ADS Webinar | AI for the City of Amsterdam

Amsterdam Data Science in collaboration with the City of Amsterdam, UvA and the VU are hosting a webinar on the implementation of AI in the city of Amsterdam.

At the city of Amsterdam, they believe Artificial Intelligence will have a significant impact on the people living in Amsterdam. But how do we encourage positive developments, solve complex challenges and apply the necessary regulation to avoid any negative effects?

AI not only stands for Artificial Intelligence but also for ‘Amsterdam Intelligence’, the essence of which is the fair and just use of technology in a manner that reinforces our status as an inclusive, free and creative city.

12:00 Introduction & Welcome
12:05 Talk #1 Amsterdam Intelligence
12:30 Talk #2 4x Student presentations
12:50 Q&A
13:00 End!

Talk #1 by Maarten Sukel and Daan Bloembergen
The AI team of the City of Amsterdam is focused on using Artificial intelligence to solve the challenges of the city and increase the livability for the people of Amsterdam. An example would be using machine learning to route service requests made by citizens more efficiently, computer vision scanning the streets of the city for issues, or using computer vision techniques to make pedestrians more aware of keeping sufficient distance.

In this presentation, Maarten Sukel from the City of Amsterdam will give a quick overview of some AI and Data science projects the city is working on, and Daan Bloembergen will discuss semantic segmentation of street-level point cloud data

Daan Bloembergen is an AI researcher with a background in machine learning and multi-agent reinforcement learning. He is currently working on the semantic segmentation of street-level point cloud data within the AI Team of the City of Amsterdam.

Maarten Sukel is AI lead at the city of Amsterdam and a PhD. researcher at the University of Amsterdam. Examples of projects he has been working on are a system that automatically routes service requests and the urban Object Detection Kit(, a system capable of detecting issues on the streets of the city using computer vision.

Talk #2 Student presentations
Several VU and UvA interns are writing their thesis at the City of Amsterdam and will present their research.

Sierk Kanis is a research intern at the AI Team and is currently working on self-learning traffic lights to decrease travel time and CO2 emission in the city. The project focuses on applying reinforcement learning techniques in order to make the computer learn to real-time adapt to approaching traffic.

Tom Lotze is a MSc AI student at the University of Amsterdam. He is currently working on unsupervised object discovery and object insertion using Generative Adversarial Networks. Ultimately, this knowledge could be used to visualize policy or let citizens envision ideas for their city, such as adding greenery in a street scene, or removing parked cars.

Kaleigh Douglas is a MSc AI student at the University of Amsterdam. She is currently working on a method of anonymizing people in city images by using Generative Adversarial Networks to replace real people with generated fake people. The goal is to protect the privacy of individuals who appear in public images, while also maintaining a realistic image.

Selma Muhammad is a MSc AI and Msc Philosophy student at the VU, where she applies her knowledge from both disciplines in the Ethical AI and Fairness domains. She is currently working on developing an automatic bias detection method by clustering the errors of ML models. As the method is model-agnostic and requires little domain expertise, it can be used to detect algorithmic bias in a wide range of algorithms used by the City

This event is hosted on Hopin, you will have to get a ticket to access the event: