Aerospace Systems and Transportation Lab
Aerospace Systems and Transportation Lab
Mechanical Engineering, University of Arkansas
Mechanical Engineering, University of Arkansas
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The Aerospace SYStems and Transportation (ASYST) Lab focuses to develop human-centered aerospace and next-generation transportation systems that are safe, intelligent, and resilient, through the integration of aerospace systems engineering, data science, machine learning, human factors analysis, and immersive experimental platforms. Under the leadership of Dr. Neelakshi Majumdar, our team pioneers research in systems modeling, predictive analysis of aviation incidents, human–machine interaction in flight systems, and the design integration of autonomous and advanced air mobility solutions. By combining empirical analysis with high-fidelity simulations, we generate actionable insights that drive safer and more resilient aerospace systems, while fostering the next generation of aerospace engineers and researchers.
Collaborative for Aviation Training and Simulation (CATS)
The Collaborative for Aviation Training and Simulation (CATS) is an approved service center housed in the ASYST Lab at the University of Arkansas, Fayetteville. CATS provides data-driven aviation training, simulation capabilities, and research support for flight schools, university partners, and industry collaborators.
Services Offered
• High-fidelity FAA-approved FRASCA flight simulator access
• Customized simulation scenarios
• Flight performance safety research support
To know more, visit this link. To schedule your session, please contact Dr. Neelakshi Majumdar at neelm@uark.edu.
RESEARCH AREAS
Aerospace Systems Engineering
Integration of complex aerospace systems, with a focus on enhancing safety and optimizing operations.
Human Factors
Human-subjects research, including flight simulator experiments, to understand the role of human factors in systems safety.
Next-Generation Transportation
Development of solutions and standards for the implementation of Advanced Air Mobility (AAM) such as, drones and air taxis into the current infrastructure.
Aviation Safety Analysis
Analysis of accident and incident data using modeling methods, text and data mining, and machine learning techniques.
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