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Aviation Safety Analytics
Aviation Safety Analytics
ASYST Lab develops data-driven methods to identify, model, and mitigate aviation safety risks through accident analysis, operational data, and predictive analytics.
AI Applications for Data Analysis
AI Applications for Data Analysis
Our team uses machine learning and natural language processing (NLP) to analyze aviation accident narratives, which often contain details not captured in coded data. By training neural network models on thousands of reports, we aim to improve accident causation analysis and address limitations of code-only approaches.
Unsupervised and supervised machine learning techniques have been applied to inflight loss of control accidents, UAS incidents, and stall/spin accidents in the National Transportation Safety Board (NTSB) and NASA's Aviation Safety Reporting System (ASRS) databases.
Previous work led to Dr. Majumdar's PhD dissertation, an MS thesis, a BS honors thesis, two research symposium poster displays, and a conference proceeding.
Students, Relevant Publications, & Funding
Students
Mehedi Hasan, Graduate Assistant, Mechanical Engineering, University of Arkansas
Lauren Westfall, Undergraduate Research Assistant, Mechanical Engineering, University of Arkansas
Cody Harrison, Undergraduate Research Assistant, Computer Science, University of Arkansas
Kacey Haws, Undergraduate Research Assistant, Computer Science, University of Arkansas
Dr. Karen Marais, Professor of Aeronautical and Astronautical Engineering, Purdue University
Publications
Hasan, M., Westfall, L., and Majumdar, N. (2025). Analysis of Stall and Spin Accidents Involving General Aviation Fixed-Wing Aircraft. In AIAA AVIATION 2025. Jul 2025. doi: 10.2514/6.2025-3322
Hasan, M. (2025). Analysis and Predictive Modeling of Stall and Spin Accidents in General Aviation Fixed-Wing Aircraft. Graduate MS Thesis. Available online
Westfall, L. (2025). Causes and Contributing Factors in General Aviation Fixed-wing Stall and Spin Accidents. Undergraduate Honors Thesis. Available online
Haws, K. (2025). Analyzing Unmanned Aircraft System (UAS) Incidents from NASA ASRS Data Using Unsupervised Machine Learning. Undergraduate Honors Thesis.Available online
Haws, K., & Majumdar, N. (2025). Poster: Analyzing Unmanned Aircraft System (UAS) Incidents from NASA ASRS Data Using Unsupervised Machine Learning. 2025 Research Poster Competition. Available online
Majumdar, N. (2023). State-based Analysis of General Aviation Loss of Control Accidents Using Historical Data and Pilots’ Perspectives (Order No. 30499136). ProQuest Dissertations & Theses Global. (2806444500). doi: 10.25394/PGS.22677526.v2
Funding
University of Arkansas, Honors College
University of Arkansas, Department of Mechanical Engineering
Instructional Aviation Accident Analysis
Instructional Aviation Accident Analysis
This study focuses on General Aviation instructional accident analysis using the National Transportation Safety Board (NTSB) accident reports. General Aviation includes non-commercial, non-military operations such as private flying, flight training, and business aviation. Nearly one-third of total active pilots are students. This work examines how instructional accidents occur and their contributing factors.
Previous work resulted in a BS honors thesis and an honors research symposium poster display (third prize).
More work is in progress.
Students, Relevant Publications, & Funding
Students
Sydney Sommers, Undergraduate Research Assistant, Mechanical Engineering, University of Arkansas
Jesse Pham, Undergraduate Research Assistant, Mechanical Engineering, University of Arkansas
Publications
Pham, J., & Majumdar, N. (2025). Solo Versus Dual: A Comparative Analysis of Instructional General Aviation Accidents. 2025 Research Poster Competition. Available online
Sommers, S. (2024). A Review and Analysis of General Aviation Instructional Accidents. Undergraduate Honors Thesis. Available online
Funding
University of Arkansas, Honors College
Influence of Daylight Saving Time on US Civil Aviation Operations and Safety
Influence of Daylight Saving Time on US Civil Aviation Operations and Safety
Daylight Saving Time (DST) involves biannual clock shifts, impacting various sectors, including transportation. While prior research has linked DST transitions to increased workplace injuries and automobile accidents, its effects on aviation safety remain unexplored. This study examined the relationship between DST transitions and aviation accident rates in the continental United States from 1978 to 2024. A statistical analysis was conducted to identify variations in accident frequencies surrounding DST transitions. Results indicated no significant increase in aviation accidents following DST changes, contrasting with findings in other industries. This study highlighted DST’s impact on aviation safety, by providing insights into its negligible impact on aviation safety.
