Find Academic Supervisors

Elias Weiss is a researcher at the University of Vienna's Institute of Political Science within the Faculty of Social Sciences. He holds a BA and MA in Political Science from the University of Vienna, focusing on interpretive qualitative and exploratory research methods. His bachelor's thesis examined the duration of electoral periods, specifically the extension of Austria's legislative period from four to five years. His master's work shifted to solidarity research, particularly in labor market, economic, and health policies, analyzing the GameStop incident's political-solidarity dimensions. Research Interests: Solidarity studies, labor market dynamics, health policy, universal basic income, election period analysis, and policy discourse analysis. His work bridges political theory with empirical policy evaluation, emphasizing interdisciplinary approaches to contemporary societal challenges. Articles Trends: His publications span cognitive science, health policy, and education, reflecting a focus on mental health interventions, workplace environments, and neurocognitive adaptations. Recent work includes studies on pandemic impacts, light therapy efficacy, and stroke rehabilitation. These themes underscore a commitment to applying empirical research to real-world challenges in academia, healthcare, and public policy. Advising & Grants: No specific advising roles or grants are mentioned. His contributions are primarily through research and academic publications. Labs/Teams: Associated with the CESCoS (Contemporary Solidarity Studies) research group at the Institute of Political Science, focusing on socio-political solidarity dynamics in modern contexts.

• Solidarity Studies
• Labor Market Policy
• Health Policy
• +4 more

Daniel Cornel is a researcher affiliated with TU Wien's Department of Engineering Hydrology, part of the E222-02 research group. He holds a Dipl.-Ing. (engineering diploma) and a Dr.techn. (technical doctorate). His work focuses on integrating computational methods with environmental hydrology, emphasizing flood modeling, high-performance computing, and geospatial visualization. Cornel collaborates extensively with experts like Prof. Günter Blöschl and Prof. Jürgen Waser on projects such as the HORA 3.0 flood risk zoning initiative. His research interests span GPU-accelerated flood simulations, hydrodynamic modeling at regional scales, and decision-support systems for disaster management. Notable contributions include developing interactive visualization tools for real-time flood data and VR-based training modules for emergency response. Cornel also explores algorithm optimization for terrain modeling and subsurface network visualization. Key projects include the 'Integrated Simulation and Visualization for Flood Management' framework and the 'Master of Disaster' VR training system. His work bridges computational science with environmental engineering, addressing both technical challenges and practical applications in flood risk mitigation.

• Flood Modeling
• Hydrology
• Computational Fluid Dynamics
• +3 more

Prof. Clemens Heitzinger is an Associate Professor at TU Wien, affiliated with the Forschungsbereich Machine Learning (E194-06) . His research focuses on interdisciplinary applications of machine learning, computational methods, and nanotechnology. Key areas include reinforcement learning for healthcare optimization, stochastic modeling of PDE systems, and Bayesian inversion in sensor design. He leads the project PDE models for nanotechnology under the Scientific Computing and Modelling department (E101-03). His work spans medical imaging (e.g., electrical impedance tomography), nanopore sequencing, and nanoscale sensor development. Notable contributions include algorithms for corticosteroid therapy optimization in sepsis and superhuman performance in sepsis prediction via distributional reinforcement learning. He has advised over 13 PhD and Master's students, including Tobias Kietreiber, Sebastian Bittner, and Leila Taghizadeh. His research methodologies integrate machine learning with numerical analysis, emphasizing uncertainty quantification and PDE modeling. Recent trends in his publications highlight applications in personalized healthcare, industrial anomaly detection, and computational fluid dynamics in nanoscale systems. While no scientific awards are explicitly mentioned, his work has been published in high-impact journals and conference proceedings, reflecting his contributions to computational science and engineering.

• Machine Learning
• Reinforcement Learning
• Nanotechnology
• +7 more

Dr. Peter Gangl is a Senior Research Scientist at the Johann Radon Institute for Computational and Applied Mathematics (RICAM), Austrian Academy of Sciences, where he leads research in optimization and computational mathematics. He holds a Ph.D. (2017) and M.Sc. (2012) from Johannes Kepler University Linz. His research focuses on topology/shape optimization, topological derivatives, and multiphysics simulation of electric machines. Research Interests: Gangl specializes in developing mathematical methods for PDE-constrained optimization, with emphasis on computational electromagnetics, automated sensitivity analysis, and multi-objective design. His work bridges applied mathematics and industrial applications, particularly in electric motor optimization. Research Projects: Principal Investigator for SFB F90 'CREATOR' (2022–2026) on topology optimization under electro-thermal coupling Led FWF project 'Multiphysical Shape Optimization of Electrical Machines' (2020–2024) Awards & Honors: Richard C. DiPrima Prize (SIAM, 2018) Erwin Wenzl Preis (2018) Anile Prize (ECMI, 2018) Promotio sub auspiciis (Austria's highest academic honor, 2017) Students & Collaboration: Supervises PhD candidates (Nepomuk Krenn, Michael Winkler) and collaborates with institutions including TU Graz, TU Darmstadt, and international partners. Organizes workshops/seminars on optimization and computational mathematics.

