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Young Scientists on stage

Martijn Nagtegaal, PhD student @ImPhys participated in the "Hoezo? Show!". The Hoe?Zo! Show is an interactive science game show in which young scientists answer questions from curious children live on stage in a race against time. Will the scientists be able to answer children's questions quickly enough? Or do the children's questions prove too difficult for these clever minds?

Cyber Security Webinar by Roland Kromes MSc - Modeling a low-power IoT architecture for Blockchain and Smart Contract applications

Cyber Security Webinar by Roland Kromes MSc - Modeling a low-power IoT architecture for Blockchain and Smart Contract applications 23 November 2021 12:00 till 12:45 - Location: Zoom meeting Join Zoom Meeting https://tudelft.zoom.us/j/93459336716?pwd=VFk4N3dCQTF2TUlHYnBLejk0dFVPUT09 Meeting ID: 934 5933 6716 Passcode: 389654 Abstract Nowadays, most IoT applications are based on a centralized system in which all of the system participants have to rely on a central entity. In such a system, data immutability, data traceability, and transparency cannot be provided. Blockchain technology is an entirely decentralized system in which the third trusted party (central entity) is removed. Contrarily to centralized systems, blockchain technology provides data immutability, traceability, and transparency. Most modern blockchains also allow the deployment of smart contracts, which are digital programs that can be read by all participants and executed automatically according to an event on the blockchain. These advantageous features of blockchain technology show a clear interest in the integration of IoT with blockchain technology. The contribution's main objectives are the study of the integration possibilities of IoT with blockchain technology and the development of a model of dedicated low-power-consumption IoT hardware architecture that enables communication with multiple types of blockchain. The proposed blockchain APIs (Ethereum, Hyperledger Sawtooth) are written in C++. These APIs can create valid transactions. The IoT architecture model's CPU is emulated with QEMU and the dedicated cryptographic hardware accelerators are modeled in SystemC-TLM high-level hardware description language. As QEMU and SystemC-TLM work on different time environments, they must be synchronized by a co-simulation platform. The CPU of the proposed IoT architecture executes a Linux Operating System, which runs blockchain APIs. These APIs cannot have direct access to the hardware accelerators. In order to handle access to the hardware accelerators and the orchestration of dedicated power management, Linux Kernel device drivers were developed. The results represent that a significant reduction of the overall energy consumption can be achieved when the elliptic curve point multiplication and hash operations are hardware accelerated. Bio I am Roland Kromes, a PhD candidate at the Université Côte d'Azur in the Electronics, Antennas and Telecommunications Laboratory (LEAT-CNRS). In January, I will join the Cybersecurity group at Delft University of Technology as a postdoctoral researcher. I obtained my diploma in Electronics, Systems and Telecommunications with the specialty of embedded systems at the Université Côte d'Azur. My thesis focuses on the possibilities of IoT integration with Blockchain technology and the modeling of a specific low power IoT architecture for Blockchain and Smart Contract applications. This thesis is part of the Smart IoT for Mobility multidisciplinary project (ANR-National Agency for Research) in which I could also work on acceptability issues of Blockchain technology with fellow management researchers. My research interests: Blockchain, IoT, applied cryptography, secure data sharing.

Cyber Security Webinar by Dr. Yunpeng Li - Uncertainty quantification and propagation in high-dimensional spaces