This work resulted in a journal paper publication.
Collaborators, Relevant Publications, & Funding
Collaborators
Dr. Linfeng Jin, Eastern Michigan University (work done at Embry-Riddle Aeronautical University, Florida)
Publications
Jin, L., and Majumdar, N. (2025). The Influence of Daylight Saving Time on US Civil Aviation Operations and Safety. Collegiate Aviation Review International, 43(2), 57–68. Available online
Modeling of General Aviation Fixed-wing Aircraft Inflight Loss of Control Accidents
Modeling of General Aviation Fixed-wing Aircraft Inflight Loss of Control Accidents
This research developed data-driven methods to understand the causes of General Aviation accidents, with a focus on inflight loss of control, the leading cause of fatal accidents. A state-based modeling framework was developed to identify how normal flights transition into hazardous conditions and accidents using aircraft and pilot states. The research analyzed National Transportation Safety Board (NTSB) accident reports and pilot-submitted incident reports to identify contributing human factors and flight maneuvers that can improve pilot training and aviation safety. This FAA-funded work at Purdue University resulted in a Ph.D. dissertation, an M.S. thesis, three journal papers, two conference papers, and two FAA technical reports.
Previous work led to Dr. Majumdar's PhD dissertation, MS thesis, a journal paper publication, and 2 FAA technical reports.
Collaborators, Relevant Publications, & Funding
Collaborators
Dr. Arjun Rao, Lead Engineer, Boeing
Dr. Karen Marais, Professor of Aeronautical and Astronautical Engineering, Purdue University
Publications
Majumdar, N., Marais, K., and Rao, A. (2021). Analysis of General Aviation Fixed-wing Aircraft Accidents Involving Inflight Loss of Control Using a State-based Approach. Aviation, 25(4), 283-294. doi: 10.3846/aviation.2021.15837
Majumdar, N. (2023). State-based Analysis of General Aviation Loss of Control Accidents Using Historical Data and Pilots’ Perspectives (Order No. 30499136). ProQuest Dissertations & Theses Global. (2806444500). doi: 10.25394/PGS.22677526.v2
Majumdar, N. (2018). A State-based Approach for Modeling General Aviation Fixed-wing Accidents. M.S. Thesis, Aeronautical and Astronautical Engineering, Purdue University, West Lafayette, Indiana, United States. Available online.
Funding
Federal Aviation Administration (FAA), Center of Excellence (PEGASAS)
Loss of Engine Power in General Aviation
Loss of Engine Power in General Aviation
This research analyzes general aviation accidents involving loss of engine power using National Transportation Safety Board (NTSB) accident data. The study investigates trends, flight phases, contributing factors, and relationships between accident conditions and injury outcomes to provide a better understanding of these accidents and inform targeted safety interventions.
This work led to a conference proceeding.
Collaborators, Relevant Publications, & Funding
Collaborators
Navin KC, Graduate Research Assistant, Mechanical Engineering, University of Arkansas
Publications
KC, N., Satappagol, S., and Majumdar, N. (2026). Loss of Engine Power in General Aviation: A Quantitative Analysis of Accident Data. In AIAA AVIATION 2026 Forum (p. 4307). doi: 10.2514/6.2026-4307
Funding
University of Arkansas, Department of Mechanical Engineering
Modeling of General Aviation Fixed-wing Aircraft Inflight Loss of Control Accidents
Modeling of General Aviation Fixed-wing Aircraft Inflight Loss of Control Accidents
This research developed data-driven methods to understand the causes of General Aviation accidents, with a focus on inflight loss of control, the leading cause of fatal accidents. A state-based modeling framework was developed to identify how normal flights transition into hazardous conditions and accidents using aircraft and pilot states. The research analyzed National Transportation Safety Board (NTSB) accident reports and pilot-submitted incident reports to identify contributing human factors and flight maneuvers that can improve pilot training and aviation safety. This FAA-funded work at Purdue University resulted in a Ph.D. dissertation, an M.S. thesis, three journal papers, two conference papers, and two FAA technical reports.
