The news is out: Our Jury has selected the winners of the 2023 edition of the EuroTech Future Award. The Jury members were truly impressed by the overall high quality of submissions. In total, we received 34 submissions, coming from early-career researchers from all six EuroTech Universities.
The three most convincing submissions all scored excellent results in the three categories “communication”, “impact”, and “excellence”.
Big congratulations go to:
- 1st Prize: Charlotte Vogt, Technion
for her submission “Carbon dioxide hydrogenation catalysis”
- 2nd Prize: Zongyao Zhou, EPFL
for his submission “Membrane-based technologies for wastewater resource recovery and green energy exploitation”
- 3rd Prize: Dinesh Krishnamoorthy, TU/e
for his submission “Transforming Diabetes Care: Personalized Insulin Dosing with AI Algorithms”
Find out more about the winners of this premiere edition of the EuroTech Future Award below. To know more about the award, click here.
Title of submission
Carbon dioxide hydrogenation catalysis
A catalyst is something that can make chemical things happen that otherwise wouldn't - it's like a chemical magic wand. Catalysts accelerate the rate of a chemical reaction, so the reaction happens much faster and uses less energy. Catalysts are directly involved in about a third of the total global economy: from oil refineries to the food industry. I believe catalysts will also be key to solving global warming. Ultimately, the main problem of global warming is the increasing CO2 content in the atmosphere. So, one possibility is that we don't let the CO2 that is produced in large industrial plants into the atmosphere but rather convert it into something useful with the help of catalysts, for example into materials or fuels. But the catalysts that we have right now are often not good enough, for example they cannot convert all of the CO2. As a result, these processes are not yet economical.
My research is mainly about developing new, better catalysts using so-called spectroscopic experiments in order to be able to study what happens during the CO2 reaction, and use that information to make processes more efficient with the help of catalysts so that fewer CO2 emissions are produced.
About Charlotte Vogt
Charlotte Vogt (1991) obtained her doctoral degree in the group of Prof. Bert Weckhuysen at Utrecht University. Her doctoral dissertation (2020) focused on fundamental concepts in catalysis, with a strong focus on the conversion of CO2 to useful fuels and materials. The development novel spectroscopic approaches in combination with advanced data analysis to generate fundamental understanding of catalysts at work is a red line throughout her research. After a short stent as an independent Niels Stensen postdoctoral fellow at the Weizmann Institute of Science and Hebrew University of Jerusalem, in March of 2021, she started her own research group at the Technion Institute for Technology. Her laboratory focuses on the fundamental understanding of the catalytic processes that will “fuel the future”, such as carbon dioxide valorization, fuel cell technology, nitrogen fixation and utilization, hydrogen production, and the recycling of plastics and other waste. Charlotte has won several awards, including in her listing as a Forbes “30 under 30” Europe, the UniSysCat “Clara Immerwahr Award” for achievements in catalysis research, the Beilby medal and prize, and her listing as one of C&EN’s “Talented Twelve”.
Link for further information
Title of submission
Membrane-based technologies for wastewater resource recovery and green energy exploitation
My research focuses on membrane-based technologies for wastewater resource recovery and green energy exploitation. I have developed a new type of microporous polymeric membrane that can quickly remove antibiotics and heavy metal ions from drinking water and efficiently extract lithium ions from seawater. My efforts align with the United Nations Sustainable Development Goals (SDGs) of promoting clean water and sanitation, ensuring healthy lives for people of all ages, and advancing affordable and clean energy. By creating a highly effective filtration system, our research has the potential to make a significant impact on global water quality and availability, ultimately improving the well-being of individuals and communities worldwide. Over the past five years, I have published more than ten papers in top-tier journals as the first author such as Nature Communications, Science Advances, Environmental Science & Technology, Advanced Materials, Advanced Functional Materials, and ACS Nano. I was awarded the Marie Skłodowska-Curie COFUND fellowship. And I also played a core role in building a start-up company called Lihytech. My research is committed to making meaningful contributions to advance the SDGs and improve the lives of people around the world.
About Zongyao Zhou
Zongyao Zhou is a postdoc scientist at the École polytechnique fédérale de Lausanne (EPFL) financially supported by a Marie Skłodowska-Curie Cofund Fellowship. He received his Ph.D. in Environmental Science and Engineering from King Abdullah University of Science and Technology (KAUST) in Saudi Arabia in 2022, after receiving his M.S. in University of Chinese Academy of Sciences (UCAS) in China in 2018.
His research focuses on membrane-based technologies for wastewater treatment and green energy generation at the water-energy nexus. He has published near 30 papers in prestigious journals such as Nature Communications, Science Advances, Environmental Science & Technology, Advanced Materials, Advanced Functional Materials, and ACS Nano. He received nomination award of the Competition of Open Design Challenge given by UN Development Programme in China at 2017, Chinese National Scholarship and venture competition silver medal in Beijing at 2017.
Link for further information
Title of submission
Transforming Diabetes Care: Personalized Insulin Dosing with AI Algorithms
Diabetes is a chronic illness that requires careful management of blood glucose levels to prevent short-term and long-term complications. According to a 2021 report from the WHO, 72 million people worldwide require insulin treatment for diabetes management. The amount of insulin needed can vary greatly between individuals due to factors like genetics and environment, making personalized insulin dosing essential. Currently, insulin doses are adjusted by the healthcare personnel during clinical visits, which may be far and few, leading to suboptimal diabetes management for long periods of time. Therefore, there is a need for a personalized and automated insulin dose guidance tool to improve quality of life, mitigate unwanted side-effects, and reduce healthcare costs.
My research has been focused on leveraging Artificial Intelligence to develop personalized dose guidance algorithms for both type 1 and type 2 diabetes management that automatically learns the optimal amount of insulin needed for each patient without compromising their safety. These automated tools can reduce the need for specialist healthcare and make diabetes management more affordable and accessible for everyone. This approach aligns with the UN Sustainable Development Goal 3 of promoting good health and well-being for all.
About Dinesh Krishnamoorthy
Dinesh Krishnamoorthy is a tenure-track Assistant Professor at the Department of Mechanical Engineering at TU Eindhoven. Prior to this, he was a post-doctoral researcher at Harvard John A. Paulson School of Engineering and Applied Sciences. Dinesh received his PhD in Process Systems Engineering from the Norwegian University of Science and Technology (NTNU), MSc in Control Systems from Imperial College London, and B.Eng in Mechatronics from the University of Nottingham. Dinesh also has more than four years of industrial research experience. He was working as a Senior Researcher at Statoil Research centre (Norway) between 2012-2016, and was also a part-time Senior Data Science consultant for Novo Nordisk R&D (2021). Among others, Dinesh has received the Dimitirs. N. Chorafas Foundation Award, Excellence in Computer-Aided Process Engineering Award from the European Federation of Chemical Engineers (EFCE), NTNU Faculty of Natural Sciences Best PhD Thesis Award, as well as an IFAC Young author award. His research interests include distributed optimization, optimal control, and data-driven optimization, with applications to energy and digital health.