Cyber Security Webinar by Dr. Yunpeng Li - Uncertainty quantification and propagation in high-dimensional spaces 28 September 2021 12:00 till 12:45 - Location: Zoom meeting Join Zoom Meeting https://tudelft.zoom.us/j/99314357068 Meeting ID: 993 1435 7068 Passcode: 678062 Abstract: Deep learning models, which are cornerstones in the success of modern machine learning applications, often lack representation of uncertainty or produce overconfident predictions that can lead to costly consequences. The optimal transport theory has found it application in quantifying uncertainty in large-scale machine learning problems by measuring the Wasserstein distance between data distributions. Separately, for real-world sequential inference applications, differentiable filters provided a mathematically principled framework to propagate model uncertainty. This talk will hence be divided into two parts. In the first part, I will discuss a new family of slice-based Wasserstein distance metrics, called augmented sliced Wasserstein distances (ASWDs), with a novel incorporation of injective neural networks. ASWDs learns nonlinear projections that can capture the complex structure of the data distributions which improve their projection efficiency. In the second part, I will discuss our recent efforts in constructing more expressive dynamic model and proposal distributions in the differentiable particle filtering framework through normalizing flow. In addition, I will introduce an end-to-end learning objective based upon the maximisation of a pseudo-likelihood function which can improve the estimation of states when large portion of groundtruth information are unknown. Bio: Dr Yunpeng Li is Senior Lecturer in Artificial Intelligence in the Department of Computer Science at the University of Surrey in the UK. Before joining Surrey as a Lecturer in AI in 2018, he was a postdoctoral researcher in the Machine Learning Research Group in the Department of Engineering Science at the University of Oxford and was a Junior Research Fellow at Wolfson College at Oxford. He received a PhD in Electrical Engineering at the McGill University in Canada in 2017. His research interests are in the areas of statistical machine learning and signal processing, particularly Bayesian inference techniques and the optimal transport theory. He has broad interests in applications of machine learning, e.g. breast cancer detection, dental disease detection, and environment acoustic sensing. His work has won the best paper award in the NeurlPS Workshop on Machine Learning for Developing World in 2018 and 2019.

Cyber Security Webinar by Martin Fejrskov MSc - Using NetFlow to measure the impact of deploying DNS-based blacklists

Cyber Security Webinar by Martin Fejrskov MSc - Using NetFlow to measure the impact of deploying DNS-based blacklists 12 October 2021 12:00 till 12:45 - Location: Zoom meeting Join Zoom Meeting https://tudelft.zoom.us/j/95465881342 Meeting ID: 954 6588 1342 Passcode: 808322 Abstract To prevent user exposure to a wide range of cyber security threats, organizations and companies often resort to deploying blacklists in DNS resolvers or DNS firewalls. The impact of such a deployment is often measured by comparing the coverage of individual blacklists, by counting the number of blocked DNS requests, or by counting the number of flows redirected to a benign web page that contains a warning to the user. This paper suggests an alternative to this by using NetFlow data to measure the effect of a DNS-based blacklist deployment. Our findings suggest that only 38-40\% of blacklisted flows are web traffic. Furthermore, the paper analyzes the flows blacklisted by IP address, and it is shown that the majority of these are potentially benign, such as flows towards a web server hosting both benign and malicious sites. Finally, the flows blacklisted by domain name are categorized as either spam or malware, and it is shown that less than 6\% are considered malicious. Short bio: Martin Fejrskov is an Industrial Ph.D. student at Telenor Denmark and Aalborg University focusing on detecting cybersecurity threats with data from Internet Service Providers. Prior to the Ph.D. studies, he was a Solution Architect at Telenor Denmark, focusing on security services and the national backbone network. Before that he was a Product Manager at the Danish company formerly known as ETI A/S, heading the development and architecture of one of the core products. He received his Master of Science from Aalborg University in 2005 with excellent grades, studying primarily within the fields of network protocols, traffic analysis and security.

Cyber Security Webinar by Dr. Shihui Fu of the University of Waterloo - Transparent Succinct Zero-Knowledge Arguments for R1CS with Efficient Verifier

Cyber Security Webinar by Dr. Shihui Fu of the University of Waterloo - Transparent Succinct Zero-Knowledge Arguments for R1CS with Efficient Verifier 09 November 2021 12:00 till 12:45 - Location: Zoom meeting Join Zoom Meeting https://tudelft.zoom.us/j/95108026354?pwd=RVhXS3EwQjIyZnVzNk1ScWNzQmtTdz09 Meeting ID: 951 0802 6354 Passcode: 378365 Abstract We propose Polaris, a zkSNARK with quasi-linear prover time and both polylogarithmic proof size and verification time in the size of the arithmetic circuit representing the statement. By instantiating with different commitment schemes, we obtain several zkSNARKs where the verifier's costs and the proof size range from $O(\log^2{N})$ to $O(\sqrt{N})$ depending on the underlying polynomial commitment schemes. All these schemes do not require a trusted setup. It is plausibly post-quantum secure when instantiated with a secure collision-resistant hash function. Our experimental evaluation demonstrates that Polaris offers a much lower verification time than Ligero and Aurora for instances with large sizes as we reduce the complexity from linear to polylogarithmic. Short bio Shihui Fu received his Ph.D. degree in Mathematics from Academy of Mathematics and Systems Science, CAS in 2018. Currently, he is a post-doc in University of Waterloo. His main research interests include cryptographic protocols and zero-knowledge proof.