Previous work led to Dr. Majumdar's PhD dissertation, MS thesis, a journal paper publication, and 2 FAA technical reports.
Collaborators, Relevant Publications, & Funding
Collaborators
Dr. Arjun Rao, Lead Engineer, Boeing
Dr. Karen Marais, Professor of Aeronautical and Astronautical Engineering, Purdue University
Publications
Majumdar, N., Marais, K., and Rao, A. (2021). Analysis of General Aviation Fixed-wing Aircraft Accidents Involving Inflight Loss of Control Using a State-based Approach. Aviation, 25(4), 283-294. doi: 10.3846/aviation.2021.15837
Majumdar, N. (2023). State-based Analysis of General Aviation Loss of Control Accidents Using Historical Data and Pilots’ Perspectives (Order No. 30499136). ProQuest Dissertations & Theses Global. (2806444500). doi: 10.25394/PGS.22677526.v2
Majumdar, N. (2018). A State-based Approach for Modeling General Aviation Fixed-wing Accidents. M.S. Thesis, Aeronautical and Astronautical Engineering, Purdue University, West Lafayette, Indiana, United States. Available online.
Funding
Federal Aviation Administration (FAA), Center of Excellence (PEGASAS)
Human Factors
Human Factors
We assess human behavior, such as pilot performance and decision-making, using human-subjects research, flight simulations, and data-driven methods. By simulating real-world challenges and gathering pilots' perspectives and insights, we inform improvements in human-system interaction, such as pilot training and certification for safer flight operations.
Assessing Pilot Performance using Flight Simulator
Assessing Pilot Performance using Flight Simulator
This research area focuses on evaluating pilot performance through advanced flight simulation, integrating human factors analysis with quantitative performance metrics. High-fidelity simulators replicate real-world flight environments, enabling controlled testing of piloting skills across various scenarios, including normal operations, abnormal events, and emergency procedures. By introducing environmental challenges, such as adverse weather or equipment failures, and using statistical methods, pilot proficiency can be assessed. The findings aim to inform targeted training interventions and certification processes for safer flight operations.
Previous work resulted in a poster presentation and a conference proceeding, with additional research currently in progress.
Students, Relevant Publications, & Funding
Students
Tolu Olatunji, Graduate Research Assistant, Mechanical Engineering, University of Arkansas
Ryker Davis, Graduate Research Assistant, Mechanical Engineering, University of Arkansas
Nina Kondur, Summer Research Assistant, Purdue University
Publications
Olatunji, T., Majumdar, N., Davis, R., and Kondur, N., (2026). Assessing Pilot Proficiency in Aircraft Energy Management Using Flight Simulation. In AIAA AVIATION 2026 Forum (p. 4242). doi: 10.2514/6.2026-4242
Funding
University of Arkansas, Honors College
University of Arkansas, College of Engineering
University of Arkansas, The Division of Research and Innovation
University of Arkansas, Department of Mechanical Engineering
From Classroom to Cockpit: Extending Uncertainty Frameworks for Aviation Safety Analysis
From Classroom to Cockpit: Extending Uncertainty Frameworks for Aviation Safety Analysis
This work introduces a framework linking educational theory and aviation human factors to examine how uncertainty shapes pilot learning, communication, and decision-making. Drawing parallels between classroom collaboration and flight training, it focuses on how student pilots experience and manage ambiguity during instructor interactions. Using narrative data from NASA’s ASRS, the study will categorize uncertainty episodes, such as confusion, miscommunication, and delayed action, to inform the design of simulator-based training that fosters adaptive thinking and clear communication. The framework also extends to multi-crew and human–autonomy contexts, supporting safer, more resilient performance under uncertainty.
