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Safe and robust decision making

Safe and robust decision making by Matthijs Spaan When autonomous systems interact with the real world, their performance is brittle. Their decisions are often only reliable in situations that are close to those they encountered during training. Furthermore, mistakes can have grave consequences in safety-critical domains. If we want to be able to trust AI systems, we need guarantees on their safety and robustness. This research themes focuses on safe and robust decision making when models of the environments are (partially) unknown.

Interactive learning & decision making

Interactive learning & decision making

Current projects

Data-driven blended care solution with virtual buddy for child health Catharine Oertel and Mark Neerincx received funding for a new research project ePartners4All: a (personalised and) blended care solution with a virtual buddy for child health. In this project, they take digital support of school-aged children and their caregivers a big leap forward, by not only monitoring their health, but also providing interactive e-health solutions (so-called ePartners), including robot buddies and virtual agents that enhance children’s health and well-being. A needs assessment, ePartners4All development, and pilot study will be performed in co-creation with end-users. These ePartners can help to prevent health problems in at-risk children, and it can help to recognise and treat health problems at an early-stage, thereby preventing deterioration of the problem. In this way, ePartners4All can help to create a more resilient society. Altogether, it could lead to lower healthcare utilisation and, in the long-run, a more resilient workforce with lower losses of productivity. Topics of the research are: ........ ......... The aim of the research involves ..... Staff involved: Catharine Oertel and Mark Neerincx . Dog Cognition Prof. Dr. Catholijn M. Jonker (INSY-depart. Delft Univ. of Technology), Dr. Tibor Bosse (AI dept. Vrije Universiteit Amsterdam), and International Behavioural Therapeutic Centre “Stichting De Roedel” initiated a long term research programme on dog cognition. The research is based on a set of aspects that are important to the method developed by International Behavioural Therapeutic Centre “Stichting De Roedel” to improve the relation between handler and dog. Topics of the research are: The relation between scent- and body-language. How does this relation affect behaviour and how do other stimulants from the environment influence this behaviour. The aim of the research involves a better understanding of dog behaviour thus supporting improvements in dog education methods. Staff involved: Catholijn M. Jonker . Hybrid Intelligence Hybrid Intelligence (HI) is the combination of human and machine intelligence, expanding human intellect instead of replacing it. HI takes human expertise and intentionality into account when making meaningful decisions and perform appropriate actions, together with ethical, legal and societal values. Our goal is to design Hybrid Intelligent systems, an approach to Artificial Intelligence that puts humans at the centre, changing the course of the ongoing AI revolution. Staff involved: Catholijn M. Jonker , Mark Neerincx , Frans Oliehoek and Myrthe Tielman . Ethics of Socially Disruptive Technologies Throughout history, technology has been a driver of social change. The technologies of the industrial revolution played a crucial role in shaping modern society, and society has since then continued to be shaped by technological innovations. The project focuses on technologies that will not just change specific domains or practices for which they were designed, but that will change our life in a much broader sense. They are called socially disruptive technologies (SDTs). SDTs transform everyday life, social institutions, cultural practices, and the organisation of the economy, business, and work. They may even affect our fundamental beliefs, rights, and values. Artificial Intelligence is one of those techniques. Together with the philosophers of technology we research new ethical frameworks and concepts to obtain ethical AI by design. Staff involved: Catholijn M. Jonker . INFLUENCE Decision-theoretic sequential decision making (SDM) is concerned with endowing an intelligent agent with the capability to choose the 'best' actions, i.e., those that that optimize the agent's performance on its task. SDM techniques have the potential to revolutionize many aspects of society, and recent successes, e.g., agents that learn to play Atari games and beat master Go players, have sparked renewed interest in this field. However, despite these successes, fundamental problems of scalability prevent SDM methods from addressing other problems with hundreds or thousands of state variables. To overcome this barrier, INFLUENCE will develop a new class of `influence-based SDM methods' that address scalability issues by using novel ways of abstraction, thus making an important step towards realizing the promise of autonomous agent technology. Staff involved: Frans A. Oliehoek . M2MGrids The M2MGrids project aims to develop a horizontal platform in which physical sensors and devices can communicate with IT systems to allow for smart information exchange. A key business case within the project involves the research and development of automated dynamic power systems to allow for a smart flow of energy and data within the energy grid. As an example, imagine a scenario where a high power consumption is measured for a certain district of consumer homes. A present-day solution