Cyber Security Webinar by Rui Wang MSc - Privacy-preserving Byzantine-Robust Federated Learning

Cyber Security Webinar by Rui Wang MSc - Privacy-preserving Byzantine-Robust Federated Learning 07 December 2021 12:00 till 12:45 - Location: Zoom meeting Join Zoom Meeting https://tudelft.zoom.us/j/93851661903?pwd=UzhXVlAxellBUDhRRXdyNWYyOGdlUT09 Meeting ID: 938 5166 1903 Passcode: 931813 Abstract Privacy and Byzantine-robustness are two major concerns of federated learning (FL), but mitigating both threats simultaneously is highly challenging: privacy-preserving strategies prohibit access to individual model updates to avoid leakage, while Byzantine-robust methods require access for comprehensive mathematical analysis. Besides, most Byzantine-robust methods only work in the honest-majority setting. In this webinar, I will introduce previous works about this topic and presents some expected experimental results about Privacy-preserving FL to resist > 1/2 Byzantine attacks.

Cyber Security Webinar by Daniël Vos Msc - Training Robust Decision Trees Against Adversarial Examples

Cyber Security Webinar by Daniël Vos Msc - Training Robust Decision Trees Against Adversarial Examples 14 September 2021 12:00 till 12:45 - Location: Zoom meeting Join Zoom Meeting https://tudelft.zoom.us/j/94484315617 Meeting ID: 944 8431 5617 Passcode: 049126 Abstract Decision trees and tree ensembles are among the most popular machine learning models for tabular data but they suffer from adversarial examples. When we make specific changes to a model's input, the resulting prediction can be completely wrong. Since this finding, researchers have proposed different methods to train trees that are robust so such attacks. However, these methods can take hours to run and offer no performance guarantees. In this seminar we will look at how to speed up training by orders of magnitude and explain how we can prove the optimality of robust decision trees.

Research lines

To serve society, the focus of the group is on two main research lines: assessment of existing concrete structures The group is famous for the research on failure mechanisms, especially shear failure, development of non-destructive techniques such as acoustic emission for damage detection (monitoring), and on assessing and developing guidelines for proof loading of existing structures. upscaling of innovative types of concrete Group activities are focused on developing safe procedures for the structural application of new types of concretes in order to serve societal demands. For example, using Ultra High Performance Fibre Reinforced Concrete (UHPFRC) for developing a fast and safe procedure for the replacement of existing bridges, using UHPFRC and bendable concrete (SHCC) for strengthening and repair or “green” (geopolymer) concrete as more sustainable building material. Current interest of the group is to investigate and develop a guideline for a safe structural application of these materials in reinforced and pre-stressed elements and structures.

Research

The mission of the group is to perform the research directly serving societal challenges. Two main challenges in the area of concrete structures are (firstly), how to maintain and deal with the existing structures, and (secondly), how to keep up with the recent developments and apply innovative concretes in structures in a safe and sustainable way. Therefore, the research activities of the group are mainly focused on two research lines: assessment of existing concrete structures, and upscaling of new concrete materials. Most research projects are performed in the Stevinlab by graduate students or PhD-students in combination with a technician and a scientific staff member. Research lines PhD candidates and Postdocs Laboratory

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Young Scientists on stage

Martijn Nagtegaal, PhD student @ImPhys participated in the "Hoezo? Show!". The Hoe?Zo! Show is an interactive science game show in which young scientists answer questions from curious children live on stage in a race against time. Will the scientists be able to answer children's questions quickly enough? Or do the children's questions prove too difficult for these clever minds?

