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Yenni Villa Acuña

Faculty of Civil Engineering and Geosciences Yenni completed her master’s degree in Applied Earth Sciences. Her thesis work is part of the IDEA-League Master Program and is done as an internship at Aramco Overseas Company BV in Delft. Minimisation and optimisation are at the heart of many challenges oil & gas companies face in structural imaging of the subsurface in oil & gas exploration. Many algorithms and ideas struggle to find robust solutions because of the scale and complexity of the subsurface. During a period of 5 months, Yenni created new ideas to make a general optimisation method significantly faster and more robust. She also demonstrated the applicability of the new method to a number of synthetic data sets that are well-known in the field of numerical optimization, as well as to seismic data processing algorithms that are used by many oil & gas companies. The quality of the results achieved are extraordinary. Yenni’s thesis was rewarded with an impressive 9.5 and her work has already been recognized as state of the art in current seismic processing software. “Yenny worked very independently on her thesis while taking the suggestions of her supervisors seriously. She managed to defended her thesis as good as perfectly. Besides her thesis work, she also did her course work very well, with excellent marks in all 3 high-standard European universities (ETH, TUD and RWTH).” Graduation committee - Dr G.G. Drijkoningen, Dr Yimin Sun, Dr Florian Wellman. Thesis synopsis Since its inception in 1975, Genetics Algorithms (GA) have been successfully used as a tool for global optimization of non-convex problems in several real world applications. Its creation was inspired by the neo-Darwinian theory of evolution, where the goal is to evolve an initial population of candidate solutions using the artificial operators of selection, crossover and mutation. An advanced Genetic Algorithm (aGA) was developed by AOC* to find the global maximum of n-th dimensional non-convex functions. However, as computational time is a key factor when it comes to scalability, the objective of this project is to improve the convergence speed of this currently available aGA by simultaneously enhancing both its global and its local search capabilities. To this end, two solutions were proposed. The first is a modified version of the well-known Island model GAs and the second is a Self-Adaptive Differential Evolution (SADE) fine tuning scheme. After a successful demonstration of its improved performance on multi-modal test functions, my enhanced Genetic Algorithm (eGA) is used to tackle two common non-linear Geophysical problems: static correction and Common Reflection Surface (CRS) stacking, where promising results were obtained. *AOC: Aramco Overseas Company

Rhythima Shinde

Faculty of Technology, Policy and Management Rhythima Shinde completed two master’s programmes: Engineering and Policy Analysis (EPA, with honours), including field work in India, and Computer Science, including a graduate project at ETH Zurich. Her career as an Honours student at Delft furthermore included an active board membership of the Energy Club, the publication of several journal papers and a book chapter, various student assistantships to support cybersecurity and open-data research, and the development of MOOCs. She also co-founded a start-up company ‘Energy Bazaar’, where she now puts her research findings and recommendations to immediate use. Rhythima graduated from MSc EPA on electrifying rural India through institutional innovation. Her thesis was rewarded with a grade 9.5. She executed empirical research in India and developed an institutional innovation framework to analyse her empirical findings, furthering Nobel prize winner Elinor Ostrom’s work. She built various agent-based computational models to verify her framework and then, through this framework and her models, she identified feasible and durable system designs and policy alternatives for electrifying rural India. She more than proved her mastery of all skills that make her a true Delft-trained policy analyst: providing computationally strong, empirically-sound engineering solutions for solving society’s critical issues. “Rhythima’s career in Delft is nothing short of impressive and she may be the ultimate example of a scientifically driven, intelligent, broadly-interested, entrepreneurial, socially responsible engineer, with a demonstrable impact on science and society.” Graduation committee – Prof. Paulien Herder, Dr Amineh Ghorbani, Dr Martijn Warnier Thesis synopsis Around 100 million households live without electricity in India. At the same time, there is a booming solar panel market in India. This gives an opportunity for escalating the reach through peer to peer (p2p) electricity exchange. The thesis explored the potential and challenges of this p2p solution with an extensive field study, development of theoretical framework to understand diffusion of emerging technologies considering community benefits (e.g. role of cooperative shops, etc.) and finally proposing socio-tech policies (e.g. hybrid microgrid-p2p solutions, anonymization of network) for making such projects a success for energy companies and consumers. The results of this thesis were successfully implemented in a computer science thesis to facilitate AI based optimization platform. The cumulative knowledge thus gained has lead to start-up 'Energy Bazaar' to implement the results in India. If implemented at scale, these solutions would accelerate complete household electrification of India by 2025.