would be to raise the production of power to balance the consumption and production of power. However, a smart solution would be to re-schedule certain flexible devices within the home of a consumer (like a dishwasher or a washing machine) such that this problem dissolves by merely using devices and data in a smart way. Within the M2MGrids project, Delft is using their negotiation theory expertise to research and develop platforms which can be used within future smart homes to enable this smart scheduling of flexible devices. By creating platforms that enables a more effective and efficient use of energy, Delft is paving the way for a better and greener future! Staff involved: Catholijn M. Jonker . ReJAM The ReJAM project aims to develop Robots engaging elderly in Joint Activities with Music. The objective of ReJAM is the promotion of physical, cognitive, emotional and social wellbeing through various music-related activities, e.g. physical exercises, games, reminiscence, and making music together. The activities are designed especially for group activities: ReJAM is well-suited for use in meeting centers or together with visitors at home. Staff involved: Mark A. Neerincx . CoreSAEP: Computational Reasoning for Socially Adaptive Electronic Partners The overall aim of the project is to develop a reasoning framework that combines logic and quantitative techniques for Socially Adaptive Electronic Partners (SAEPs) that adapt their behavior to norms and values of people. This becomes more and more important as technology becomes an integral part of our daily lives. The computational reasoning techniques are aimed at determining when and to what extent norm-compliance can be guaranteed, and deciding what to do if in exceptional situations a norm cannot or should not be complied with. Staff involved: Myrthe Tielman (PI), Catholijn M. Jonker . PAL: Personal Assistant for healthy Lifestyle The PAL (Personal Assistant for healthy Lifestyle) project proposal for Horizon 2020 was “favourably evaluated” and started on the 1st of March 2015 (EU grant is 4.5M Euro; ref. H2020-PHC-643783). This 4 year project involves the research partners TNO (coordinator), DFKI, FCSR, Imperial and Delft University of Technology, next to end-users (the hospitals Gelderse Vallei and Meander, and the Diabetics Associations of Netherlands and Italy), and SME’s (Mixel and Produxi). PAL will use, refine and extend the knowledge-base and support models of ALIZ-E to improve child’s diabetes regimen by assisting the child, health professional and parent. The PAL system will be composed of a social robot (NAO), its (mobile) avatar, and an extendable set of (mobile) health applications (diabetes diary, educational quizzes, sorting games, etc.), which all connect to a common knowledge-base and reasoning mechanism. Staff involved: Mark A. Neerincx . COMMIT/ - IUALL: A Value-sensitive mobile social application for families and children We try to create mobile apps that provide value-sensitive support for families with children in the elementary school age, through using agreement technologies such as norms and social commitments. Staff involved: Mark A. Neerincx . TRADR: Designing the mind of a robotic teammember Robots can be useful members of a rescue team in case of a disaster, but only if they do not burden the humans with complex controls. In my work I search for ways to make robots good team-members, so they automatically know where and to whom they can be of use. One of my methods is to systematically sabotage robot communication to find out what are good strategies to recover from this. Staff involved: Mark A. Neerincx . VESP: Virtual eCoaching and storytelling technology for post-traumatic stress disorder treatment This project studies how effectively and in what manner a stand-alone, multi-modal memory restructuring (3MR) system and Internet-based guided self-therapy version could be used for the treatment of post-traumatic stress disorder patients (PTSD). Staff involved: Mark A. Neerincx , Willem-Paul Brinkman . Negotiation Negotiation is a complex emotional decision-making process aiming to reach an agreement to exchange goods or services. Although a daily activity, few people are effective negotiators. Existing support systems make a significant improvement if the negotiation space is well-understood, because computers can better cope with the computational complexity. However, the negotiation space can only be properly developed if the human parties jointly explore their interests. The inherent semantic problem and the emotional issues involved make that negotiation cannot be handled by artificial intelligence alone, and a human-machine collaborative system is required. We are developing a new type of human-machine collaborative system that combines the strengths of both and reduces the weaknesses. Fundamental in these systems will be that user and machine explicitly share a generic task model. Furthermore, such systems are to support humans in coping with emotions and moods in human-human interactions. For this purpose we will contribute new concepts, methods and techniques. For integrative bargaining we will develop such a system, called a Pocket Negotiator, to collaborate with human negotiators. The Pocket Negotiator will handle computational complexity issues, and provide bidding- and interaction advice, the user will handle background knowledge and interaction with the opponent negotiator. Staff involved: Catholijn M. Jonker . SocioCognitive Robotics The Interactive Intelligence section and TNO work on socio-cognitive robots that are able to interact with humans. Staff involved: Mark A. Neerincx .