Cyber Security Webinar by Roland Kromes MSc - Modeling a low-power IoT architecture for Blockchain and Smart Contract applications

Cyber Security Webinar by Roland Kromes MSc - Modeling a low-power IoT architecture for Blockchain and Smart Contract applications 23 November 2021 12:00 till 12:45 - Location: Zoom meeting Join Zoom Meeting https://tudelft.zoom.us/j/93459336716?pwd=VFk4N3dCQTF2TUlHYnBLejk0dFVPUT09 Meeting ID: 934 5933 6716 Passcode: 389654 Abstract Nowadays, most IoT applications are based on a centralized system in which all of the system participants have to rely on a central entity. In such a system, data immutability, data traceability, and transparency cannot be provided. Blockchain technology is an entirely decentralized system in which the third trusted party (central entity) is removed. Contrarily to centralized systems, blockchain technology provides data immutability, traceability, and transparency. Most modern blockchains also allow the deployment of smart contracts, which are digital programs that can be read by all participants and executed automatically according to an event on the blockchain. These advantageous features of blockchain technology show a clear interest in the integration of IoT with blockchain technology. The contribution's main objectives are the study of the integration possibilities of IoT with blockchain technology and the development of a model of dedicated low-power-consumption IoT hardware architecture that enables communication with multiple types of blockchain. The proposed blockchain APIs (Ethereum, Hyperledger Sawtooth) are written in C++. These APIs can create valid transactions. The IoT architecture model's CPU is emulated with QEMU and the dedicated cryptographic hardware accelerators are modeled in SystemC-TLM high-level hardware description language. As QEMU and SystemC-TLM work on different time environments, they must be synchronized by a co-simulation platform. The CPU of the proposed IoT architecture executes a Linux Operating System, which runs blockchain APIs. These APIs cannot have direct access to the hardware accelerators. In order to handle access to the hardware accelerators and the orchestration of dedicated power management, Linux Kernel device drivers were developed. The results represent that a significant reduction of the overall energy consumption can be achieved when the elliptic curve point multiplication and hash operations are hardware accelerated. Bio I am Roland Kromes, a PhD candidate at the Université Côte d'Azur in the Electronics, Antennas and Telecommunications Laboratory (LEAT-CNRS). In January, I will join the Cybersecurity group at Delft University of Technology as a postdoctoral researcher. I obtained my diploma in Electronics, Systems and Telecommunications with the specialty of embedded systems at the Université Côte d'Azur. My thesis focuses on the possibilities of IoT integration with Blockchain technology and the modeling of a specific low power IoT architecture for Blockchain and Smart Contract applications. This thesis is part of the Smart IoT for Mobility multidisciplinary project (ANR-National Agency for Research) in which I could also work on acceptability issues of Blockchain technology with fellow management researchers. My research interests: Blockchain, IoT, applied cryptography, secure data sharing.

Cyber Security Webinar by Dr. Yunpeng Li - Uncertainty quantification and propagation in high-dimensional spaces

Cyber Security Webinar by Dr. Yunpeng Li - Uncertainty quantification and propagation in high-dimensional spaces 28 September 2021 12:00 till 12:45 - Location: Zoom meeting Join Zoom Meeting https://tudelft.zoom.us/j/99314357068 Meeting ID: 993 1435 7068 Passcode: 678062 Abstract: Deep learning models, which are cornerstones in the success of modern machine learning applications, often lack representation of uncertainty or produce overconfident predictions that can lead to costly consequences. The optimal transport theory has found it application in quantifying uncertainty in large-scale machine learning problems by measuring the Wasserstein distance between data distributions. Separately, for real-world sequential inference applications, differentiable filters provided a mathematically principled framework to propagate model uncertainty. This talk will hence be divided into two parts. In the first part, I will discuss a new family of slice-based Wasserstein distance metrics, called augmented sliced Wasserstein distances (ASWDs), with a novel incorporation of injective neural networks. ASWDs learns nonlinear projections that can capture the complex structure of the data distributions which improve their projection efficiency. In the second part, I will discuss our recent efforts in constructing more expressive dynamic model and proposal distributions in the differentiable particle filtering framework through normalizing flow. In addition, I will introduce an end-to-end learning objective based upon the maximisation of a pseudo-likelihood function which can improve the estimation of states when large portion of groundtruth information are unknown. Bio: Dr Yunpeng Li is Senior Lecturer in Artificial Intelligence in the Department of Computer Science at the University of Surrey in the UK. Before joining Surrey as a Lecturer in AI in 2018, he was a postdoctoral researcher in the Machine Learning Research Group in the Department of Engineering Science at the University of Oxford and was a Junior Research Fellow at Wolfson College at Oxford. He received a PhD in Electrical Engineering at the McGill University in Canada in 2017. His research interests are in the areas of statistical machine learning and signal processing, particularly Bayesian inference techniques and the optimal transport theory. He has broad interests in applications of machine learning, e.g. breast cancer detection, dental disease detection, and environment acoustic sensing. His work has won the best paper award in the NeurlPS Workshop on Machine Learning for Developing World in 2018 and 2019.