This work led to two conference proceedings and one undergraduate honors thesis.
Collaborators, Relevant Publications, & Funding
Collaborators
Dr. Chandan Dasgupta, Faculty of Behavioural, Management and Social Sciences, University of Twente, Enschede, Netherlands
Navin K C, Graduate Assistant, Mechanical Engineering, University of Arkansas
Abigail Henson, Undergraduate Assistant, Mechanical Engineering, University of Arkansas
Publications
KC, N., Majumdar, N., and Dasgupta, C. (2026). “Cross or Hold Short?”: Extending Uncertainty Frameworks for Aviation Safety Analysis. In 2026 ASEE Annual Conference & Exposition. Peer Reviewed
Majumdar, N., & Dasgupta, C. (2025), From Classroom to Cockpit: Extending Uncertainty Frameworks for Aviation Safety Analysis Paper presented at 2025 ASEE Midwest Section Conference, Fayetteville, AR. https://peer.asee.org/57816
Gaining Pilot Perspectives using Human-subjects Research Methods
Gaining Pilot Perspectives using Human-subjects Research Methods
By surveying and interviewing pilots, engineers, and subject-matter experts, we investigate systemic and human factors (HF) and operational conditions influencing human performance in aviation. This approach goes beyond accident analysis to identify training gaps, procedural challenges, and design considerations, guiding improvements in pilot training, operational procedures, and human-systems integration.
Loss of Control Analysis: In a previous study, we asked pilots about their loss of control experiences, recovery methods, and training to provide a deeper understanding of the role of human factors in these events. Using surveys, interviews, and lessons learned articles, we identified patterns in pilot actions/decisions. This work was conducted at Purdue University and led to Dr. Majumdar's PhD dissertation, 2 journal papers, 3 conference proceedings, and 2 FAA technical reports.
Flight Deck HF Course Design: Another study validated four core competencies for human factors practitioners in flight deck design through a survey of experts, highlighting the need for interdisciplinary skills to meet safety and regulatory demands. This research, in collaboration with Honeywell Aerospace, led to a peer-reviewed conference proceeding.
More work is currently in progress at the University of Arkansas.
Students, Collaborators, Relevant Publications, & Funding
Students & Collaborators
Tolu Olatunji, Graduate Research Assistant, Mechanical Engineering, University of Arkansas
Dr. Alexandra Kemp, Advanced Systems Engineer - Human Factors, Honeywell Aerospace Technologies
Dr. Gernot Konrad, Chief Engineer - Human Factors, Honeywell Aerospace Technologies
Dr. Thea Feyereisen, Senior Fellow - Human Factors, Advanced Technology, Honeywell Aerospace Technologies
Dr. Karen Marais, Professor of Aeronautical and Astronautical Engineering, Purdue University
Publications
Majumdar, N., and Marais, K. (2025). Lessons Learned to Prevent Loss of Control: A Review of Incidents from Pilot Archives. Proceedings of the 23rd International Symposium on Aviation Psychology, 144-149. May 2025. doi: 10.5399/osu/1188
Majumdar, N., and Marais, K. (2025). A Deeper Dive into General Aviation Loss of Control: Interviews with Pilots. Journal of Air Transportation. doi: 10.2514/1.D0522
Majumdar, N., and Marais, K. (2025). Lessons Learned to Prevent Loss of Control: A Review of Incidents from Pilot Archives. Proceedings of the 23rd International Symposium on Aviation Psychology, 144-149. May 2025. doi: 10.5399/osu/1188
Majumdar, N., and Marais, K. (2025). Human Factors in General Aviation Loss of Control: Survey of Pilot Experiences. Journal of Air Transportation, Vol. 33, No. 1, pp. 57-68 doi: 10.2514/1.D0432
Kemp, A., Gernot, K., Majumdar, N., and Feyereisen, T. (2025). Development of a competency-based short course syllabus for flight deck human factors practitioners. Transportation Research Procedia, 88, 176-184. doi: 10.1016/j.trpro.2025.05.022
Majumdar, N., and Marais, K. (2022). A Survey of Pilots’ Experiences of Inflight Loss of Control Incidents and Training. In AIAA AVIATION 2022 (p. 3778). Jul 2022. doi: 10.2514/6.2022-3778
Majumdar, N. (2023). State-based Analysis of General Aviation Loss of Control Accidents Using Historical Data and Pilots’ Perspectives (Order No. 30499136). ProQuest Dissertations & Theses Global. (2806444500). doi: 10.25394/PGS.22677526.v2
Funding
University of Arkansas, College of Engineering
University of Arkansas, The Division of Research and Innovation
University of Arkansas, Department of Mechanical Engineering
Purdue University
Pilot Age and Accident Risk
Pilot Age and Accident Risk
This study analyzed over 15 years of NTSB accident records and FAA pilot population data to investigate the relationship between pilot age, flight experience, and accident risk in general aviation. We developed exposure-based safety metrics to quantify accident likelihood and severity, revealing increased risk among older pilots despite greater flight experience.
