ML systems for the Automotive & Airports of tomorrow with Lightyear & Schiphol
We are very happy to announce that we are organizing the sixth Eindhoven Data Community meetup in collaboration with Lightyear and Schiphol! We will host this meetup in a very unique location, namely the Lightyear factory itself! During this meetup, we will dive deep into the ML systems that will enable the airports and automotive of tomorrow. You will hear about all the challenges- and opportunities in designing these systems. Moreover, we will get a unique insight into the philosophy of Lightyear: the meetup will be accompanied by a tour through the Lightyear factory!
Lightyear
Lightyear is a unique company with big ambitions: to make clean mobility accessible to everyone, everywhere. The Lightyear 0 is unique in the sense that it can use solar energy to charge itself. However, that’s not the only thing that makes Lightyear stand out. Lightyear has developed a unique perspective on how to design a car and does things radically differently. From the power source to the engine to aerodynamics. Lightyear has revised- and optimized all aspects involved in the design of its first model. Lightyear is an amazing company, with an amazing team and we are very happy to have them on board for this meetup.
Engin Baglayici will talk about the development of ADAS (Advanced driver-assistance system) for the Lightyear 2, Lightyear’s next-generation solar car. The car, which is expected in 2025, will heavily rely on the usage of AI to assist the driver in several ways. Think about lane assistance or allowing the car to park itself such that it can recharge in a sunny spot. As you can imagine, developing such systems poses great challenges. Together with our speaker Engin, we will dive deeper into both the technical challenges and opportunities that lie in designing such systems.
Schiphol
Schiphol is one of the largest airports in The Netherlands, and has the ambitious goal to making their airport fully autonomous by 2050. Predicting lines at the gates and security checks, predicting delays, self-driving passenger busses, and automated passenger bridges are all part of this project. We think it’s amazing to see how Schiphol uses cutting-edge techniques such as AI/Deep Learning to streamline their processes, and we are delighted to have them as speakers during our meetup! Marcel Raas & Santiago Ruiz will talk about their work to streamline the turnaround process and make it more predictable, Amsterdam Airport Schiphol has developed Turnaround Insights. This cutting-edge solution uses deep learning technology to translate camera images from aircraft stands into usable data. This data, which provides insight into the various sub-processes, such as refueling, pushback, cleaning, and catering, will help us predict and prevent delays. During the talk, Marcel & Santiago will talk give a deep insight into how they tackled this challenge.
Program
- 17:00 – 18:00 Food
- 18:00 – 18:10 Welcome
- 18:10 – 19:00 Marcel Raas & Santiago Ruiz about Turnaround Insights
- 19:00 – 19:15 Break
- 19:15 – 20:00 Engin Baglayici about ADAS for the Lightyear 2
- 20:00-21:00 Drinks + Factory Tour (divided into 2 groups)
Note: everyone is asked to sign an NDA. This is mandatory to attend the meetup
About Engin
Engin is an ADAS engineer in the Research Autonomous driving team of Lightyear. Engin has a background in Computer Engineering and brings years of working experience in the Autonomous driving sector. Before working at lightyear, he did several projects focussed on perception and planning. Besides, he conducted research in the development of robotics and automation Systems.
About Santiago
Santiago has an educational background in industrial engineering, operations research, and machine learning. In the last years, Santiago has been working extensively with computer vision to make real-time detections of the flight preparation process with the final aim of reducing flight delays. Santiago passion is to develop data-driven solutions to help to improve people’s life.
About Marcel
Marcel completed a study in theoretical physics, after which he did a PhD in particle physics at CERN. After completing his PhD, Marcel worked at Shell and ASML and currently he is a data scientist at GoDataDriven. During the time he worked for GoDataDriven, he has undertook a diverse scala of projects: demand forecasting, money laundering detection and e-commerce recommendations. Currently he has been working on the Turnaround Insights project at Schiphol, both on the core computer vision part, as well as building forecasting models that use the detections from the computer vision model.