• Topology Optimization
• Shape Optimization
• Computational Mathematics
• +3 more

Johannes Friedl is an Adjunct Senior Lecturer at Queensland University of Technology and Senior Scientist at the Institute of Soil Research, University of Natural Resources and Life Sciences Vienna (BOKU). With a PhD in Environmental Science from Queensland University of Technology (2017), he specializes in soil nitrogen and carbon cycling within terrestrial ecosystems, focusing on greenhouse gas emissions and microbial pathways in agricultural systems across climate zones. Key Appointments : 2023: Adjunct Senior Lecturer, Queensland University of Technology 2023: Senior Scientist, Institute of Soil Research, BOKU Core Expertise : Stable isotope techniques Biogeochemical modeling Nutrient loss mitigation Climate-agriculture interactions His research integrates high-resolution sensor data , molecular analysis , and 15N tracer methods to optimize nitrogen management in pastures and sugarcane systems. Recent work emphasizes emission hotspots and dual N2O/N2 measurement for accurate biogeochemical modeling. Selected Scientific Awards : 2020: Future Leaders Project Award, QUT 2017: QUT Vice-Chancellor’s Performance Award 2016: Soil Science Australia Thesis Award 2015: QUT Faculty Publication Award As a community reviewer for journals like Agriculture, Ecosystems & Environment and Biogeosciences , he contributes to advancing nitrogen cycle research. His international collaborations span institutions in Australia, Denmark, and Austria.

• Soil science
• greenhouse gas emissions
• stable isotopes
• +7 more

Patrick Höschele is a researcher at Graz University of Technology (TU Graz), holding the academic degrees of Dipl.-Ing. (equivalent to MSc), Dipl.-Ing. Dr.techn. (Doctor of Technical Sciences), and BSc. He is affiliated with the Institute for Vehicle Safety at TU Graz, where he conducts research on vehicle safety and battery technologies. Research Focus: Lithium-ion battery safety and reliability Electro-mechanical interactions in battery systems Second-life applications for automotive batteries Crash safety and mechanical deformation effects on batteries Thermal management and aging mechanisms His research spans multiple interdisciplinary areas including mechanical engineering, electrical engineering, materials science, and energy storage systems. The primary focus lies in understanding how mechanical stresses, environmental conditions, and aging processes affect the performance and safety of lithium-ion batteries, particularly in automotive applications. Research Trends: The body of work demonstrates a consistent focus on battery safety under mechanical loading conditions, with particular emphasis on pouch cell behavior. Recent studies investigate the interplay between electrochemical performance and mechanical integrity, especially concerning second-life applications. The research methodology combines experimental investigations with numerical modeling approaches. Contact Information: Email: patrick.hoeschele@tugraz.at Institute for Vehicle Safety TU Graz Inffeldgasse 13/VI 8010 Graz, Austria

• Vehicle Safety
• Lithium-Ion Battery Safety
• Electro-Mechanical Systems
• +3 more

Mohammadreza Aali is a Researcher at the Institute of Polymer Processing and Digital Transformation, Johannes Kepler University Linz, Austria. His work focuses on advancing polymer manufacturing through computational modeling and digital transformation, with active involvement in European and Austrian-funded research projects. Dr. Aali's research spans polymer processing, computational fluid dynamics, and digital transformation in manufacturing. Key areas include viscoelastic material behavior analysis, centrifugal drying system optimization for pelletizing, and extrusion die design enhancement using high-performance computing. His methodologies integrate OpenFOAM, DEM-MPS coupling, and advanced simulation techniques to improve process efficiency and product quality in industrial polymer applications. Recent publications (2024-2025) demonstrate a concentrated focus on computational solutions for polymer processing challenges. Works cover force/torque calculations for viscoelastic materials, drying efficiency optimization, digitalization techniques, and extrusion die design, appearing in journals like Polymers and International Polymer Processing . These publications highlight interdisciplinary research at the intersection of materials science, mechanical engineering, and computational methods. Dr. Aali currently contributes to the Pro2Future CoExCo 2 project (2021-2025), funded by the Austrian Research Promotion Agency (FFG), and previously participated in an EU-funded PVC extrusion project (2023-2024). His research portfolio indicates strong grant acquisition capabilities in polymer processing optimization, with opportunities for collaboration and mentorship in computational polymer engineering. As part of Johannes Kepler University's Institute of Polymer Processing and Digital Transformation, Dr. Aali collaborates within a multidisciplinary team advancing digital transformation in polymer manufacturing. His work involves close cooperation with researchers across institutions on projects integrating experimental validation and computational modeling to solve industrial challenges in polymer processing equipment design and operation.