People

Professors Prof. dr. ir. J. (Hans) Hellendoorn Head of department Director of Education & Graduate School Autonomous Robots & software-based control architectures Knowledge Representation, Model-based Systems Engineering, Self-adaptive Systems Prof. dr. ir. D.A. (David) Abbink Human-Robot Interaction Human-Robot Interaction, Shared Control, Haptic Interaction, Driver Modeling, Interface Design, Tele-robotics, Meaningful Human Control Prof. dr. R. (Robert) Babuska Group leader Learning and Autonomous Control Reinforcement learning, nonlinear control, data-driven model construction, deep learning Prof. dr. D.M. (Dariu) Gavrila Group leader Intelligent Vehicles Intelligent Vehicles, Machine Perception Prof. Dr. ir. R. (Riender) Happee Intelligent Vehicles Human factors and comfort of automated driving Prof. Dr. ir. J.C.F. (Joost) de Winter Human-Robot Interaction Human Factors, simulation, driver assessment, statistics, automated driving Prof. dr. ir. M. (Martijn) Wisse Group leader Robot Dynamics Biorobotics Associate Professors / Senior Lecturers Dr. J. (Javier) Alonso-Mora Learning and Autonomous Control Motion Planning, Multi-robot Systems, Robot Autonomy , Intelligent Transportation, Learning for Coordination and Planning Dr. ir. C. (Carlos) Hernández Corbato Robot Dynamics Autonomous Robots, Software-based Control Architectures, Knowledge Representation and Reasoning, Self-Adaptive Systems, Model-Based Systems Engineering Dr. ing. J. (Jens) Kober Learning and Autonomous Control Motor Skill Learning, Reinforcement Learning, Imitation Learning, Deep Learning, Interactive Learning Dr. J.F.P. (Julian) Kooij Intelligent Vehicles Multi-sensor Perception, Machine Learning, Self-driving vehicles, Situation analysis and Prediction, Probabilistic inference, Representation learning, 3D Urban Understanding lab Dr. ing. L. (Laura) Marchal Crespo Group leader Human-Robot Interaction Rehabilitation robotics, motor learning, neurorehabilitation, sensorimotor training, robot control, virtual/augmented reality Dr. ir. G.N. (Gillian) Saunders Robot Dynamics Senior Lecturer Engineering Education, Competencies & Skills, Assessment & Curriculum Development Dr. B. (Barys) Shyrokau Intelligent Vehicles Dynamics, Vehicle Control, ADAS/AD Dr. M. (Michaël) Wiertlewski Human-Robot Interaction Human-Machine Interaction, Friction modulation, Haptics Assistant Professors Dr. H. (Holger) Caesar Intelligent Vehicles Deep learning, Autonomous Vehicles, Perception, Prediction, ML Planning, Active learning Dr. C. (Cosimo) Della Santina Learning and Autonomous Control Soft Robotics, Robot Control, Learning for Control, Robotic Hands, Nonlinear Dynamics, Human Motor Control Dr. Ir. Y.B. (Yke Bauke) Eisma Human-Robot Interaction Eye-tracking and visual attention modelling, Gaze-contingent paradigms, Attention-based robot control Psychometrics, Expertise measurement Dr. L. (Laura) Ferranti Learning and Autonomous Control Cooperative Control, Real-time Optimization, Fault-tolerant Control Mobile Robots, Privacy-preserving Motion Planning Dr. G. (Georgios) Papaioannou Intelligent Vehicles Motion comfort, human perception, postural stability, human body modelling, seat design, vehicle control Dr. C. (Chris) Pek Robot Dynamics Robot safety, task and motion planning, formal methods, machine learning, human-robot interaction Dr. L. (Luka) Peternel Human-Robot Interaction Physical Human-Robot Interaction, Teleoperation, Robotic Manipulator Control, Robot Learning, Human Motor Control Dr. J.M. (Micah) Prendergast Human-Robot Interaction Medical Robotics and Rehabilitation, Human-Robot Interaction, Robot Perception and Control Dr. Y. (Yasemin) Vardar Human-Robot Interaction haptic interface technology, understanding tactile contact, human-machine interaction Dr. A. (Arkady) Zgonnikov Human-robot Interaction Human cognition, Cognitive modeling, Driver behavior, Traffic interactions, Meaningful human control Support J. (Jolanda) Dijkshoorn Department Manager E.M. (Ellen) Driessen Management - / Office Assistant N. (Noortje) Fousert Management - / Office Assistant & Event management PA Head of department