Previous work resulted in a BS honors thesis and a conference proceeding.
Students, Relevant Publications, & Funding
Students
Jackson Jolley, Undergraduate Research Assistant, Mechanical Engineering, University of Arkansas
Publications
Jolley, J. (2026). Pilot Age and Accident Rates in General Aviation: Analysis and Recommendations. Undergraduate Honors Thesis. Available online
Jolley, J., and Majumdar, N. (2026). Too Young, Too Old? Pilot Age and Accident Risk in General Aviation. In: Li, WC., Plioutsias, A. (eds) Engineering Psychology and Cognitive Ergonomics. In International Conference on Human-Computer Interaction 2026. Lecture Notes in Computer Science (pp 177–191), vol 16707. Springer, Cham. doi: 10.1007/978-3-032-29456-2_13. Peer reviewed
Funding
University of Arkansas, Honors College
Autonomous Aerospace Systems
Autonomous Aerospace Systems
We design resilient autonomous systems that enable safe, adaptive, and collaborative operations across aerospace applications.
Systems Modeling of Autonomous Unmanned Aerial Vehicles (UAV) Swarms
Systems Modeling of Autonomous Unmanned Aerial Vehicles (UAV) Swarms
Development of an agent-based simulation, modeling a coordinated swarm of UAVs for crop spraying. By combining safety-driven design principles with swarm coordination strategies, the research aims to enhance both the reliability and performance of UAV-based agricultural operations. The work aims to integrate safety analysis into systems modeling, offering a framework adaptable to other UAV applications beyond agriculture.
Previous work led to an MS thesis, a conference proceeding, and a journal manuscript under preparation.
Students, Collaborators, Relevant Publications, & Funding
Students & Collaborators
Ryker Davis, Graduate Research Assistant, Mechanical Engineering, University of Arkansas
Dr. Cengiz Koparan, Assistant Professor of Precision Agriculture Technology, University of Arkansas
Swapnil Saha, Graduate Research Assistant, Mechanical Engineering, University of Arkansas
Publications
Davis, R., Majumdar, N., and Koparan, C. (2026). Simulation-Based Analysis of Autonomous UAV Swarm Spraying for Precision Agriculture. In AIAA AVIATION 2026 Forum (p. 4648). doi: 10.2514/6.2026-4648
Swapnil, S., Rajanasiriyur Jagadeesha, B., Patnaik, K., and Majumdar, N. (2026). A Systems Engineering Framework for Vision-Language-Enabled UAV Triage and Disaster Response. In AIAA AVIATION 2026 Forum (p. 4010). doi: 10.2514/6.2026-4010
Funding
University of Arkansas, Department of Mechanical Engineering
Unmanned Air Systems (UAS) Incident Analysis
Unmanned Air Systems (UAS) Incident Analysis
This study reviewed the status of UAS safety reporting to compare the recorded information and discuss limitations of the databases. Further, using the NASA Aviation Safety Reporting System (ASRS) database and accident classification categories with unsupervised machine learning, the study identified contributing factors in UAS incidents. Using an enhanced classification framework, key categories influencing the incidents were highlighted to inform safety decisions and potential challenges in the current reporting system. Results contributed to a better understanding of operational risks in UAS systems and the effectiveness of using a voluntary reporting system such as the ASRS database.
