AI Summer School | TomTom Careers

Sergio is a Data Scientist in TomTom’s Navigation product unit. He uses large volumes of data to derive actionable insights that contribute to improved business decisions and the creation of better products. With a background in physics, he holds a master’s degree in data science from the Sapienza University of Rome, specialized in recommender systems for routes.

Soeren leads the TomTom AI geospatial research lab (TAIGR) in the organization’s Traffic and Travel Information product unit. In his academic career, he has been conducting research in machine learning for over a decade. He holds a master’s degree in computer science, and a PhD with honors in machine learning from TU-Berlin. Both his master’s and PhD theses were honored with nominations or prizes (Hugo Geiger Preis; Nomination GI-Dissertationspreis; Nomination ERCIM Cor Baayen Award, as one of two Germans). Soeren has contributed to both theory, software and applications to bioinformatics at the Fraunhofer and Max-Planck Society and established the machine learning open source software track in the renowned journal of machine learning research.

Michael is Software Engineering Manager in TomTom's Autonomous Driving product unit. He leads multiple research and engineering teams working on automated perception for HD mapping, using the latest in machine learning. Prior to TomTom, he worked in the augmented reality domain, developing and leading the development of core algorithms for real-time object detection and tracking on mobile phones, and large-scale image retrieval. Michael holds a PhD in computer science from the University of Amsterdam, and has 16 years of experience in computer vision, machine learning, and software engineering.

Kia Eisinga is a Senior Data Scientist in TomTom’s Navigation product unit. She works with TomTom’s different sources of structured and unstructured data to solve complex, practical problems, with three years of experience in the field of data science.

Sander Pluimers is a Customer Project Engineer for TomTom’s Enterprise business unit, providing technical consultancy to TomTom’s key accounts. He holds a bachelor’s degree in applied physics and a master’s degree in applied earth sciences from TU Delft.

Eduardo has been sharing professional activities between academia and industry for two decades. Currently he is Assistant Professor at the Vrije Universiteit and Economics and Research Coordinator at Geodan (private geo-information company). He received his PhD in economics (2007) under the topics evaluation, acceptance and added-value of spatial information systems. He has extensive teaching experience, coordinating and teaching several courses both at bachelor and master levels on introduction and advanced use of geographic information systems (he is the coordinator of the national Geo information minor, GIS course for MBA, among others). He researches and publishes on the use of spatial analysis and the development of innovative spatial tools in support of spatial planning. He has done consultancy work on geo-spatial information for the United Nations Cartographic Department and the World Bank.

Sandjai is a professor at Vrije Universiteit Amsterdam, where his expertise lies in business analytics, optimization and machine learning. He is also a co-founder of the Amsterdam Center for Business Analytics (ACBA). Sandjai's research is on the interface of mathematics, computer science and operations management. His passion for research is also reflected in his teaching, for which he has been distinguished several times by the university. Besides research and teaching, Sandjai is driven to bridge the gap between academia and industry. He has led many analytics projects across a wide range of industries where scientific methods have significantly improved business operation processes.

Elenna is the Faculty of Science at Vrije Universiteit Amsterdam. She has 20 years of experience in transportation demand modelling, land use transportation planning, infrastructure planning and logistics. In the past decade, she has provided professional consultancy for a number of large development projects in the Netherlands, including regional development strategies for North Brabant province, Ymere Housing Corporation, South Holland province, and Friesland, Groningen, and Drenthe provinces, as well as corridor development strategies for the A1 and A2 highways. She has also coordinated the comprehensive ICT and education innovation projects "Promoting international, interdisciplinary and inter¬ institutional education via ICT" and "Sealing-up Network Education" and has consulted for the World Bank Global Development Learning Network. Her academic research addresses diffusion of innovation in dynamic networks, focusing on applications at the junction of passenger and freight transportation and ICT. She is co-founder of the international scientific workshop series "Frontiers in Transportation" and is guest editor of numerous special issues in international transportation research journals. At the Vrije Universiteit, she is involved in a multi-disciplinary study of the impact of the North/South metro line on mobility and accessibility in the greater Amsterdam metropolitan area. She also currently leads collaborative projects in research and education with logistics partners such as Port of Amsterdam, Schiphol Amsterdam Airport, Air Cargo Netherlands, Tata Steel and Panalpina World Transport.

Efstratios is an Assistant Professor at the University of Amsterdam and Scientific Manager of the QUVA Deep Vision Lab. After he completed his PhD in 2014 at the University of Amsterdam, he worked as a post-doctoral researcher before being invited to join the University of Amsterdam. As part of the QUVA Lab, he supervises and guides 12 doctoral and post-doctoral students on machine learning and computer vision. He has authored several papers in major computer vision conferences and journals, including CVPR, ICCV, ECCV, PAMI, IJCV, CVIU, ICML, ICLR. He is also the author of several patents. At the University of Amsterdam, he teaches deep learning in the Artificial Intelligence MSc. All material is available on the project website, uvadlc.github.io, and his course has been shortlisted worldwide for those interested in delving into deep learning. His research focus is on temporal learning and dynamics, novel spatiotemporal representations and deep machine learning.