H.M. (Hanneke) Hustinx Management - / Office Assistant (Coordinator) K. (Kseniia) Khomenko Assistent lecturer/Junior researcher assistant L.A.M. (Loulou) Zorgui-Martens Management - / Office Assistant K.J. (Karin) van Tongeren Assistant MSc Coördinator Robotics/Vehicle Engineering/ BioRobotics/Haptic Interfaces Technical Support Ir. R.M. (Ronald) Ensing Intelligent Vehicles Dr. M.A. (Mario) Garzon Intelligent Vehicles Ir. G.A. (Gijs) van der Hoorn Robot Dynamics A.A.M. (André) van der Kraan Cognitive Robotics M. (Maurits) Pfaff Cognitive Robotics Teachers Ir. C. (Cilia) Claij Cognitive Robotics Junior Docent Ir. T. (Thijs) Hoedemakers Cognitive Robotics Junior Docent M. (Martin) Klomp MSc Robot Dynamics Researchers and PostDocs Dr. G. (Gang) Chen Learning and Autonomous Control C.S. (Charlotte) Croucher Intelligent Vehicles Dr. J. (Jiatao) Ding Learning and Autonomous Control Dr. D.F. (Deborah) Forster Human-Robot Interaction A. (Alex) Gabriel Robot Dynamics A. (Ahmad) Gazar) Learning and Autonomous Control Ir. O.M. (Oscar) de Groot Intelligent Vehicles A. (Arend-Jan) van Hilten Robot Dynamics Education Robot Developer A. (Alessandro) Ianniello Human-Robot Interaction G. (Guopeng) Li Intelligent Vehicles Y. (Yancong) Lin Intelligent Vehicles F. (Federico) Scarí Human-Robot Interaction Dr. E. (Ebrahim) ShahabiShalghouni Learning and Autonomous Control Ir. O. (Olger) Siebinga Human-Robot Interaction Dr.ir. J. (Joris) Sijs Learning and Autonomous Control State estimation, navigation, automated planning, knowledge representation and reasoning Dr. B. (Burak) Şişman Robot Dynamics Ir. M. (Max) Spahn Learning and Autonomous Control S. (Sihao) Sun Learning and Autonomous Control W. (Wilbert) Tabone Human-Robot Interaction F. (Farzam) Tajdari Intelligent Vehicles D. (Daniel) Feliu Talegón Learning and Autonomous Control Ir. E. (Elia) Trevisan Learning and Autonomous Control C. (Cong) Wang Learning and Autonomous Control N. (Nils) Wilde Learning and Autonomous Control L. (Laurence) Willemet Human-Robot Interaction PhD Students S. (Saray) Bakker Learning and Autonomous Control I. (Italo) Belli Human-Robot Interaction Ir. D. (Dennis) Benders Learning and Autonomous Control Ir. A. (Alex) van den Berg Human-Robot Interaction A. (Alberto) Bertipaglia Intelligent Vehicles H.J. (Hidde) Boekema Intelligent Vehicles Z. (Zhaochong) Cai Human-Robot Interaction T. (Tomás) Coleman Learning and Autonomous Control S.L. (Salvo) Cucinella Human-Robot Interaction A. (Alberto) Garzás Villar Human-Robot Interaction Ir. A. (Ashwin) George Human-Robot Interaction R. (Roel) Horeman Human-Robot Interaction Y. (Yuxuan) Hu Human-Robot Interaction V. (Vishrut) Jain Intelligent Vehicles E. (Ekaterina) Karmanova Human-Robot Interaction C.U. (Celal) Kenanoğlu Human-Robot Interaction Ir. V. (Varun) Kotian Intelligent Vehicles L. (Luzia) Knödler Learning and Autonomous Control J. (Jagan) Krishnasamy Balasubramanian Human-Robot Interaction L. (Zhaoting) Li Learning and Autonomous Control Ir. J. (Jingyue) Liu Learning and Autonomous Control Ir. J.D. (Jelle) Luijkx Learning and Autonomous Control Ir. L. (Lorenzo) Lyons Learning and Autonomous Control A. (Andreu) Matoses Gimenez Learning and Autonomous Control C. (Chrysovalante) Messiou Intelligent Vehicles Ir. N. (Nicky) Mol Human-Robot Interaction A. (Anna) Mészáros Learning and Autonomous Control K. (Khaled) Mustafa Learning and Autonomous Control L. (Lasse) Peters Learning and Autonomous Control M. (Mariano) Ramírez Montero Learning and Autonomous Control A.R. (Alex) Ratschat Human-Robot Interaction G. (Gustavo) Rezende Silva Robot Dynamics Ir. J.F. (Julian) Schumann Human-Robot Interaction M.W. (Maximilian) Stölzle Learning and Autonomous Control L. (Lukas) Stracovsky Human-Robot Interaction Y. (Yujie) Tang Robot Dynamics T. (Tasos) Tsolakis Learning and Autonomous Control G. (Giuseppe) Vitrani Human-Robot Interaction T. (Ted) de Vries Lentsch Intelligent Vehicles S. (Shiming) Wang Intelligent Vehicles M. (Mubariz) Zaffar Intelligent Vehicles F. (Forough) Zamani Robot Dynamics C. (Chuhan) Zhang Learning and Autonomous Control R. (Renchi) Zhang Human-Robot Interaction

