Find Academic Supervisors

• Plant Physiology
• Drought Tolerance
• Metabolomics
• +3 more

Dr. Karin Köhl is a Researcher and Service Group Leader at the Max-Planck-Institut für Molekulare Pflanzenphysiologie in Potsdam, Germany. She specializes in plant stress responses, particularly drought tolerance in potato and Arabidopsis. Her work integrates genetics, metabolomics, and advanced phenotyping techniques to identify biomarkers and improve crop resilience. Köhl holds a Diplom (1991) and Ph.D. (1995) from the University of Düsseldorf, followed by postdoctoral research at Oxford University and the MPI-MP. Her research emphasizes translating controlled environment studies into real-world ecological relevance, addressing challenges like light quality effects, container-based stress assays, and field validation. Key contributions include developing software tools for phenotypic data management and advancing understanding of ion transport in photosynthesis and freezing tolerance. Research interests focus on: Abiotic stress biology (drought, cold, salinity) Genetic and metabolic basis of stress adaptation High-throughput phenotyping and data integration Climate-resilient crop development Publications highlight innovative approaches in: Whole-genome sequencing for drought tolerance in potatoes LIDAR-based phenotyping for non-destructive stress analysis Thylakoid ion transport mechanisms in photosynthetic acclimation Laboratory activities center on the Plant Cultivation/Transformation service group, supporting cutting-edge plant physiology research with advanced cultivation and transformation infrastructure.

• Cognitive Science
• Computer Science
• Education
• +3 more

Christopher Young is a researcher with a diverse academic portfolio spanning Cognitive Science, Computer Science, and Biomedical Engineering. His work primarily focuses on Human-Computer Interaction , Virtual Reality applications , and Child Development in educational contexts. While his university affiliation is not explicitly stated in the provided texts, he earned his PhD from the University of Illinois Urbana-Champaign in 1992, specializing in digital filters. Young's interdisciplinary research bridges education , technology , and biomedical rehabilitation . Research Trends : His publications from 2024 to 1992 reveal a trajectory in Virtual Reality for workforce and management training Embedded Systems and energy-efficient object detection Cognitive Development in children's numerical and spatial abilities Biomedical Applications including surgical video summarization and motor rehabilitation Architectural Design with augmented reality interfaces Awards & Collaborations : No explicit awards are listed in the texts. His collaborations include prominent figures like Susan C. Levine (Cognitive Science), Boris Murmann (Electrical Engineering), and Barbara Cutler (Computer Science).

• High Performance Computing
• Energy Efficiency
• Data Center Operations
• +3 more

Dr. Torsten Wilde is a researcher at Technical University Munich , Germany, with a focus on High Performance Computing (HPC) and Energy Efficiency in data centers. His work spans over a decade, integrating Machine Learning , Simulation and Modeling , and Operational Data Analytics to optimize HPC systems.

Jens GerkenView profile

Professor

• Human-Robot Interaction
• Assistive Robotics
• Human-Computer Interaction (HCI)
• +3 more

Jens Gerken is a Professor of Technology for Inclusion: Mechatronics and Robotics at TU Dortmund University since July 2023, affiliated with the Research Unit for Inclusive Human-Robot Interaction. He holds a PhD (2011), Master (2006), and Bachelor (2004) in Information Engineering from the University of Konstanz. Previously, he was a Professor of Media Informatics (2015-2023), Managing Director of Immersion7 GmbH (2014-2016), and Senior Consultant at ICT AG (2011-2013). Key Research Focus: Inclusive human-robot collaboration mechanisms, transparency in AI-driven systems, mixed-reality simulation environments Expertise: Human-Computer Interaction (HCI), assistive robotics, adaptive control interfaces, accessibility design His work emphasizes trust-building through transparent interaction systems and accessible assistive technologies. Recent publications (2023-2024) focus on shared control mechanisms for robotic arms, AI-enhanced interfaces, and gamified rehabilitation tools like HoloBoard.

Nicole SchubertView profile

Researcher

• Image Processing
• Medical Imaging
• 3D Visualization
• +5 more

Nicole Schubert is a researcher at the Forschungszentrum Jülich GmbH, affiliated with the Institute of Neuroscience and Medicine (INM) , specifically the Structural and Functional Organisation of the Brain (INM-1) . Her work focuses on medical imaging, 3D visualization, and high-performance computing for brain architecture analysis. Research Interests: Image Processing, Medical Imaging, 3D Visualization, High Performance Computing, and Computational Neuroscience. Key Methodologies: 3D-Polarized Light Imaging (3D-PLI), multimodal imaging integration, and geometric modeling of nerve fibers. Technical Contributions: Development of tools like FAConstructor and advanced algorithms for fiber orientation analysis and histological data alignment. Her publications emphasize brain microstructure reconstruction, computational neuroanatomy, and visualization techniques. No explicit awards, educational history, or student advisement details are provided in the available data.

