About Kamal Acharya
I am a Ph.D. candidate in Information Systems at the University of Maryland, Baltimore County (UMBC), where my research focuses on interpretable AI for future mobility and transportation decision support.
Research Identity
My work sits at the intersection of Advanced Air Mobility demand modeling, neurosymbolic AI, forecasting, and optimization. I am interested in AI systems that are not only accurate, but also transparent enough for planners, researchers, and decision-makers to understand and use.
Recent projects include demand forecasting for regional and urban air mobility, interpretable travel demand prediction using symbolic rules and neural models, and neural-accelerated optimization for pre-disaster mobility planning.
What Drives My Work
Transportation systems are becoming more data-rich, automated, and complex. My research asks how machine learning, symbolic reasoning, and optimization can support safer planning decisions in settings where uncertainty, infrastructure constraints, policy choices, and human trust all matter.