GovTech over BigTech

GovTech, the co-development of government technology by public and private parties, is on the rise. GovTech can better safeguard public values and make governments less dependent on tech giants such as Amazon, Google and Microsoft. In the Digicampus partnership, co-founded by TU Delft, prototypes of GovTech technology are being developed, including a successor to DigiD.

TU Delft AE Diversity & Inclusion ‘Safety Beyond Boundaries’ Panel

TU Delft AE Diversity & Inclusion ‘Safety Beyond Boundaries’ Panel 19 September 2024 17:30 till 19:30 - Location: TU Delft Faculty of Aerospace Engineering, Lecture room A | Add to my calendar Safety Beyond Boundaries: Bridging Aerospace and LGBTIQ+ Safety Join us for an enlightening event titled "Safety Beyond Boundaries", where we delve into the fascinating parallels between aerospace safety and LGBTIQ+ safety. Our goal is to draw insights from the rigorous and evolving safety practices in aerospace to better understand and enhance safety within the LGBTIQ+ community. Aerospace safety has long been shaped by learning from unforeseen accidents and continuously adapting to meet safety standards. The sector is a model of vigilance and responsiveness, recognizing that safety is an ongoing process that demands constant attention and adaptation. In much the same way, ensuring safety within the LGBTIQ+ community requires ongoing awareness, flexibility, and proactive measures. Just as the aerospace sector cannot afford to be complacent, neither can we when it comes to fostering a secure and supportive environment for everyone. At this event, we will explore these parallels through a panel discussion featuring members of the LGBTIQ+ community and key figures from our own faculty. Together, we will examine existing safety practices, identify areas for improvement, and work towards creating an even safer and more inclusive environment—just as the aerospace industry continually strives to do. Join us in this crucial dialogue as we work together to build not only a safer environment for today but also a secure foundation for the future. Let’s stay vigilant, stay prepared, and understand that the safety of tomorrow begins with the actions we take today!

Education

Education Courses 2024/2025 Data Science and Artificial Intelligence for Engineers | CEGM2003 Machine Learning for Graph Data | CS4350 Modeling Uncertainty and Data for Engineers | CEGM1000 Mutimedia Analysis | CSE2230 Signal Processing | CSE2220 2023/2024 Data Science and Artificial Intelligence for Engineers | CEGM2003 Machine Learning for Graph Data | CS4350 Modeling Uncertainty and Data for Engineers | CEGM1000 Research skills 1 | CIE5431 Mutimedia Analysis | CSE2230 Signal Processing | CSE2220 2022/2023 Data Science and Artificial Intelligence for Engineers | CEGM2003 Machine Learning for Graph Data | CS4350 Modeling Uncertainty and Data for Engineers | CEGM1000 Research skills 1 | CIE5431 Mutimedia Analysis | CSE2230 Signal Processing | CSE2220 2021/2022 Applied Machine Learning | CS4305TU Research skills 1 | CIE5431 Mutimedia Analysis | CSE2230 Signal Processing | CSE2220 2020/2021 Applied Machine Learning | CS4305TU Research skills 1 | CIE5431 Mutimedia Analysis | CSE2230 2019/2020 Research skills 1 | CIE5431 Mutimedia Analysis | CSE2230 Signal Processing | CSE2220 Master projects Ongoing Applied AI projects Distribution System State Estimation with Graph Neural Networks ML for Dynamics in power systems Algorithms for Distribution Grid Expansion Reinforcement Learning for Congestion Management Incentive-Based Community Management with Network Constraints Stable Diffusion for Energy-system Optimized Solar Nowcasting User-centric EV charging cycles to maximise battery lifetime Fundamental AI projects Non-intrusive load monitoring for residential houses Scalable dictionary learning to learn high-level features Multivariable Anomaly Detection Framework for Multi-sensor Network Fault Detection and Isolation of Nonlinear Systems with Optimized Model Mismatch Robustness in Fault Diagnosis applied in the Lateral Control of Automated Vehicles Transferring Domain Knowledge to Data-driven Controller Associated projects MSc Project proposal: Correlations for the hydrodynamics of spouted bubbling fluidized beds uzing CFD, ANN's & ecperiments Finished “Reinforcement Learning for Coordinating Energy communities”, Catarina Santos Neves, TU Delft in collaboration with Instituto Superior Técnico, Lisbon, Portugal “Market mechanisms for Frequency Service provided by Dynamic Virtual Power Plants”, Torben Zeller, TU Delft in collaboration with RWTH Aachen University “Quantum Computing for Power Systems” Hjalmar Lindstedt, TU Delft “Market Mechanism Design for Virtual Inertia”, Johnny Zheng, TU Delft “Reinforcement learning for transmission network topology control” Geert-Jan Meppelink, TU Delft, in collaboration with NTNU, Trondheim, Norway “Neural Ordinary Differential Equations for Frequency Dynamics” Nila Krishnakumar, TU Delft “End-to-end learning for N-k SC-OPF” Bastien Giraud, TU Delft, in collaboration with NTNU, Trondheim, Norway “Data-Driven Adaptive Dynamic Equivalents of Active Distribution and Transmission Networks” Alex Neagu, TU Delft End-to-End Learning for Sustainable Energy Systems with PV and Wind, Rushil Vohra, TU Delft Meter Placement for Estimating Power System States, Sattama Datta, TU Delft thesis together with Alliander, DSO Netherlands Graph Neural Networks for State Estimation, Benjamin Habib, TU Delft thesis together with Stedin, DSO Netherlands Prediction of malfunctioning of PV panels with Machine Learning, Dion de Mooy, TU Delft End-to-End Learning for Sustainable Energy Scheduling, Dariush Wahdany, TU Delft, RWTH Aachen University Multi-Agent Reinforcement Learning for Incentive-based Residential Demand Response, Jasper van Tilburg, TU Delft On the Road from Active Inference to Regret Minimization, TU Delft, 2021 Conjugate Dynamic Programming, TU Delft, 2021 Tractable Algorithms for Large Scale Mixed Integer Quadratic Programming: A Principal Component Analysis Approach, TU Delft, 2021 Learning Parametric Mixed Integer Quadratic Programming via Inverse Optimization, TU Delft, 2021 On Complexity of Data-driven Controls in Stochastic Environments, TU Delft, 2021

