Kamal Acharya
Ph.D. Candidate at UMBC, AI Researcher
Selected conference talks, research seminars, and invited sessions on Neurosymbolic AI, Advanced Air Mobility, and trustworthy AI systems.
AIAA SCITECH 2026 Forum | Orlando, FL, USA | Conference Presentation
Presented flight demand modeling research for airport-connected Urban Air Mobility in New York City, focusing on demand estimation methods for future advanced air mobility operations.
Authors: Kamal Acharya, Katherine Vasiloff, Zhenbo Wang, Liang Sun, and Houbing Song.
IJCAI 2025 | Montreal, Canada | Conference Presentation
Presented a comprehensive survey of neurosymbolic AI methods for Advanced Air Mobility, emphasizing interpretable, reliable, and safety-aware decision support.
Authors: Kamal Acharya, Iman Sharifi, Mehul Lad, Liang Sun, and Houbing Song.
IWCMC 2025 | Abu Dhabi, United Arab Emirates | Conference Presentation
Presented a neurosymbolic travel demand prediction method that integrates decision tree rules into neural network learning for more interpretable demand modeling.
Authors: Kamal Acharya, Mehul Lad, Liang Sun, and Houbing Song.
IEEE CAI 2025 | Santa Clara, CA, USA | Conference Presentation
Presented a data-driven enhancement of gravity models for trip demand prediction, connecting classical transportation modeling with modern AI methods.
Authors: Kamal Acharya, Mehul Lad, Liang Sun, and Houbing Song.
AIAA SCITECH 2025 Forum | Orlando, FL, USA | Conference Presentation
Presented regional air mobility demand modeling research for Tennessee, highlighting how demand estimation can support future AAM planning and infrastructure decisions.
Authors: Kamal Acharya, Mehul Lad, Houbing Song, and Liang Sun.
IEEE BigData 2024 | Washington, DC, USA | Conference Presentation
Presented demand modeling research for Advanced Air Mobility, addressing opportunities and challenges in data-driven AAM planning.
Authors: Kamal Acharya, Mehul Lad, Liang Sun, and Houbing Song.
27th IEEE International Conference on Intelligent Transportation Systems (ITSC 2024) | Edmonton, Canada | Poster Presentation
Presented a poster on improving pre-disaster air mobility planning with a neural network-accelerated genetic algorithm framework.
Authors: Kamal Acharya, Alvaro Velasquez, Yongxin Liu, Dahai Liu, Liang Sun and Houbing Herbert Song.
COEIT Research Day 2025 | April 11, 2025 | Poster Presentation
Presented in the afternoon poster session at the second COEIT Research Day.
Poster presented a data-driven view of AAM demand modeling, highlighting planning implications for future air mobility operations.
Doctorate Student Award (Poster Session Winner)
Authors: Kamal Acharya, Mehul Lad, Liang Sun, and Houbing Song.
IJCAI 2025 | Montreal, Canada | Poster Presentation
Authors: Kamal Acharya, Iman Sharifi, Mehul Lad, Liang Sun, and Houbing Song.
Poster summarized the neurosymbolic AI landscape for AAM, emphasizing how symbolic reasoning and machine learning can be combined for interpretable and reliable decision support.
IS 792 Guest Lecture | UMBC Department of Information Systems
Delivered a guest lecture on neurosymbolic methods for Advanced Air Mobility, focusing on symbolic reasoning and machine learning approaches for reliability, demand modeling, and future AAM operations.
Invited by Dr. Houbing Herbert Song; session included active student discussion on research and deployment directions in trustworthy AAM systems.
2024 Training Session | May 20, 2024 - August 9, 2024 (12 Weeks)
Served as a Teaching Assistant (TA) and delivered training support for AI/ML and cybersecurity modules, including hands-on mentoring and participant guidance.
Role Highlight: TA, Department of Information Systems, UMBC.
Full program details (instructors, structure, eligibility, stipend, and updates) are available on the official page.
I am open to invited talks, research seminars, workshops, and interdisciplinary panels. For speaking requests, please use the Contact page.