• Polymer Processing
• Computational Fluid Dynamics
• Digital Transformation
• +3 more

Peter Kulczycki is a researcher at the Research Center Hagenberg Bioinformatics, University of Applied Sciences Hagenberg. He serves as a Researcher specializing in bioinformatics and high-performance computing with expertise in developing computational solutions for biological research challenges. His research interests span multiple domains: Bioinformatics and computational biology High Performance Computing and parallel processing Intelligent scheduling algorithms Resource management systems DNA analysis and primer design Web-based bioinformatics education Dr. Kulczycki's work focuses on bridging computational science and biological research through efficient algorithms and systems for processing complex biological data. He has made significant contributions to scheduling systems that optimize heterogeneous computing resources for bioinformatics applications, with research progression from foundational bioinformatics resources to sophisticated scheduling systems that predict job execution times. His publication record shows consistent focus on computational efficiency in bioinformatics through innovative scheduling approaches, with notable work on heterogeneous multiplatform hardware, DNA primer calculation using GPGPUs, and web-based bioinformatics education frameworks. Dr. Kulczycki served as Principal Investigator for the Bioinformatics Resource Facility Hagenberg project (2009-2012) under the COIN Cooperation & Innovation program. He has been active in academic discourse, delivering invited talks on Evolution and Genetics and the Birth of Life in 2007. His research collaborations include G. Lirk, H. Brandstätter-Müller, B. Parsapour, and A. Hölzlwimmer on various bioinformatics projects.

• Bioinformatics
• High Performance Computing
• Intelligent Scheduling
• +4 more

Jonas Ries is a Professor at the University of Vienna, affiliated with the Department of Structural Biology and Computational Biology. His research focuses on super-resolution microscopy, cryo-electron microscopy, and structural analysis of cellular components. Department: Structural Biology and Computational Biology Specialization: Nuclear pore complex architecture, MINFLUX nanoscopy, fluorescent labeling. His recent work includes 2025 projects on mitochondrial fission during apoptosis via SMLM and MINFLUX, and developing a cost-effective MINFLUX microscope. He collaborates internationally, with a focus on nuclear pore complexes and artificial intelligence applications in microscopy. 2024 contributions highlight advancements in 3D MINFLUX excitation, dynamic structural biology, and synaptonemal complex analysis in C. elegans. His projects often involve computational modeling and high-throughput imaging. Research Trends Recent publications emphasize super-resolution techniques (MINFLUX, SMLM), PSF inverse modeling for microscope calibration, and nuclear pore complex dynamics. Subfields include apoptosis mechanisms, clathrin coat bending, and AI-driven image analysis. Academic Engagement He participated in the Dies Academicus event at the University of Vienna in 2024, indicating active involvement in academic community activities.

• Structural Biology
• Computational Biology
• Super-Resolution Microscopy
• +4 more

Fabian Paischer is a Researcher at the Institute for Machine Learning, Johannes Kepler University Linz (JKU), holding a Doctorate and Master of Science degree. His work bridges machine learning with high-impact scientific domains including plasma physics for fusion energy and reinforcement learning systems. Education: Doctorate (Dr.) Master of Science (MSc) His research focuses on developing neural surrogate models for plasma turbulence simulations and advancing reinforcement learning through pre-trained model modulation and human-readable memory architectures. This interdisciplinary work integrates deep learning with computational physics and autonomous decision-making, targeting applications in sustainable energy and intelligent systems where interpretability and data efficiency are critical. Analysis of his 2023-2025 publications reveals two dominant research thrusts: (1) neural operator applications for plasma edge simulations requiring long-term predictive accuracy in fusion environments, and (2) modular reinforcement learning frameworks enabling knowledge transfer between pre-trained models. These directions highlight his commitment to solving complex scientific computing challenges through novel AI methodologies. Dr. Paischer actively participates in academic communities, including the ELLIS Doctoral Symposium (2021), and maintains ongoing research output through preprints and conference publications at venues like NeurIPS and ICLR workshops.

• Machine Learning
• Reinforcement Learning
• Plasma Physics Simulations
• +1 more