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Graduation Awards Ceremony & Exhibition 2023-2024

On 14 October, the nominated and winning projects of the Circularity in the Built Environment Graduation Awards 2023-2024 will be announced. Do you want to learn more about the projects? Join the awards ceremony on 14 October or visit the exhibition in the corridor around the Oostserre between 14 and 30 October.

Upcoming debate: Material culture - a broader vision on heritage

On 22 October, the sixth debate in the 'Making the Circular Built Environment a Reality' series focuses on the cultural dimensions of transitioning to a circular built environment. This conversation introduces a fresh viewpoint on cultural heritage, focusing on historical and aesthetic values embedded in materials.

Interview with Jan-Carel Diehl: “TU Delft can be one big playground”

Professor of Design for Inclusive Sustainable Healthcare Jan-Carel Diehl combines healthcare solutions with care for our planet. His many projects make an impact from Rotterdam to Sub-Saharan Africa. Where does he want to make a difference? What is he most proud of? And where lies the added value of a designer in the healthcare sector? Find out in this interview. Prof Diehl gives his inaugural lecture at TU Delft's Aula on Friday 11 October.

Study Abroad week 14 – 18 October

Informational week for a semester abroad. Every year in October all faculties hold ‘Study Abroad Week’ events whereby they give presentations about the possibilities of going abroad as part of your study programme. They provide information regarding the partners, destinations, and application process. Students who have been abroad share their experiences too. If you are thinking about going abroad as part of your BSC of MSc programme, keep an eye on your faculty Brightspace page, faculty website or this page for more information. This academic year the Study Abroad Sessions will be held from 14 – 18 October (except for the Faculty of Applied Sciences, they will hold theirs from 21 – 25 October) for students planning to go abroad as part of their study programme in the academic year 2025-2026. Also there will be hosted an online Q&A session about scholarships: we will answer the top 5 questions we receive about the scholarships and give you the opportunity to ask questions too. More details about the Study abroad sessions will be posted here shortly.

Quarterly report to education inspectorate

Together, we build a safer working environment at TU Delft. Each month, we reflect on the previous month: what actions were taken as part of the Plan for Change, and we look ahead to the upcoming month: what's on the agenda.

Security & Privacy Symposium

In the month of October, various activities will be organized that focus on information security and privacy. One of these activities is the Security & Privacy Symposium on October 10 from 1:30 PM to 5:00 PM.​​​​​ During the symposium, employees and students can listen to several interesting speakers who are experts in the field of information security and privacy. Bert Hubert , expert in the field of information security, tells you who keeps hacking us and why. He is a former supervisor at the AIVD and a scientist. He can tell you about themes such as cybersecurity, innovation, science and data in an understanding and compelling way like no other. Arnoud Engelfriet makes us aware of the privacy risks that we run every day. Arnoud is a privacy expert and an expert in the field of law and the internet. He wrote the book ‘AI and Algorithms’, among other things. The symposium ends with an interactive session with our a.i. Chief Privacy Officer (CPO) and Chief Information Security Officer (CISO). During this session we will look at the state of information security and privacy within TU Delft. The afternoon will be presented by Rini van Solingen and will be in English. You can register here .

NWO grants funding for innovative research on physical experimental environments

The Netherlands, recognised as a European leader in innovation, is home to more than 100 experimental environments. These environments range from controlled field labs to more open, participatory urban living labs. A consortium in which Alfons van Marrewijk (MBE) among others, has been awarded a prestigious grant from the Netherlands Organisation for Scientific Research (NWO) to explore how various forms of innovation in field labs, such as the Green Village, urban living labs such as Engy Lab South-East in Amsterdam, and in all sorts of citizens’ initiatives, can be mainstreamed and make more impact on sustainability transitions.

The Educator Newsletter | September

Discover inspiring stories, developments, (training) activities, and other reads about Education.

