Independent Researcher Applies AI to Aviation Safety, Emissions, and Maintenance Gaps
Sam Suseelan’s published work addresses fuel efficiency, predictive maintenance, contrail avoidance, and cybersecurity — each backed by verifiable academic sources.
Aviation is under mounting pressure on multiple fronts simultaneously: tightening environmental obligations, an aging general aviation fleet, and the growing cybersecurity exposure of networked aircraft systems. Sam Suseelan, an independent researcher, has spent recent years publishing peer-reviewed work and filing intellectual property on AI-based approaches to each of these problems.
Working without institutional affiliation, Suseelan has built a body of research spanning fuel optimization, predictive maintenance, contrail avoidance, and aircraft safety computing. One paper has been formally published in a peer-reviewed journal; additional work is listed on his academic profiles. His research profile is publicly available on Google Scholar and ResearchGate.
Predictive Maintenance for General Aviation
General aviation has historically received less investment in predictive technologies than commercial carriers, despite accounting for a disproportionate share of mechanical incidents. Suseelan’s 2026 paper, published in the International Journal of Intelligent Systems and Applications in Engineering (IJISAE), examines how AI and machine learning can be applied to detect component failure before it occurs in general aviation aircraft.
The paper — titled “AI-Based Predictive Maintenance for General Aviation Aircraft” — focuses on data analytics and machine learning models for scheduling maintenance based on failure prediction rather than fixed intervals. It also addresses future directions including edge computing and autonomous maintenance systems.
The full paper is published at doi.org/10.17762/ijisae.v14i1s.8123
Fuel Efficiency and Emissions Reduction
Suseelan’s research in this area covers AI-based fuel optimization applied across commercial aviation flight phases. The work positions machine learning as a practical tool for reducing fuel burn and moving toward measurable emissions reductions, relevant to the industry’s net-zero commitments.
Contrail Avoidance as a Climate Lever
Contrails formed in ice-supersaturated atmospheric regions are increasingly recognized as a significant driver of aviation’s climate impact. Research published in Nature’s Communications Engineering journal found that per-flight altitude adjustments reduced satellite-visible contrails by 64 percent at a fuel cost increase of roughly 2 percent per adjusted flight. A large-scale trial involving 2,400 transatlantic flights led by Google Research and American Airlines found AI-guided altitude changes reduced contrail formation by 62 percent.
Suseelan’s research addresses contrail avoidance through AI-based rerouting of flights around ice-supersaturated atmospheric conditions. His work sits within a growing body of industry research that positions contrail avoidance as a scalable climate intervention that does not require major infrastructure changes or new aircraft.
Aircraft Safety and Cybersecurity
Suseelan holds a UK Design Patent for an AI-based aircraft safety computer device that addresses both bird strike detection and cybersecurity vulnerabilities in networked aircraft systems. The solution combines sensor fusion with anomaly-detection algorithms.
The dual focus on bird strike detection and cybersecurity reflects a gap that has grown more critical as modern aircraft systems have become increasingly networked. The UK IPO’s design patent system covers novel, non-obvious physical or functional designs, and grants registered protection in the United Kingdom.
Peer Review and Research Community Contributions
Beyond his own publications, Suseelan has contributed to the research community as a peer reviewer for academic journals in the aviation AI space.
Research Profiles
Suseelan’s academic profiles are publicly available:
Google Scholar: Google Scholar
ResearchGate: ResearchGate
ORCID: ORCID
Context
Independent researchers in applied AI fields have become more common as tools and publishing platforms lower the barriers to academic contribution. Suseelan’s work is concentrated in a set of aviation challenges that have seen increased industry and regulatory attention: the International Civil Aviation Organization (ICAO) has set net-zero carbon targets for international aviation by 2050, while the FAA and EASA have both flagged cybersecurity as a growing concern for networked aircraft systems.