The Young Academy Twente is excited to announce its eleven new members for 2025. Representing all five faculties of the UT, the new members will join the current team in, for instance, offering both solicited and unsolicited advice to the Executive Board and the Strategic Board. Together, YAT will foster a vibrant community for early-career UT employees, contributing to discussions on a wide range of topics. The new members will be officially installed on 2 July.
Elnaz Neinavaz (ITC)
Elnaz's research interests focus on monitoring biodiversity using remote sensing and Earth observation applications to understand the trends and impacts of climate change-related extreme events on biodiversity. She primarily applies high-resolution thermal infrared hyperspectral data in her research studies.
As a remote sensing expert with a background in ecology and biodiversity, Elnaz investigates which vegetation biochemical and biophysical variables can be applied to discover robust relationships with biodiversity metrics. This will enable scientists to monitor biodiversity more effectively, reduce the adverse impacts of extreme events, and better plan mitigation schemes.
Annika Betken (EEMCS)
From the daily values of stock indices to the minutely recorded number of your heart beats: time series appear everywhere. Their analysis becomes increasingly important due to the massive production of data through, e.g. the internet of things or the digitalization of healthcare. Annika’s research focuses on robust methods for time series analysis, i.e. on statistical techniques that are designed to handle data that contains outliers, structural changes, or other types of deviations from expected patterns.
Mehrshad Mehrpouya (ET)
Advanced manufacturing technologies are crucial for designing and fabricating innovative products that cannot be produced using conventional methods. Integrating smart materials, such as shape memory materials, presents a unique opportunity to develop a new generation of smart products with multifunctional properties. Mehrshad focuses on the 3D/4D printing of smart materials and structures, particularly on developing novel shape memory materials and improving the techniques used for their fabrication.
Gerwin Hoogsteen (EEMCS)
We are in the midst of a revolutionary transition that reshapes how we produce, store and consume energy. The future sustainable electricity supply chain of the future is organized bottom-up and consists of millions of digitally connected devices that together need to reliably provide and consume electricity. Gerwin Hoogsteen researches and demonstrates novel distributed and robust energy coordination algorithms together with a diverse team of experts and industry partners to jointly enable this energy transition. This entails research on distributed optimization algorithms, deep integration of systems in their new cyber-physical context, and the development of strategies to make this digitalized intelligent grid resilient to e.g., component failure and cyber-attacks.
Davoud Jafari (ET)
Davoud Jafari's research focuses on developing and investigating the fundamental science and engineering of energy materials through additive manufacturing. His work aims to tailor and control correlated functions related to thermodynamics, kinetics, and transport. This includes creating surfaces for thermochemical or electrochemical reactions, conducting electrons and heat, and distributing fluids. Leading the additive manufacturing solutions for energy materials team, Davoud explores enhanced processes to create and test complex geometrical shapes and realize hierarchical structures with graded composition and length scales. His research is concentrated on three main application areas: heat transfer, electrochemical, and thermochemical systems. A common key challenge in his work is achieving precise control over material properties to tailor them for sustainable energy-related applications.
Gréanne Leeftink (BMS)
How can healthcare processes be organised in such a way that they are people-centred in an increasingly complex world? Gréanne Leeftink supports the transformation of healthcare through the development of data-driven decision support algorithms for the efficient design of integrated healthcare processes. Her focus is on bridging the gap between theoretical optimization algorithms and real-world healthcare applications with all its inherent uncertainties, ultimately benefitting both patients and professionals. To this end, she develops strategies for resource management and process optimization, ensuring that healthcare runs efficiently and effectively, while promoting a sustainable and considerate deployment of scarce healthcare professionals. Her goal is to maximize the impact on patient care through a multi-stakeholder approach and advanced algorithm development.
Russell Chan (BMS)
Russell Chan is an Assistant Professor at the University of Twente, working in the area of cognitive-motor neuroscience. He is well-known for using cognitive enhancement techniques to unlock the potential of the mind with the vision of improving health, well-being, and performance. Using multimodal neuroimaging techniques, he investigates performances in motor sequence learning to understand the different mechanisms. His work intersects the boundaries of movement, cognition, and consciousness.
Sophie Langer (EEMCS)
How do deep learning methods distinguish between cats and dogs? Or more importantly, how do they detect diseases or identify traffic signs? Without answering these questions, we risk unexpected behaviour of the methodology with potentially legal or ethical implications. Sophie Langer investigates the underlying functioning of deep learning-based methods, particularly focusing on their statistical properties. Her research enhances the theoretical understanding of the methodology, contributing to a safer and more reliable AI future.
Jelmer Renema (TNW)
Jelmer Renema is at the forefront of developing photonic quantum computers, where individual light particles, photons, perform highly complex calculations beyond the capability of current (super) computers. He obtained his PhD cum laude from Leiden University in 2015, focusing on superconducting single photon detectors. Following this, he worked at Oxford with a Rubicon grant, developing optical chips despite facing a chip shortage that spurred his interest in the technology. In 2018, Renema received a Veni grant for a postdoc position at the University of Twente, where he became acquainted with the university's research. By 2020, he had joined the Adaptive Quantum Optics group as an associate professor. Alongside his academic achievements, Renema is also the CTO of Quix Quantum, a successful start-up from the University of Twente.
Julia Mikhal (BMS)
Julia Mikhal develops computational models for clinical applications and decision support. Her research combines mathematical modelling and clinical data analysis to improve safe and early discharge after oncological surgery, as well as uncover mechanisms of vascular disease. Julia Mikhal’s work utilizes advanced mathematical and computational methods to extract meaningful information from complex datasets and develop accurate models predicting patient-specific outcomes.
Kuan Chen (EEMCS)
How can we create future-proof computing systems that serve as the backbone of modern society while maximizing their resilience against environmental uncertainties? As a computer scientist, Kuan-Hsun Chen is dedicated to advancing cyber-physical systems, which continuously interact with the physical world in numerous safety-critical scenarios. These systems must not only deliver correct functionalities but also ensure timely performance to prevent catastrophic failures. By prioritizing predictability and reliability, he explores efficient mapping solutions that meet all non-functional constraints imposed by underlying hardware platforms. His pioneering research lies at the intersection of computer science and electrical engineering, driven by his conviction that synergy between software and hardware is key to creating such systems.
