleteness Mitigation
Feras A. Batarseh, Ajay Kulkarni
The results of data mining endeavors are majorly driven by data quality. Throughout these deployments, serious show-stopper problems are still unresolved, such as: data collection…
Application of Machine Learning in Forecasting International Trade Trends
Feras Batarseh, Munisamy Gopinath, Ganesh Nalluru +1
International trade policies have recently garnered attention for limiting cross-border exchange of essential goods (e.g. steel, aluminum, soybeans, and beef). Since trade critical…