• Molecular Simulations
• Neurobiology
• Drug Design
• +4 more

Prof. Paolo Carloni is Director of the Computational Biomedicine group (INM-9) at the Institute of Neuroscience and Medicine (INM), Research Center Jülich. He holds a Professorship and has over 30 years of expertise in developing multiscale molecular simulation methods to study biomolecular systems. His research focuses on structure-function relationships of enzymes, neuroreceptors, and drug resistance mechanisms, leveraging high performance computing and machine learning. Research Interests: Multiscale simulation techniques (quantum to coarse-grained) Neurobiological processes and signaling cascades Drug design targeting neuroreceptors and RNA-binding proteins Metadynamics and free-energy calculations Exascale computing for biomolecular applications Recent Work: His publications emphasize computational drug discovery, ligand-receptor interactions, and understanding protein mutations linked to neurodegenerative diseases. He leads projects on exascale algorithm optimization and FAIR data principles in simulations. Awards: While no specific awards are listed, his Google Scholar h-index of 67 reflects significant academic impact. Lab & Collaborations: Active in the INM-9 lab, collaborating with Jülich Supercomputing Centre (JSC) and Helmholtz Association initiatives. His team focuses on computational tools like MiMiC and QM/MM simulations.

Emiliano IppolitiView profile

Researcher

• Molecular Dynamics
• High Performance Computing
• Quantum Mechanics/Molecular Mechanics (QM/MM)
• +3 more

Dr. Emiliano Ippoliti is a Senior Scientist at the Institute of Neuroscience and Medicine (INM-9: Computational Biomedicine) at Forschungszentrum Jülich GmbH , Germany. His primary focus is on advancing high-performance computing methodologies for biological systems, particularly classical and ab initio molecular dynamics , and developing tools like the MiMiC framework for multiscale simulations. He holds a Master's in Physics (University of Pisa, 2001) and a PhD in Theoretical Physics (University of Trieste, 2005), followed by postdoctoral research at SISSA/ISAS and the German Research School for Simulation Sciences. His research integrates quantum mechanics/molecular mechanics (QM/MM) , exascale computing , and drug design , addressing challenges in membrane transport, enzyme mechanisms, and drug permeation. Recent work includes studies on CLC transporters, PETase enzyme dynamics, and computational drug screening. He has authored over 40 publications and serves as a referee for PRACE and journals such as Journal of Chemical Theory and Computation . Key contributions include: Developing MiMiC and MiMiCPy for scalable QM/MM simulations Advancing understanding of proton transport in biological systems Modeling drug interactions with cell membranes and ion channels No specific awards are listed, but his work is recognized through extensive peer-reviewed output. He collaborates internationally in exascale computing initiatives and contributes to the Computational Biomedicine group at Jülich.

• Seismology
• Geophysics
• Probabilistic Seismic Hazard Assessment (PSHA)
• +4 more

Pablo Cristián Iturrieta is a Researcher at the Section 2.6 Seismic Hazard and Risk Dynamics , GFZ German Research Centre for Geosciences , affiliated with Universität Potsdam . His work focuses on Seismology , Probabilistic Seismic Hazard Assessment (PSHA) , and Earthquake Forecasting , with a specialization in modeling seismicity rates, stress field disruption, and fault interactions in tectono-volcanic systems. Education : PhD in Earth Science (2024), Universität Potsdam Research Affiliations : GFZ German Research Centre for Geosciences, Department of Earth Sciences, Universidad Potsdam His recent publications address seismic hazard models for New Zealand , statistical power of forecast tests , geothermal fluid dynamics , and non-Poissonian seismicity . Collaborative work spans the CSEP (Collaboratory for the Study of Earthquake Predictability) framework and tectonic implications of fault zones in the Andean Southern Volcanic Zone . Key contributions include multi-resolution grid approaches and uniform rate zone forecasts for hazard assessment. His articles emphasize earthquake rate variability , fluid-magma interactions , and software modernization for forecast testing. Collaborations include institutions in Germany, New Zealand, Italy, and Chile. No scientific awards or formal student advising details are explicitly mentioned in the provided texts.