Charlotte Koster

Faculty of Applied Sciences Charlotte obtained her master’s degree in Life Sciences & Technology. She chose to focus on the generation and analysis of industrially relevant yeast hybrids. She developed a fast and efficient method to generate new genetic variants of yeasts by ‘crossing’ parental strains with specific desired characteristics. The method that Charlotte designed, tested and optimized is highly relevant for industrial application. She applied this method to produce a new hybrid yeast that can be used in the beer brewing industry. Her thesis formed the basis for a patent application, on which she is one of the inventors. Charlotte received an impressive 9.5 for her thesis. Besides her excellent study achievements, she has also been an active member of the TU Delft student team that won a gold medal in the 2016 International Genetically Engineered Machine competition (iGEM). Another illustrative example of Charlotte’s drive to seek challenges is her internship performed at Ginkgo Bioworks, a high-profile Boston-based company active in the frontline of synthetic biotechnology. The top scientists who supervised Charlotte at Ginkgo awarded her a 9.5 for her internship. “During her graduation project, Charlotte was not only scientifically, but also socially a ‘pacemaker’, with a very positive impact on our research group. As evident from discussions in the lab and her activities on social media, she has an active interest in the societal impacts of science.” Graduation committee – Prof. Jack Pronk, Arthur Gorter de Vries, Dr Jean-Marc Daran, Dr Peter-Leon Hagedoorn Thesis synposis With ongoing climate change, we need to make our industrial processes more sustainable. In biotechnology, micro-organisms like yeast are used as ‘cell factories’ to produce products like biofuels, medicine and bioplastics in a sustainable way. However, this often requires genetic modification of the organisms, which is still a controversial issue. The use of hybrid yeasts can form a non-GMO alternative. Like some animals, different yeasts can mate with each other, forming hybrids that inherit qualities from each parent. For instance, mating a bioplastic-producing yeast with a plant-consuming yeast could result in a hybrid capable of making bioplastics from plant waste, without using genetic modification. However, such mating is rare, so hybrids are difficult to obtain. Therefore, I developed a method to obtain hybrid yeasts, based on color-coding and optical sorting of different yeasts, providing a promising approach to develop new non-genetically modified yeasts for the biotech industry.

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Yenni Villa Acuña

Faculty of Civil Engineering and Geosciences Yenni completed her master’s degree in Applied Earth Sciences. Her thesis work is part of the IDEA-League Master Program and is done as an internship at Aramco Overseas Company BV in Delft. Minimisation and optimisation are at the heart of many challenges oil & gas companies face in structural imaging of the subsurface in oil & gas exploration. Many algorithms and ideas struggle to find robust solutions because of the scale and complexity of the subsurface. During a period of 5 months, Yenni created new ideas to make a general optimisation method significantly faster and more robust. She also demonstrated the applicability of the new method to a number of synthetic data sets that are well-known in the field of numerical optimization, as well as to seismic data processing algorithms that are used by many oil & gas companies. The quality of the results achieved are extraordinary. Yenni’s thesis was rewarded with an impressive 9.5 and her work has already been recognized as state of the art in current seismic processing software. “Yenny worked very independently on her thesis while taking the suggestions of her supervisors seriously. She managed to defended her thesis as good as perfectly. Besides her thesis work, she also did her course work very well, with excellent marks in all 3 high-standard European universities (ETH, TUD and RWTH).” Graduation committee - Dr G.G. Drijkoningen, Dr Yimin Sun, Dr Florian Wellman. Thesis synopsis Since its inception in 1975, Genetics Algorithms (GA) have been successfully used as a tool for global optimization of non-convex problems in several real world applications. Its creation was inspired by the neo-Darwinian theory of evolution, where the goal is to evolve an initial population of candidate solutions using the artificial operators of selection, crossover and mutation. An advanced Genetic Algorithm (aGA) was developed by AOC* to find the global maximum of n-th dimensional non-convex functions. However, as computational time is a key factor when it comes to scalability, the objective of this project is to improve the convergence speed of this currently available aGA by simultaneously enhancing both its global and its local search capabilities. To this end, two solutions were proposed. The first is a modified version of the well-known Island model GAs and the second is a Self-Adaptive Differential Evolution (SADE) fine tuning scheme. After a successful demonstration of its improved performance on multi-modal test functions, my enhanced Genetic Algorithm (eGA) is used to tackle two common non-linear Geophysical problems: static correction and Common Reflection Surface (CRS) stacking, where promising results were obtained. *AOC: Aramco Overseas Company

