| ID | Forename | Surname | Affiliation |
|---|---|---|---|
| 1 | Malgorzata | Tolisz | Viaratech |
| 2 | Kasia | Tolisz | Viaratech |
whimsical-night
Poland
Description and Rationale
We are a multidisciplinary aviation and data science team from Viaratech, combining expertise in aerospace engineering, software and data engineering, machine learning, and aviation operations.
Our team brings together experience from both the aviation industry and large-scale data and technology environments. This gives us an opportunity to approach the challenge not only as a machine-learning prediction problem, but also from the perspective of the physical and operational factors that influence aircraft ground movements.
We decided to participate in the PRC Data Challenge because taxi-out time is a particularly interesting example of a highly variable aviation process where operational conditions, airport configuration, traffic intensity, aircraft characteristics and network effects interact. Developing a model that performs well across 11 major European airports therefore represents both an interesting data-science problem and a practical aviation challenge.
Our objective is to explore a transparent and reproducible modelling approach that combines aviation-domain understanding with data-driven feature engineering and machine-learning methods. We are particularly interested in understanding which operational variables explain taxi-out variability and how well those relationships generalise across different airports and operating conditions.
The challenge also strongly aligns with our interest in open aviation research. Beyond achieving a competitive prediction accuracy, we hope to produce an interpretable and reproducible methodology that contributes useful insights to the wider aviation community.
Details
- Type: Independent
- Country: Poland
- Number of team members: 2