Cyber Security Webinar by Martin Fejrskov MSc - Using NetFlow to measure the impact of deploying DNS-based blacklists

Cyber Security Webinar by Martin Fejrskov MSc - Using NetFlow to measure the impact of deploying DNS-based blacklists 12 October 2021 12:00 till 12:45 - Location: Zoom meeting Join Zoom Meeting https://tudelft.zoom.us/j/95465881342 Meeting ID: 954 6588 1342 Passcode: 808322 Abstract To prevent user exposure to a wide range of cyber security threats, organizations and companies often resort to deploying blacklists in DNS resolvers or DNS firewalls. The impact of such a deployment is often measured by comparing the coverage of individual blacklists, by counting the number of blocked DNS requests, or by counting the number of flows redirected to a benign web page that contains a warning to the user. This paper suggests an alternative to this by using NetFlow data to measure the effect of a DNS-based blacklist deployment. Our findings suggest that only 38-40\% of blacklisted flows are web traffic. Furthermore, the paper analyzes the flows blacklisted by IP address, and it is shown that the majority of these are potentially benign, such as flows towards a web server hosting both benign and malicious sites. Finally, the flows blacklisted by domain name are categorized as either spam or malware, and it is shown that less than 6\% are considered malicious. Short bio: Martin Fejrskov is an Industrial Ph.D. student at Telenor Denmark and Aalborg University focusing on detecting cybersecurity threats with data from Internet Service Providers. Prior to the Ph.D. studies, he was a Solution Architect at Telenor Denmark, focusing on security services and the national backbone network. Before that he was a Product Manager at the Danish company formerly known as ETI A/S, heading the development and architecture of one of the core products. He received his Master of Science from Aalborg University in 2005 with excellent grades, studying primarily within the fields of network protocols, traffic analysis and security.

Cyber Security Webinar by Dr. Shihui Fu of the University of Waterloo - Transparent Succinct Zero-Knowledge Arguments for R1CS with Efficient Verifier

Cyber Security Webinar by Dr. Shihui Fu of the University of Waterloo - Transparent Succinct Zero-Knowledge Arguments for R1CS with Efficient Verifier 09 November 2021 12:00 till 12:45 - Location: Zoom meeting Join Zoom Meeting https://tudelft.zoom.us/j/95108026354?pwd=RVhXS3EwQjIyZnVzNk1ScWNzQmtTdz09 Meeting ID: 951 0802 6354 Passcode: 378365 Abstract We propose Polaris, a zkSNARK with quasi-linear prover time and both polylogarithmic proof size and verification time in the size of the arithmetic circuit representing the statement. By instantiating with different commitment schemes, we obtain several zkSNARKs where the verifier's costs and the proof size range from $O(\log^2{N})$ to $O(\sqrt{N})$ depending on the underlying polynomial commitment schemes. All these schemes do not require a trusted setup. It is plausibly post-quantum secure when instantiated with a secure collision-resistant hash function. Our experimental evaluation demonstrates that Polaris offers a much lower verification time than Ligero and Aurora for instances with large sizes as we reduce the complexity from linear to polylogarithmic. Short bio Shihui Fu received his Ph.D. degree in Mathematics from Academy of Mathematics and Systems Science, CAS in 2018. Currently, he is a post-doc in University of Waterloo. His main research interests include cryptographic protocols and zero-knowledge proof.