Andreea MolnarView profile

Associate Professor

• Computing for Social Good
• Gender and Diversity in Information Technology
• Healthcare Information Systems
• +3 more

Dr. Andreea Molnar is an Associate Professor at Swinburne University of Technology's School of Science, Computing and Emerging Technologies. She holds the Anna Boyksen Fellowship at the Technical University of Munich (TUM-IAS) and is a Fellow of the International Science Council. Her research focuses on computing for social good, gender diversity in IT, and health-related information systems. Dr. Molnar earned her PhD from the National College of Ireland and has held positions at Lancaster University, University of Portsmouth, and Arizona State University. Education: PhD (Technology Enhanced Learning, National College of Ireland), MSc (Modelling & Simulations), BSc (Computer Science) Professional Roles: Co-Chair of Anita Borg Institute's Pass It On Awards (2015-2020), Global Health Project Lead at Global Young Academy Her work addresses gender equity in IT education and the ethical use of AI. Key publications include analyses of diversity initiatives and generative AI ethics in computing education. She has secured grants such as the Identifying the Initiatives that Influence 1st Year Female Students Choosing Computing Degrees (ACDICT, 2018-2019) and collaborates on projects like the Glen Eira Social Data Analytics Dashboard. Awards include the Science & Technology Australia scholarship, Adobe Innovation Award (2021), and recognition as a Senior Editor for Information Technology & People .

• Quantum Computing
• Optimization Methods
• Smart Grid Technologies
• +5 more

Junpeng Zhan is an Assistant Professor of Renewable Energy Engineering at the Inamori School of Engineering, Alfred University, NY, USA. He holds a Ph.D. and B.Sc. in Electrical Engineering from Zhejiang University (2014 and 2009). Before joining Alfred, he worked as a Research Associate at Brookhaven National Laboratory (2018–2020), a Postdoctoral Fellow at the University of Saskatchewan and Hong Kong Polytechnic University, and a Visiting Research Assistant at the University of Liverpool. His research focuses on quantum computing, optimization methods, smart grid technologies, machine learning, and renewable energy integration. Notable contributions include developing the Quantum Feasibility Labeling algorithm and the hybrid Variational Quantum Search, which address NP-complete problems like the Vertex Coloring problem. He currently leads NSF-funded projects on variational quantum algorithms for power system simulation and ISO-New England-funded work on quantum computing for unit commitment. Zhan is an Associate Editor of IET Generation, Transmission & Distribution and actively reviews for 20+ journals. His grants include $199,980 from the NSF (2022), $50,000 from ISO-New England (2024–2026), and a co-PI role in a $1.37M NYSERDA-funded workforce training initiative. His work bridges fundamental research and practical energy system challenges, emphasizing computational innovation and scalability. Labs and collaborations include the Engineering Laboratories at Alfred University, with partnerships extending to institutions like RIT and GE. His teaching spans courses in power systems, Python for research, and mechatronics.

• Social Hierarchy
• Social Networks
• Anthropology
• +3 more

Daniel Redhead is a Researcher at the Max Planck Institute for Evolutionary Anthropology within the Department of Human Behavior, Ecology and Culture. He holds a PhD in Psychology from the University of Essex and advanced degrees in Anthropology from Durham University. His research examines social hierarchy dynamics through interdisciplinary approaches combining anthropology, psychology, and network analysis. Research interests focus on: Evolution of social hierarchies and status acquisition Cross-cultural analysis of cooperation networks Computational modeling of group dynamics Longitudinal studies in diverse populations including indigenous communities Development of methodological tools for social network analysis His publications (2019-2025) demonstrate consistent focus on social networks, inequality, and cultural transmission, with methodological innovation in statistical modeling and field research. Recent works emphasize computational approaches to network analysis and cross-cultural examinations of cooperation. Awards and honors include: ESRC Research Methods Development Grant (Co-I, £200K, 2020) European Human Behavior & Evolution Association Award (2017) Experimental Psychology Society Study Visit Award (2016) Multiple University of Essex research grants and scholarships Teaching experience includes graduate instruction in Social Network Analysis and Research Methods at University of Essex. Professional activities encompass peer review for major journals and memberships in anthropological/psychological associations. Fieldwork spans four continents including ongoing longitudinal research with Mayangna communities in Nicaragua.