TU Delft helps Maastricht air traffic controllers make safe choices

In March 2024, the EUROCONTROL air traffic control centre MUAC in Maastricht launched a new software tool that allows their air traffic controllers to make faster and more intuitive decisions about air traffic in their area. The tool was developed by MUAC , but is based on research into ecological interfaces by colleagues Clark Borst, René van Paassen and Max Mulder at Control & Simulation.

New ‘captains’ in the cockpit of Rotterdam The Hague Innovation Airport

On 1 September, Jos van den Boom, Lennard Verhoeff, and Victor Rijkaart joined the new executive team of Rotterdam The Hague Innovation Airport (RHIA).This trio is preparing to usher in the next phase of RHIA. A period in which, community-driven, privately led and publicly supported, they want to make visible and where possible accelerate the transition to a cleaner, quieter and smarter future of aviation.

Systems Workforce Summit 2024 at TU Delft

As the need for systems engineers is rising, TU Delft and NXTGEN Hightech are organising a unique global event on systems engineering on October 8 and 9, 2024. Thoughtleaders from organisations such as Airbus, ASML, MIT and NASA will discuss the future needs of the Systems Engineering workforce tackling the major transformations in society.

The Systems Workforce summit

TU Delft and NXTGEN Hightech will organize the unique worldwide Systems Workforce Summit at the TU Delft on October 8 and 9, 2024. Reserve your spot now to attend this unique summit! This global summit will address the future of systems engineering in industries like energy, health, aerospace, semicon and transportation. Skilled systems engineers are scarce and in high demand by enterprises worldwide. Cooperation between the diverse organizations participating in this Summit could significantly advance the needed 'Workforce of the Future'. This Summit is open to: Professionals from various industries: junior, senior or potential systems engineers/systems architects, less or more experienced; Scientists of knowledge institutes working in the discipline of systems engineering, management, technology or policy; Talents/students from engineering disciplines interested in systems engineering/system thinking. From universities and universities of applied sciences. Date: 8 & 9 October 2024 Location: TU Delft Aula Conference Centre Click here to register

First-ever imaging of pathogens on lettuce leaves in real-time

Met een groeiende wereldbevolking van meer dan 8 miljard mensen is voldoende voedsel produceren een uitdaging. Nederland is ‘s werelds tweede exporteur van voedsel en verbouwt enorm efficiënt allerlei gewassen. Plantenziektes zoals valse meeldauw zijn echter een veelvoorkomend probleem dat de oogst van de boer flink kan bederven. Delftse wetenschappers hebben voor het eerst een manier ontwikkeld om de infectie in planten real-time te volgen, zonder de plant te hoeven doden. De hiermee opgedane kennis helpt om nieuwe resistente gewassen te kweken met een hogere opbrengst en minder gebruik van pesticiden. Het onderzoek staat nu in Nature Communications.

New LDE trainee in D&I office

Keehan Akbari has started since the beginning of September as a new LDE trainee in the Diversity and Inclusion office. What motivated him to work for the D&I office, what does he expect to achieve during this traineeship? Read the short interview below! What motivated you to pursue your LDE traineeship in Diversity and Inclusion office of the TU Delft? I completed both bachelor's and master's degrees in Cultural Anthropology and Development Sociology at Leiden University. Within these studies, my main area of interest was in themes of inclusion and diversity. After being hired as a trainee for the LDE traineeship, and discovering that one of the possible assignments belonged to the Diversity and Inclusion office, my choice was quickly made. I saw this as an excellent opportunity to put the theories I learned during my studies into practice. What specific skills or experiences do you bring to the D&I office that will help promote inclusivity on campus? I am someone who likes to connect rather than polarize, taking into account the importance of different perspectives and stakeholders. I believe that this is how one can achieve the most in fostering diversity and inclusion. You need to get multiple parties on board to get the best results. What are your main goals as you begin your role here, and how do you hope to make an impact? An important goal for me this year is to get students more involved in diversity and inclusion at the university. One way I will try to accomplish this is by contributing to the creation of D&I student teams. By establishing a D&I student team for faculties, it will be possible to deal with diversity- and inclusion-related issues that apply and relate to the specific department. How do you plan to engage with different (student) communities within the university? Since I am new to TU Delft, the first thing I need to do is expand my network here. Therefore, I am currently busy exploring the university and getting to know various stakeholders. Moreover, I intend to be in close contact with various student and study organizations to explore together how to strengthen cooperation on diversity and inclusion. Welcome to the team Keehan and we wish you lots of success with your traineeship!