Previous work yielded a BS honors thesis, 2 honors research symposium poster displays, and a conference proceeding.
Students, Relevant Publications, & Funding
Students
Ryker Davis, Graduate Research Assistant, Mechanical Engineering, University of Arkansas
Kacey Haws, Undergraduate Research Assistant, Computer Science, University of Arkansas
Publications
Davis, R. and Majumdar, N. (2025). A Review of Unmanned Aircraft Vehicle Safety Reporting and Analysis of Incidents. In International Conference on Human-Computer Interaction 2025. Jun 2025. Sweden. (in press). Peer-Reviewed
Haws, K. (2025). Analyzing Unmanned Aircraft System (UAS) Incidents from NASA ASRS Data Using Unsupervised Machine Learning. Undergraduate Honors Thesis. Available online
Davis, R., & Majumdar, N. (2025). Poster: A Review of Unmanned Aircraft Systems Safety Reporting and Analysis of Incidents. 2025 Research Poster Competition. Available online
Haws, K., & Majumdar, N. (2025). Poster: Analyzing Unmanned Aircraft System (UAS) Incidents from NASA ASRS Data Using Unsupervised Machine Learning. 2025 Research Poster Competition. Available online
Funding
University of Arkansas, Honors College
University of Arkansas, Department of Mechanical Engineering
Next-Generation Air Transportation Systems
Next-Generation Air Transportation Systems
We advance the integration of emerging aviation technologies, such as advanced air mobility (AAM), electric vehicle takeoff and landing (eVTOLs), air taxis, and delivery drones into the national airspace (NAS) through transportation planning, infrastructure design, and human-centered implementation.
Systems Engineering Framework for Advanced Air Mobility Implementation
Systems Engineering Framework for Advanced Air Mobility Implementation
This research investigates the safe and effective integration of Advanced Air Mobility (AAM) into existing transportation systems. Using survey methods, spatial analysis, and systems engineering approaches, this work examines public perceptions of safety, acceptance, benefits, and operational concerns associated with emerging air transportation technologies.
AAM Noise Modeling: Current efforts focus on characterizing community noise exposure, identifying human-centered design considerations, and developing implementation frameworks to support AAM integration into the National Airspace System and surrounding communities.
This work led to an MS thesis, two conference proceedings, and a journal paper.
Students, Collaborators, Relevant Publications, & Funding
Students & Collaborators
Swapnil Saha, Graduate Research Assistant, Mechanical Engineering, University of Arkansas
Noah Bretz, Graduate Assistant, Mechanical Engineering, University of Arkansas
Dr. Abhishek Phadke, Assistant Professor of Engineering and Computing, Christopher Newport University
Publications
Phadke, A., and Majumdar, N. (2025). Towards Personal Aerial Vehicles for Urban Air Mobility Transportation: Examining Considerations and Potential Challenges. IEEE Access. https://doi.org/10.36227/techrxiv.175760291.12910474/
Bretz, N. (2026). A Multi-Criteria Decision and Spatial Modeling Framework for Socially Informed Advanced Air Mobility Implementation Planning. Graduate Theses and Dissertations. Available online
Bretz, N., and Majumdar, N. (2026). A Spatial Modeling Framework for Socially Informed Advanced Air Mobility Implementation Planning. In AIAA AVIATION 2026 Forum (p. 4189). doi: 10.2514/6.2026-4189
Swapnil, S., Mistry, Z., Majumdar, N. (2026). An ArcGIS Framework for Mapping Human-Centered Noise Annoyance for AAM Infrastructure Planning. In AIAA AVIATION 2026 Forum (p. 4075). doi: 10.2514/6.2026-4075
Funding
University of Arkansas, Honors College
University of Arkansas, College of Engineering
University of Arkansas, The Division of Research and Innovation
University of Arkansas, Department of Mechanical Engineering
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