Pia EbelingView profile

Researcher

• Hydrology
• Environmental Science
• Catchment Hydrology
• +6 more

Dr. Pia Ebeling is a Researcher at the Department of Hydrogeology, Helmholtz Centre for Environmental Research - UFZ in Leipzig, Germany. She holds a Master of Science in Hydrology (2018) and a Bachelor of Science in Hydrology (2014), both from Technical University Dresden. Her research focuses on water quality dynamics, catchment-scale nutrient interactions, data-driven hydrological analysis, and groundwater dynamics under climate variability. She has been involved in international research stays, including at INRAE in France (2018-2022), and has contributed to projects such as CAMELS-DE and QUADICA, which compile extensive hydro-meteorological datasets for German catchments. Dr. Ebeling has received the Karl-Franz-Busch Medal (2018) for her Master’s thesis on seawater intrusion remediation. She collaborates with interdisciplinary teams in the Helmholtz program 'Changing Earth - Sustaining our Future', particularly in topics like coastal zones, landscapes of the future, and sustainable bioeconomy. Her work emphasizes developing Python-based modeling tools, integrating machine learning for environmental prediction, and addressing global challenges in water security and ecosystem health. Education: Bachelor of Science in Hydrology, Technical University Dresden (2014) Master of Science in Hydrology, Technical University Dresden (2018) Research Interests: Quantifying groundwater dynamics and drought patterns Examining nutrient depletion and stoichiometric imbalances in streams Advancing large-sample hydrological analysis through data synthesis Modeling subsurface processes under climate change scenarios Developing open-source tools for hydro-ecological research Advising & Grants: Completed PhD under the supervision of Prof. Jan Fleckenstein at UFZ (2022) Contributed to interdisciplinary research initiatives like Helmholtz TRACER PhD school Involved in international collaborations, including with the University of Texas at Austin’s hydrology team Labs/Teams: Member of the Hydrogeology Department team at UFZ Contributor to the 'Healthy Planet' and 'Landscapes of the Future' research topics Developed the HydroEcoLSTM package for hydro-ecological modeling

• Earth System Modeling
• Scientific Programming
• Climate Science
• +3 more

Nadine Wieters is a Researcher at the Alfred Wegener Institute (AWI) in Bremerhaven, Germany, specializing in Climate Dynamics. Her primary affiliation is within the Climate Sciences division, focusing on Earth System Modeling and Scientific Programming. She contributes to the development of modular infrastructure for coupled Earth system models through projects like ESM-Tools. Her research emphasizes advancing computational frameworks to enhance model interoperability and efficiency. Key collaborations include work on the AWI-CM model prototype and the esm-interface library. Wieters actively participates in international conferences such as EGU General Assemblies and deRSE events, presenting advancements in software tools for climate research. With a focus on software engineering for climate science, her work bridges computational methods and environmental modeling, supporting both standalone and coupled simulations. She is based at the AWI's Bremerhaven site, contributing to the institute's broader mission in polar and marine research through innovative technical solutions.

• Bioinformatics
• Cryptography
• Genetic Algorithms
• +5 more

Mohammad Nassef is an academic researcher with a focus on interdisciplinary applications combining computer science, bioinformatics, and cryptography. His work spans multiple domains, including Developing bio-inspired algorithms for audio and image encryption Optimization techniques in genetic data analysis Automated scoring systems in educational software Edge detection methods for biomedical imaging Research Trends: His publications highlight a consistent integration of biological sequence modeling into computational algorithms, with recent work emphasizing cybersecurity, data compression, and machine learning applications in genetics. Collaborations with researchers like Ibrahim Farag, Amr Badr, and Monagi H. Alkinani indicate a networked approach to solving complex problems in data security and medical informatics.

• Data Science
• Machine Learning
• Distributed Computing
• +4 more

Chris Mattmann is an academic affiliated with the University of Southern California, specializing in data science, machine learning, and high-performance computing. His work spans interdisciplinary applications in Earth sciences, climate modeling, and distributed systems. He has contributed to projects like the Earth System Grid Federation and Apache open-source software. His research emphasizes scalable data management, secure parser development, and automated machine learning systems. Education & Background: While specific educational details aren't listed, his extensive publication record in top-tier journals and conferences indicates advanced training in computer science and computational science. Research Interests: Focus areas include distributed computing infrastructure for scientific applications, machine learning for geosciences, and data-intensive systems. He explores challenges in data movement, scalable supercomputing, and open-source tools for scientific workflows. Publications: Over 150 peer-reviewed articles since 2003, with recent work on super-resolution satellite data, deep learning in geosciences, and secure parser systems. His contributions highlight advancements in both foundational computing and applied environmental science.