Cyber Security Webinar by Rui Wang MSc - Privacy-preserving Byzantine-Robust Federated Learning

Cyber Security Webinar by Rui Wang MSc - Privacy-preserving Byzantine-Robust Federated Learning 07 December 2021 12:00 till 12:45 - Location: Zoom meeting Join Zoom Meeting https://tudelft.zoom.us/j/93851661903?pwd=UzhXVlAxellBUDhRRXdyNWYyOGdlUT09 Meeting ID: 938 5166 1903 Passcode: 931813 Abstract Privacy and Byzantine-robustness are two major concerns of federated learning (FL), but mitigating both threats simultaneously is highly challenging: privacy-preserving strategies prohibit access to individual model updates to avoid leakage, while Byzantine-robust methods require access for comprehensive mathematical analysis. Besides, most Byzantine-robust methods only work in the honest-majority setting. In this webinar, I will introduce previous works about this topic and presents some expected experimental results about Privacy-preserving FL to resist > 1/2 Byzantine attacks.

Cyber Security Webinar by Daniël Vos Msc - Training Robust Decision Trees Against Adversarial Examples

Cyber Security Webinar by Daniël Vos Msc - Training Robust Decision Trees Against Adversarial Examples 14 September 2021 12:00 till 12:45 - Location: Zoom meeting Join Zoom Meeting https://tudelft.zoom.us/j/94484315617 Meeting ID: 944 8431 5617 Passcode: 049126 Abstract Decision trees and tree ensembles are among the most popular machine learning models for tabular data but they suffer from adversarial examples. When we make specific changes to a model's input, the resulting prediction can be completely wrong. Since this finding, researchers have proposed different methods to train trees that are robust so such attacks. However, these methods can take hours to run and offer no performance guarantees. In this seminar we will look at how to speed up training by orders of magnitude and explain how we can prove the optimality of robust decision trees.

Research lines

To serve society, the focus of the group is on two main research lines: assessment of existing concrete structures The group is famous for the research on failure mechanisms, especially shear failure, development of non-destructive techniques such as acoustic emission for damage detection (monitoring), and on assessing and developing guidelines for proof loading of existing structures. upscaling of innovative types of concrete Group activities are focused on developing safe procedures for the structural application of new types of concretes in order to serve societal demands. For example, using Ultra High Performance Fibre Reinforced Concrete (UHPFRC) for developing a fast and safe procedure for the replacement of existing bridges, using UHPFRC and bendable concrete (SHCC) for strengthening and repair or “green” (geopolymer) concrete as more sustainable building material. Current interest of the group is to investigate and develop a guideline for a safe structural application of these materials in reinforced and pre-stressed elements and structures.

Research

The mission of the group is to perform the research directly serving societal challenges. Two main challenges in the area of concrete structures are (firstly), how to maintain and deal with the existing structures, and (secondly), how to keep up with the recent developments and apply innovative concretes in structures in a safe and sustainable way. Therefore, the research activities of the group are mainly focused on two research lines: assessment of existing concrete structures, and upscaling of new concrete materials. Most research projects are performed in the Stevinlab by graduate students or PhD-students in combination with a technician and a scientific staff member. Research lines PhD candidates and Postdocs Laboratory
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Moving the Closet

You simply cannot miss it, it is big and magenta: the Pink Closet . On 12 November 2024 the Pink Closet will head to the Main Hall of the TU Delft Library for the first time! The Pink Closet will take its place at the Nook, where it will feature as part of the Studium Generale programme on loneliness. More information on events that coincide with and incorporate the Pink Closet at TU Delft Library will soon be available on the website of Studium Generale .

Green ammonia remains a challenge, but researchers make significant progress

The production of ammonia, essential for fertiliser production, is responsible for almost 1.5% of global carbon emissions. This needs to be greener, which is why researchers have been looking for sustainable alternatives for years.

"Measuring brain activity through the skull with ultrasound opens new doors"

PhD Candidate Rick Waasdorp is looking for ways to correct the distortion caused by the skull when using Ultrasound technology. ‘’My goal is to develop an adaptive method for skull corrections that automatically measures the skull of new patients.’’

