Find Academic Supervisors

Matthias DrosselView profile

Professor

• Applied Health-Care
• Health-Care Education
• Nursing Science
• +6 more

Prof. Dr. Matthias Drossel has been Professor of Applied Health-Care at Hof University of Applied Sciences , Faculty of Interdisciplinary and Innovative Sciences, since September 2022. He leads the Chair of Applied Health-Care, teaches across nursing and health-care education programmes, and previously served as programme director for Innovative Health-Care , the Bachelor and Master Nursing programmes, and part-time Health-Care Education. Education & Career Path Trained as a registered nurse with intensive-care experience. Bachelor’s degree in Medical Education (part-time while working). Master of Science in Nursing Science & Education. Doctor of Philosophy (Dr. phil.) in Gerontology & Demography, 2018 – dissertation on strengthening informal care for older adults in rural Upper Franconia. 2010–2022: Lecturer, later Professor of Medical Education, SRH University of Health; Academic Director (from 2020) at Bamberg Academies for Health & Nursing Professions. Research Focus Prof. Drossel’s scholarship centres on applied health-care delivery, nursing education, gerontology, and organisational development . He develops and evaluates models for evidence-based nursing , designs health-promotion interventions in vocational schools, and investigates informal caregiving in structurally weak rural regions. His RefID-Model (Reflection-Identification-Model) fosters continuous school development and has been implemented in nursing schools and companies. Recent Publication Trends Between 2017 and 2022, Prof. Drossel’s articles increasingly addressed informal caregiver support, rural health-care challenges, simulation-based education, and innovative curricular models . A noticeable cluster of works explores the Skill-&-Grade-Mix Center as a best-practice facility for competency-oriented training, while another stream deepens understanding of salutogenic approaches to student and staff well-being. Scientific & Professional Service Co-founder & Director, SURefId-Institut (School & Corporate Development via Reflection & Identification). Project Leader, Didactics & Research Transfer (third-party funded, 2020–2022). Editor-in-Chief, peer-reviewed open-access journal „Lehren und Lernen im Gesundheitswesen“ (Facultas). Vice-President, Bavarian Association of Nurses (registered association). Board member, AWO Bamberg City & District; Head of Department for School Development & Management, Federal Association of Teachers in Health-Care Professions. Laboratories & Collaborative Teams Prof. Drossel initiated Germany’s first Skill-&-Grade-Mix Center® at Bamberg Academies, equipped for high-fidelity simulation and interprofessional training. Via the SURefId-Institut he continues to advise schools, hospitals, and long-term care facilities on implementing reflective development processes and blended-learning environments.

Kapil AhujaView profile

Professor

• Machine Learning
• Network Science
• Computational Optimization
• +4 more

Prof. Kapil Ahuja is a Full Professor in the Department of Computer Science & Engineering at the Indian Institute of Technology Indore (IIT Indore), where he heads the Mathematics of Data Science and Simulation (MODSS) research lab. After completing dual Master's degrees and a Ph.D. from Virginia Tech (USA) followed by postdoctoral work at the Max Planck Institute in Germany, he has held visiting positions at UT Austin, IMT Atlantique, Sandia National Labs, TU Dresden, and TU Braunschweig. His administrative roles include founding Dean of International Affairs and former Head of Computer Science & Engineering at IIT Indore. Education: Ph.D. in Mathematics, Virginia Tech (2011) M.S. in Mathematics, Virginia Tech (2009) M.S. in Computer Science, Virginia Tech (2007) B.Tech. in Mechanical Engineering, IIT (BHU) Varanasi (2001) Research Focus: Prof. Ahuja's work bridges theoretical advances with real-world applications, emphasizing machine learning algorithms for plant/cancer studies, game-theoretic poverty reduction models, exascale climate modeling solvers, and drone trajectory optimization. His interdisciplinary approach integrates numerical linear algebra with network science to solve complex systems problems across healthcare, agriculture, and climate science, supported by 4.85 Crores INR in external funding. Publication Trends: Recent work demonstrates growing emphasis on AI-driven optimization for physical systems (drones, climate models) and biomedical applications (cancer classification). His publications increasingly feature cross-disciplinary collaborations between computer science, biology, and economics, with notable contributions in explainable AI for healthcare and resource allocation algorithms for social networks. Scientific Recognition: National Teacher's Award (2024) from the President of India Five-time recipient of IIT Indore's Best Teacher Award (2013-2023) Best Poster Award at International Workshop on Game Theory & Networks (2019) Steeneck Graduate Research Fellowship (Virginia Tech, 2011) Multiple SIAM travel awards for international conferences Mentorship & Service: Prof. Ahuja has graduated 5 Ph.D. and 4 M.S. (Research) students while mentoring 75 B.Tech. projects. He serves as Associate Editor for Applied Intelligence Journal (Springer Nature) and Knowledge and Information Systems, organizes international conferences, and reviews for 35+ academic sources. His administrative leadership significantly expanded IIT Indore's global partnerships through the Research Park initiative. Research Infrastructure: The MODSS lab maintains active collaborations with Oak Ridge National Lab, Sandia National Labs, and European institutions. Current projects include AI-optimized drone swarms for agricultural monitoring and game-theoretic models for poverty intervention, utilizing high-performance computing resources for large-scale simulations.