Researchers from TU Delft and Cambridge University collaborate on innovative methods to combat Climate Change

For over a year and a half, researchers from TU Delft and the Cambridge University Centre for Climate Repair have worked together on groundbreaking techniques to increase the reflectivity of clouds in the fight against global warming. During a two-day meeting, the teams are discussing their progress. Researchers at Cambridge are focusing on the technical development of a system that can spray seawater, releasing tiny salt crystals into the atmosphere to brighten the clouds. The team from TU Delft, led by Prof. Dr. Ir. Herman Russchenberg, scientific director of the TU Delft Climate Action Program and professor of Atmospheric Remote Sensing, is studying the physical effects of this technique. Prof. Russchenberg emphasizes the importance of this research: "We have now taken the first steps towards developing emergency measures against climate change. If it proves necessary, we must be prepared to implement these techniques. Ideally, we wouldn't need to use them, but it's important to investigate how they work now." Prof. Dr. Ir. Stefan Aarninkhof, dean of the Faculty of Civil Engineering and Geosciences, expresses pride in the team as the first results of this unique collaboration are becoming visible. If the researchers in Delft and Cambridge can demonstrate the potential of the concept, the first small-scale experiments will responsibly begin within a year. This research has been made possible thanks to the long-term support from the Refreeze the Arctic Foundation, founded by family of TU Delft alumnus Marc Salzer Levi . Such generous contributions enable innovative and high-impact research that addresses urgent global challenges like climate change. Large donations like these enable the pursuit of innovative, high-impact research that may not otherwise be feasible, demonstrating how our collective effort and investment in science can lead to real, transformative solutions for global challenges like climate change. Climate-Action Programme

IDE Publication Highlights (Week 39 2024)

Click here to view recent publication highlights from our staff and students.

National and International Phishing Attackers revealed

Phishing attacks, which trick users into sharing private data, have been a major online security threat for years. According to a 2023 FBI report, it is the top digital crime type. Researchers from the Intelligent Systems department have collaborated with three European country-code top-level domains (ccTLDs) to characterize phishing attacks, focusing on the Netherlands’ .nl, Belgium’s .be, and Ireland’s .ie. By understanding these patterns, the research aims to enhance security measures and protect internet users from phishing threats.

11,000 young researchers have obtained a PhD from TU Delft

It was a very memorable day for PhD Amey Vasulkar last Thursday, the 19th of September. Not only did he successfully defend his promotion on Arctic Sea Ice in Tide Models, but he was also the 11,000th student to obtain a PhD from TU Delft. We are incredibly proud of and thankful for every single one of these 11,000 PhDs who started their scientific journey with us and continuously strive to change the world through their scientific innovations.

How system safety can make Machine Learning systems safer in the public sector

Machine Learning (ML), a form of AI where patterns are discovered in large amounts of data, can be very useful. It is increasingly used, for example, in chatbot Chat GPT, facial recognition, or speech software. However, there are also concerns about the use of ML systems in the public sector. How do you prevent the system from, for example, discriminating or making large-scale mistakes with negative effects on citizens? Scientists at TU Delft, including Jeroen Delfos, investigated how lessons from system safety can contribute to making ML systems safer in the public sector. “Policymakers are busy devising measures to counter the negative effects of ML. Our research shows that they can rely much more on existing concepts and theories that have already proven their value in other sectors,” says Jeroen Delfos. Jeroen Delfos Learning from other sectors In their research, the scientists used concepts from system safety and systems theory to describe the challenges of using ML systems in the public sector. Delfos: “Concepts and tools from the system safety literature are already widely used to support safety in sectors such as aviation, for example by analysing accidents with system safety methods. However, this is not yet common practice in the field of AI and ML. By applying a system-theoretical perspective, we view safety not only as a result of how the technology works, but as the result of a complex set of technical, social, and organisational factors.” The researchers interviewed professionals from the public sector to see which factors are recognized and which are still underexposed. Bias There is room for improvement to make ML systems in the public sector safer. For example, bias in data is still often seen as a technical problem, while the origin of that bias may lie far outside the technical system. Delfos: “Consider, for instance, the registration of crime. In neighbourhoods where the police patrol more frequently, logically, more crime is recorded, which leads to these areas being overrepresented in crime statistics. An ML system trained to discover patterns in these statistics will replicate or even reinforce this bias. However, the problem lies in the method of recording, not in the ML system itself.” Reducing risks According to the researchers, policymakers and civil servants involved in the development of ML systems would do well to incorporate system safety concepts. For example, it is advisable to identify in advance what kinds of accidents one wants to prevent when designing an ML system. Another lesson from system safety, for instance in aviation, is that systems tend to become more risky over time in practice, because safety becomes subordinate to efficiency as long as no accidents occur. “It is therefore important that safety remains a recurring topic in evaluations and that safety requirements are enforced,” says Delfos. Read the research paper .

Kaitai Liang receives Distinguished Reviewer Award by ESORICS 2024

I am pleased to share that Kaitai Liang, a tenured faculty member of the Cybersecurity group, has been honored with the Distinguished Reviewer Award by ESORICS 2024.