Rhythima Shinde

Faculty of Technology, Policy and Management Rhythima Shinde completed two master’s programmes: Engineering and Policy Analysis (EPA, with honours), including field work in India, and Computer Science, including a graduate project at ETH Zurich. Her career as an Honours student at Delft furthermore included an active board membership of the Energy Club, the publication of several journal papers and a book chapter, various student assistantships to support cybersecurity and open-data research, and the development of MOOCs. She also co-founded a start-up company ‘Energy Bazaar’, where she now puts her research findings and recommendations to immediate use. Rhythima graduated from MSc EPA on electrifying rural India through institutional innovation. Her thesis was rewarded with a grade 9.5. She executed empirical research in India and developed an institutional innovation framework to analyse her empirical findings, furthering Nobel prize winner Elinor Ostrom’s work. She built various agent-based computational models to verify her framework and then, through this framework and her models, she identified feasible and durable system designs and policy alternatives for electrifying rural India. She more than proved her mastery of all skills that make her a true Delft-trained policy analyst: providing computationally strong, empirically-sound engineering solutions for solving society’s critical issues. “Rhythima’s career in Delft is nothing short of impressive and she may be the ultimate example of a scientifically driven, intelligent, broadly-interested, entrepreneurial, socially responsible engineer, with a demonstrable impact on science and society.” Graduation committee – Prof. Paulien Herder, Dr Amineh Ghorbani, Dr Martijn Warnier Thesis synopsis Around 100 million households live without electricity in India. At the same time, there is a booming solar panel market in India. This gives an opportunity for escalating the reach through peer to peer (p2p) electricity exchange. The thesis explored the potential and challenges of this p2p solution with an extensive field study, development of theoretical framework to understand diffusion of emerging technologies considering community benefits (e.g. role of cooperative shops, etc.) and finally proposing socio-tech policies (e.g. hybrid microgrid-p2p solutions, anonymization of network) for making such projects a success for energy companies and consumers. The results of this thesis were successfully implemented in a computer science thesis to facilitate AI based optimization platform. The cumulative knowledge thus gained has lead to start-up 'Energy Bazaar' to implement the results in India. If implemented at scale, these solutions would accelerate complete household electrification of India by 2025.

Charlotte Koster

Faculty of Applied Sciences Charlotte obtained her master’s degree in Life Sciences & Technology. She chose to focus on the generation and analysis of industrially relevant yeast hybrids. She developed a fast and efficient method to generate new genetic variants of yeasts by ‘crossing’ parental strains with specific desired characteristics. The method that Charlotte designed, tested and optimized is highly relevant for industrial application. She applied this method to produce a new hybrid yeast that can be used in the beer brewing industry. Her thesis formed the basis for a patent application, on which she is one of the inventors. Charlotte received an impressive 9.5 for her thesis. Besides her excellent study achievements, she has also been an active member of the TU Delft student team that won a gold medal in the 2016 International Genetically Engineered Machine competition (iGEM). Another illustrative example of Charlotte’s drive to seek challenges is her internship performed at Ginkgo Bioworks, a high-profile Boston-based company active in the frontline of synthetic biotechnology. The top scientists who supervised Charlotte at Ginkgo awarded her a 9.5 for her internship. “During her graduation project, Charlotte was not only scientifically, but also socially a ‘pacemaker’, with a very positive impact on our research group. As evident from discussions in the lab and her activities on social media, she has an active interest in the societal impacts of science.” Graduation committee – Prof. Jack Pronk, Arthur Gorter de Vries, Dr Jean-Marc Daran, Dr Peter-Leon Hagedoorn Thesis synposis With ongoing climate change, we need to make our industrial processes more sustainable. In biotechnology, micro-organisms like yeast are used as ‘cell factories’ to produce products like biofuels, medicine and bioplastics in a sustainable way. However, this often requires genetic modification of the organisms, which is still a controversial issue. The use of hybrid yeasts can form a non-GMO alternative. Like some animals, different yeasts can mate with each other, forming hybrids that inherit qualities from each parent. For instance, mating a bioplastic-producing yeast with a plant-consuming yeast could result in a hybrid capable of making bioplastics from plant waste, without using genetic modification. However, such mating is rare, so hybrids are difficult to obtain. Therefore, I developed a method to obtain hybrid yeasts, based on color-coding and optical sorting of different yeasts, providing a promising approach to develop new non-genetically modified yeasts for the biotech industry.
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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

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