Publications

Peer-reviewed journal articles, conference papers, and book chapters by Kamal Acharya on Advanced Air Mobility, neurosymbolic AI, demand modeling, intelligent transportation systems, trustworthy machine learning, optimization, and applied cybersecurity.

Google Scholar ORCID

Research Contribution Summary

My peer-reviewed publications span Advanced Air Mobility demand modeling, Neurosymbolic AI, trustworthy machine learning, intelligent transportation systems, optimization, and applied cybersecurity. A central theme across this work is building AI methods that are not only predictive, but also interpretable, operationally useful, and aligned with real-world planning constraints.

Recent work focuses on AAM forecasting and infrastructure planning, including regional air mobility, airport-connected urban air mobility, travel demand prediction, and gravity-model enhancement. Related AI research investigates neurosymbolic methods, symbolic knowledge distillation, reinforcement learning and planning, and robust decision-support systems.

For broader context, see my research areas and conference talks and presentations.

Publication Themes

Advanced Air Mobility and Transportation Demand

Demand modeling, forecasting, portal siting, regional air mobility, urban air mobility, and intelligent transportation systems.

Neurosymbolic and Trustworthy AI

Neurosymbolic surveys, symbolic knowledge distillation, rule-aware learning, robustness, uncertainty, and interpretable decision support.

Optimization, Resilience, and Applied AI Systems

Neural-accelerated optimization, pre-disaster mobility planning, cybersecurity applications, and AI methods for constrained operational settings.

Journal Articles

2026

1. Vasiloff K., Acharya K., Wang Z., Song H., Sun L. Demand Forecast and Energy-Aware Portal Siting for Regional Air Mobility. Journal of Air Transport Management. under major revision Advanced Air Mobility Demand Forecasting Infrastructure Planning
2. Acharya K., Raza W., Vasiloff K., Wang Z., Sun L., Song H. H. Demand Modeling for Advanced Air Mobility: Challenges, Opportunities, and Future Directions. IEEE Transactions on Intelligent Transportation Systems. DOI Advanced Air Mobility Demand Modeling Intelligent Transportation Systems
3. Acharya K., Song H. A Comprehensive Review of Neuro-symbolic AI for Robustness, Uncertainty Quantification, and Intervenability. Arabian Journal for Science and Engineering. DOI Neurosymbolic AI Trustworthy AI Robustness
4. De Macedo A. R., Jagatheesaperumal S. K., Da Costa K. A., Acharya K., Song H., Guizani M., De Albuquerque V. H. C. Quantum AI-Enhanced IoT-Fog Communication: A Survey From Cybersecurity and Data Privacy Perspective. IEEE Communications Surveys & Tutorials. DOI Quantum AI IoT Cybersecurity

2024

1. Acharya K., Velasquez A., Song H. H. A Survey on Symbolic Knowledge Distillation of Large Language Models. IEEE Transactions on Artificial Intelligence. DOI Symbolic Knowledge Distillation Large Language Models Neurosymbolic AI
2. Acharya K., Raza W., Dourado C., Velasquez A., Song H. H. Neurosymbolic Reinforcement Learning and Planning: A Survey. IEEE Transactions on Artificial Intelligence. DOI Neurosymbolic AI Reinforcement Learning Planning

2023

1. Raza W., Ma X., Song H., Ali A., Zubairi H., Acharya K. Long Short-Term Memory Neural Network Assisted Peak to Average Power Ratio Reduction for Underwater Acoustic Orthogonal Frequency Division Multiplexing Communication. KSII Transactions on Internet & Information Systems. DOI Machine Learning LSTM Underwater Acoustic Communication

Conference Proceedings

2026

1. Acharya K., Vasiloff K., Wang Z., Song H., Sun L. Urban Air Mobility Flight Demand Modeling for Airports in New York City. AIAA SCITECH 2026 Forum. DOI Urban Air Mobility Airport Demand Modeling Advanced Air Mobility

2025

1. Acharya K., Sharif I., Lad M., Sun L., Song H. Integrating neurosymbolic AI in advanced air mobility: a comprehensive survey. IJCAI 2025. DOI Neurosymbolic AI Advanced Air Mobility Survey
2. Acharya K., Lad M., Sun L., Song H. Neurosymbolic Approach for Travel Demand Prediction: Integrating Decision Tree Rules into Neural Networks. IWCMC 2025. DOI Travel Demand Prediction Neurosymbolic AI Decision Trees
3. Acharya K., Lad M., Sun L., Song H. A Data-Driven Approach to Enhancing Gravity Models for Trip Demand Prediction. IEEE CAI 2025. DOI Gravity Models Trip Demand Prediction Data-Driven Modeling
4. Acharya K., Lad M., Song H., Sun L. Regional Air Mobility Flight Demand Modeling in Tennessee State. AIAA SCITECH 2025 Forum. DOI Regional Air Mobility Demand Modeling Advanced Air Mobility
5. Hakim S. B., Adil M., Acharya K., Song H. H. Decoding Android Malware with a Fraction of Features: An Attention-Enhanced MLP-SVM Approach. NSS 2024 (LNCS 15564, 2025). DOI Android Malware Cybersecurity Machine Learning

2024

1. Lad M., Acharya K., Sun L., Song H. Enhancing Forecasting for Advanced Air Mobility. IEEE BigData 2024. DOI Advanced Air Mobility Forecasting Big Data
2. Acharya K., Lad M., Sun L., Song H. Demand Modeling for Advanced Air Mobility. IEEE BigData 2024. DOI Advanced Air Mobility Demand Modeling Big Data
3. Acharya K., Velasquez A., Liu Y., Liu D., Sun L., Song H. H. Improving Air Mobility for Pre-Disaster Planning with Neural Network Accelerated Genetic Algorithm. IEEE ITSC 2024. DOI Pre-Disaster Planning Genetic Algorithm Air Mobility

2023

1. Zhu L., Lan Q., Velasquez A., Song H., Kamal A., Tian Q., Niu S. SKGHOI: Spatial-Semantic Knowledge Graph for Human-Object Interaction Detection. IEEE ICDMW 2023. DOI Knowledge Graph Human-Object Interaction Computer Vision

Book Chapters

2025

1. Hakim S. B., Adil M., Acharya K., Song H. H. AI for Android Malware Detection and Classification. In AI for Cybersecurity. DOI Cybersecurity Android Malware Artificial Intelligence