Current Role
Graduate Research Assistant at UMBC, contributing to NASA ULI research initiatives.
Kamal Acharya
Ph.D. Candidate, Information Systems, UMBC
Kamal Acharya is a Ph.D. candidate in Information Systems at the University of Maryland, Baltimore County (UMBC). His research focuses on Advanced Air Mobility demand modeling, Neurosymbolic AI, trustworthy machine learning, forecasting, and optimization for transportation systems.
I build interpretable AI systems for safer transportation planning, connecting neurosymbolic modeling and data-driven forecasting with operational decision support.
Open to collaboration in AAM forecasting, trustworthy AI, and neurosymbolic systems.
Research Networks
UMBC
NASA ULI
IEEE
IJCAI
Professional Snapshot
Research Output
15+ publications across IEEE journals and major AI and transportation conferences.
Core Areas
Neurosymbolic AI, AAM demand modeling, optimization, and trustworthy AI systems.
What I Am Working On Now
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Extending temporal demand forecasting for regional and urban AAM use cases.
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Designing interpretable neurosymbolic pipelines that preserve controllability and domain logic.
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Applying neural-accelerated optimization to resilience and disaster-planning scenarios.
Selected Work
Integrating Neurosymbolic AI in Advanced Air Mobility
IJCAI 2025 Survey paper mapping practical integration paths for neurosymbolic AAM systems.
Demand Modeling for Advanced Air Mobility
IEEE TITS Journal publication analyzing open challenges and modeling opportunities for AAM demand forecasting.
Symbolic Knowledge Distillation of Large Language Models
IEEE TAI Framework for extracting symbolic structures from LLMs while retaining prediction utility.