NWO funding for flexible power demand in electrically driven industry

NWO is funding two projects to explore ways to make the power demand of industry more flexible, allowing it to better align with future energy supplies. One of these projects, “DEFLAME,” is led by Machteld van den Broek from TU Delft.

Students Amos Yusuf, Mick Dam & Bas Brouwer winners of Mekel Prize 2024

Master students Amos Yusuf, from the ME faculty (Mick Dam, from the EEMCS faculty and graduate Bas Brouwer have won the Mekel Prize 2024 for the best extra scientific activity at TU Delft: the development of an initiative that brings master students into the classroom teaching sciences to the younger generations. The prize was ceremonially awarded by prof Tim van den Hagen on 13 November after the Van Hasselt Lecture at the Prinsenhof, Delft. They received a statue of Professor Jan Mekel and 1.500,- to spend on their project. Insights into climate change are being openly doubted. Funding for important educational efforts and research are being withdrawn. Short clips – so called “reels” – on Youtube and TikTok threaten to simplify complex political and social problems. AI fakes befuddle what is true and what is not. The voices of science that contribute to those discussion with modesty, careful argument and scepticism, are drowned in noise. This poses a threat for universities like TU Delft, who strive to increase student numbers, who benefit from diverse student populations and aim to pass on their knowledge and scientific virtues to the next generation. It is, therefore, alarming that student enrolments to Bachelor and Master Programs at TU Delft have declined in the past year. Students in front of the class The project is aimed to make the sciences more appealing to the next generation. They have identified the problem that students tend miss out on the opportunity of entering a higher education trajectory in the Beta sciences – because they have a wrong picture of such education. In their mind, they depict it as boring and dry. In his pilot lecture at the Stanislas VMBO in Delft, Amos Yusuf has successfully challenged this image. He shared his enthusiasm for the field of robotics and presented himself as a positive role model to the pupils. And in return the excitement of the high school students is palpable in the videos and pictures from the day. The spark of science fills their eyes. Bas Brouwer Mick Dam are the founders of NUVO – the platform that facilitates the engagement of Master Students in high school education in Delft Their efforts offer TU Delft Master Students a valuable learning moment: By sharing insights from their fields with pupils at high school in an educational setting, our students can find identify their own misunderstandings of their subject, learn to speak in front of non-scientific audiences and peak into education as a work field they themselves might not have considered. An extraordinary commitment According to the Mekel jury, the project scored well on all the criteria (risk mitigation, inclusiveness, transparency and societal relevance). However, it was the extraordinary commitment of Amos who was fully immersed during his Master Project and the efforts of Brouwer and Dam that brought together teaching and research which is integral to academic culture that made the project stand out. About the Mekel Prize The Mekel Prize will be awarded to the most socially responsible research project or extra-scientific activity (e.g. founding of an NGO or organization, an initiative or realization of an event or other impactful project) by an employee or group of employees of TU Delft – projects that showcase in an outstanding fashion that they have been committed from the beginning to relevant moral and societal values and have been aware of and tried to mitigate as much as possible in innovative ways the risks involved in their research. The award recognizes such efforts and wants to encourage the responsible development of science and technology at TU Delft in the future. For furthermore information About the project: https://www.de-nuvo.nl/video-robotica-pilot/ About the Mekel Prize: https://www.tudelft.nl/en/tpm/our-faculty/departments/values-technology-and-innovation/sections/ethics-philosophy-of-technology/mekel-prize

The ENHANCE Diversity Seed Fund

Are you a student at TU Delft or another ENHANCE university with a passion for promoting diversity and inclusion? The ENHANCE Diversity Seed Fund is your chance to turn that passion into action. ENHANCE provides funding to support innovative, student-led projects that address key challenges related to inclusion and diversity within our academic communities. Key Details: Funding Available: Up to 1500 Euros per project in the 1st round! Eligibility: Students from ENHANCE member universities. Staff can also join student-led initiatives. Application Deadline: 8 January 2025. More information: Join the online Information Event on the 26 November 2024 16:00-17:00 CET on Zoom . More information: enhanceuniversity.eu/diversity/diversityseedfund/

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