3mE well represented in TU Delft AI labs

News - 02 June 2020 - Webredactie 3ME

Today TU Delft launched eight new 'TU Delft AI Labs'. The goal is to use artificial intelligence (AI) to accelerate scientific progress. The labs bring together scientists doing research in AI and with AI.

The first eight TU Delft AI Labs are:

  • 3DUU - 3D Urban Understanding
  • AidroLab - Artificial intelligence research in water management
  • CTAI-Lab - CiTy AI Lab
  • DeTAIL - Delft Tensor AI Lab
  • DI_Lab - Designing Intelligence Lab
  • IRIS - Intelligent & Reliable Imaging Systems
  • MACHINA - Machine Intelligence Advances for Materials
  • AI*MAN-lab - Transparent & Traceable AI in Human-AI Teamwork

In the course of 2020 and 2021, these eight interdisciplinary AI labs will be expanded with another sixteen labs. Recruitment for scientific talent will start on 2 June. The Faculty of Mechanical Engineering is well represented in the labs. Here is an overview of the labs with our scientists’ projects:


  • Understanding and modelling Urban environments in 3D
  • Julian Kooij (Cognitive Robotics) in cooperation with Liangliang Nan (Faculty of Architecture)

The aim of the 3DUU lab is to develop novel methods and techniques to automatically identify and model real-world objects in 3D for large-scale urban environments. These objects range from large structures such as buildings down to small structures such as trees, lampposts, and traffic signs. Read more.

DeTAIL (Delft Tensor AI lab)

  • Training & innovation in tensor-based AI methods for biomedical signals
  • Kim Batselier (Delft Center for Systems and Control) & Borbála Hunyadi (EEMCS)

Within the DeTAIL Lab, the researchers focus on both the development and application of novel low-rank tensor methods for biomedical signal processing, thereby enabling a much faster training of AI models from large datasets without any loss of accuracy. Read more.

IRIS (Intelligent & Reliable Imaging Systems)

  • AI for quantitative imaging
  • Carlas Smith (Delft Center for Systems and Control), David Maresca  and Arjen J. Jakobi (AS)

The aim of the IRIS lab is to open the black box of AI and develop methodologies for context-independent, knowledge-based learning of imaging systems that will address fundamental challenges in all quantitative imaging applications. Read more.

MACHINA (Machine Intelligence Advances for Materials)

  • Miguel Bessa (Materials Science and Engineering) & Angelo Accardo (Precision and Microsystems Engineering in cooperation with Deepesh Toshniwal (EWI) en David Tax (EEMCS)

The aim of the MACHINA lab is to discover new materials and structures by bridging the gap between machine learning developers (researchers working in AI) and practitioners (researchers working with AI). Read more.

Read the press release ‘TU Delft launches first eight TU Delft AI Labs’