People

Eugene Pik

Postgraduate Research Student
School of Mathematics, Statistics and Actuarial Science
 Eugene Pik

Profile

Ask me about
  • Aviation cybersecurity
  • Research collaboration

Biography

Eugene Pik is a PhD research student in Data Science within the Department of Mathematics, Statistics and Actuarial Science at the University of Essex. His research applies statistical modelling and large-scale data engineering to the integrity of decentralised aviation surveillance networks, working with datasets of hundreds of billions of records. His methodological interests include count regression for overdispersed and heavy-tailed data, exposure-offset models for rate normalisation, spatial and spatiotemporal analysis, anomaly detection, and the treatment of survivorship bias and pseudoreplication in observational data pipelines. He is the lead author of the Global Envelope Thresholding (GET) framework, which established the first global, traffic-normalised baseline of ADS-B kinematic consistency from 246.7 billion messages using negative binomial regression across 260 Flight Information Regions, and defined "Ghost Records" as a new class of surveillance anomaly. The resulting GET-25 benchmark dataset is openly available with a Python API. His work has appeared in the Journal of Aerospace Information Systems (10.2514/1.I011527), the Journal of Transportation Security (10.1007/s12198-025-00323-w), and AIAA conference proceedings. Eugene holds an M.Sc. in Aviation and Aerospace Sustainability and Aviation Cybersecurity from Embry-Riddle Aeronautical University, with earlier training in robotics and software engineering. He previously led requirements development for a hybrid-electric eVTOL aircraft programme for emergency medical services. Eugene is the founder of Mevocopter Aerospace, which provides aerospace cybersecurity consulting services..

Qualifications

  • M.Sc. in Aviation and Aerospace Sustainability / Aviation Cybersecurity Embry-Riddle Aeronautical University (2024)

Research and professional activities

Thesis

Kinematic Integrity and Security in Automated Aviation Systems

GNSS jamming and spoofing routinely disrupt aviation. Regulators call it a critical safety threat, yet evidence rests on isolated reports, not a global, traffic-normalized measure. Four peer-reviewed papers build one from open ADS-B data, defining GPS gap and deviation measures. In 376.9 billion OpenSky messages (2023), they detect 53,232 gaps and 5,878,275 deviations. 66% of gap-NOTAM intersections fall in active warnings; deviation rates show a small link to ACLED conflict (13% higher odds).

Supervisor: Igor Rodionov

Research interests

statistical modelling of large-scale observational data · count and rate regression · spatiotemporal analysis · anomaly detection · aviation surveillance integrity · GNSS interference and spoofing

login