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Bert van Wee is Professor of Excellence 2020

On Monday 31 August, Bert van Wee, Professor of Transport Policy at the Faculty of Technology, Policy and Management (TPM) is named Professor of Excellence 2020 by Delft University Fund. Van Wee receives this prestigious prize for the indelible mark he has left on the Delft, national and international transport communities. He displays a continuous drive to improve education, including his own. He is committed and critical, yet always positive and constructive in his supervision of graduate (198!) and PhD students (28). Professor van Wee has been nominated by prof. drs. Aukje Hassoldt, Dean of Faculty TPM, Study Association Curius, (current and former) PhD students and a large number of internal and external colleagues from the transport community, including organisations such as Oxford University, Ministry of Infrastructure and Water Management, Institute for Road Safety Research (SWOV) and TRAIL - Research School for Transport , Infrastructure and Logistics. Not only are his qualities as a researcher recognized, he is also highly praised for his positive attitude, unbridled enthusiasm, accessibility and unyielding dedication. Bert is one of the most cited TU Delft scientists in national and international media. Prof.dr.ir. Fred van Keulen, Chair selection committee Professor of Excellence “The selection committee was very impressed with the nomination. Bert van Wee has an extensive and comprehensive track record. Of special interest to the committee was how his role as coach and mentor has impacted so many others in the transport domain. The committee further recognized how Bert van Wee continues to have a positive impact on society at the national and international level.” Prof. drs. Aukje Hassoldt, Dean Faculty TPM “With a unique mix of research, educational and administrative qualities, Bert makes a unique scientific and social contribution to his field that is difficult to overestimate. With a broad palette of methodologies at his disposal, he has time and again developed new, integrated viewpoints that in turn inspire others. The faculty is privileged to have someone like Bert, with his high scientific caliber and engaging personality, as a key member of our community.” Thomas van Gerven, President Study Association Curius “Bert is a real educator. Within the transport domain of our faculty, he is truly a walking encyclopedia, constantly coming up with beautiful examples that appeal to the imagination. It is thanks to lecturers like Bert that more students are attracted to our faculty each year, allowing more students to experience the inspiring combination of technology and policy.” Best of TU Delft Delft University Fund has awarded the prestigious Professor of Excellence Award (in Dutch: Leermeesterprijs) since 1994. A Professor of Excellence is someone who excels in both research and education, and who knows how to inspire and motivate the next generation of Delft engineers. Recipients of the award are reckoned among the top of TU Delft. Professors of Excellence are not elected on the basis of yield figures or impact scores, nor are they selected top-down. You can only receive this honorary title on the recommendation of your colleagues and your students, who consider you to be their ‘Leermeester’. The prize The Professor of Excellence receives the silver Leermeester medal and a check for € 15,000. Also, KLM bestows two business class tickets for a destination of choice. The award ceremony Due to corona measures, the award ceremony will take place later. Bert van Wee Motorway speed limits of 100 km/h largely advantageous

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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

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 .