Track / Overview

Civil aviation provides flight services through networked operations provided by several players. In this fascinating industry, many different organizations and businesses work closely together to enable passengers and goods to travel safely and efficiently through the world. The main players involved are airlines, airports, ground handlers, manufacturers, air traffic control centers, government authorities, distributors and various forms of providers ranging from startups to established suppliers. They operate in a very complex and intertwined system in which large amounts of data is gathered and processed to assure a safe, time and cost efficient, reliable and customer-friendly service.

Artificial Intelligence (AI) methods like Machine Learning (ML), Deep Learning (DL) and others, are starting to influence the industry and are becoming key methodologies in many research projects and new developments. The goal of this track is to give the audience a deep insight into the latest and most advanced applied research projects in the field. The aim is to touch upon the following five core topics from aviation operations throughout the presentations: Flight Operations, Dynamic Pricing, Technics and Flight Safety, Airports and Ground Operations and Air Traffic Management.

Track / Schedule

Machine Learning for Aviation Safety at NASA

With Nikunj Oza

Anomaly Detection and Pattern Recognition in Flight Data for Airline Safety Management

With Lishuai Li

Aircraft Atypical Approach Detection using Functional Principal Component Analysis

With Daniel Delahaye

Dynamic Pricing For Ancillaries In Travel Industry using Reinforcement Learning

With Ravi Kumar

“Catching Signals”: Augment predictive Revenue Management models with contextual data

With Tabea Hasler & George Brova

Break

Flying round the bermuda triangle of predictive analytics

With Matthias Platho

Deep Learning Anomaly Detection

With Sergei Bobrovskyi

Improving air traffic control capacity planning with ML solutions

With Seddik Belkoura & Ramon Dalmau

Data-driven trajectory management at airports

With Michael Schultz

Opportunities and Challenges when Building AI for Autonomous Flight

With David Haber

Track / Speakers

Seddik Belkoura

Data Science Expert

Ravi Kumar

Senior Scientist, PROS

Lishuai Li

Assistant Professor, Delft University of Technology

Nikunj Oza

Leader, Data Sciences Group, NASA Ames Research Center

Daniel Delahaye

Head of the Optimization and Machine Learning Group, ENAC Laboratory (French Civil Aviation Uni)

Sergei Bobrovskyi

Data Scientist, Airbus

David Haber

Head of Deep Learning, Daedalean

Matthias Platho

Principal Data Scientist, zeroG

Tabea Hasler

Senior Project Coordinator Revenue Management, SWISS

George Brova

CTO, Migacore Technologies

Ramon Dalmau

Data Scientist, EUROCONTROL

Michael Schultz

Researcher, TU Dresden

Track / Co-organizers

Chrysanthi Tsimitri

Team lead Data Insights & Analytics, SWISS International Air Lines

Michel Philipp

Revenue Management Data Scientist, Swiss International Air Lines

Manuel Renold

Associate Professor, ZHAW – Zurich University of Applied Sciences

AMLD EPFL 2020 / Tracks & talks

AI & Nutrition

Marinka Zitnik, Marcel Salathé, Fabio Mainardi, Tome Eftimov, Barbara Koroušić Seljak, Nives Ogrinc, Aleksandra Kovachev

13:30-17:00 January 282A

AI & Policy

Joanna Bryson, Sofia Olhede, Emanuele Baldacci, Sabrina Kirrane, Bruno Lepri, Dennis Diefenbach, Ioannis Kaloskampis, Benoît Otjacques, Steve MacFeely, Christina Corbane

13:30-17:30 January 272A

Challenge Track

Danny Lange, Sunil Mallya, Marcel Salathé, Florian Laurent, Erik Nygren, Sharada Mohanty, Parth Kothari, Navid Rekabsaz, Wilhelmina Welsch, Ewan Oglethorpe, Nicholas Jones, Gokula Krishnan, Jeremy Watson, Andrew Melnik

13:30-17:00 January 284A

AMLD / Global partners