Alexander EckerView profile

Professor

• Machine Learning
• Computational Neuroscience
• Visual Perception
• +3 more

Prof. Dr. Alexander Ecker is Professor of Data Science at the Institute of Computer Science, University of Göttingen, and concurrently holds the prestigious Max Planck Fellow position at the Max Planck Institute for Dynamics and Self-Organization. Since 2020 he also serves on the Executive Board of the Campus Institute Data Science in Göttingen. He leads the Neural Data Science research group, comprising 14 PhD students and 2 postdoctoral researchers, focusing on the interface of machine learning and computational neuroscience. His educational background includes a Dr. rer. nat. in Neuroscience (2014) from the Graduate School of Neural and Behavioral Sciences/IMPRS, University of Tübingen, followed by post-doctoral and group-leader positions at the University of Tübingen and the Max Planck Institute for Biological Cybernetics. Research Interests Machine Learning & Deep Learning: developing novel algorithms for representation learning and generative modeling. Computational Neuroscience: large-scale data-driven modeling of visual cortical circuits. Visual Perception: bridging biological vision and computer vision via biologically inspired architectures. His work has produced a steady stream of influential publications (2019-2025) in leading journals such as Nature Communications , Nature , Nature Methods , PLOS Computational Biology , ICLR , NeurIPS , and CVPR . The publications trend toward integrating high-resolution neural recordings with state-of-the-art machine-learning models to uncover principles of sensory processing, neuron-type classification, and behavior. Scientific Awards & Honors Max Planck Fellow, Max Planck Institute for Dynamics and Self-Organization (ongoing) Executive Board Member, Campus Institute Data Science, Göttingen (since 2020) Teaching, Advising & Grants Regularly teaches advanced courses: “Deep Learning for Image Synthesis”, “Current Topics in Deep Learning”, and “Graph Machine Learning”. Supervises 14 current PhD students and 2 postdocs within the Neural Data Science Group. Offers numerous Bachelor’s and Master’s thesis projects, with topics ranging from neuronal morphology clustering to primate vocalization analysis. Leads or co-leads large collaborative consortia with labs in Göttingen, Tübingen, Baylor College of Medicine, and other institutions across the US and Germany. Labs & Teams The Neural Data Science Group operates at the Institute of Computer Science, University of Göttingen, and is tightly integrated with the Max Planck Institute for Dynamics and Self-Organization. The group maintains active collaborations with over a dozen partner laboratories, including groups led by Fabian Sinz, Andreas Tolias, Thomas Euler, Tim Gollisch, and Viola Priesemann, fostering an interdisciplinary environment that spans computer science, physics, biology, and psychology.

Kurt RothermelView profile

Professor

• Distributed Systems
• Time-Sensitive Networking
• Networked Control Systems
• +7 more

Prof. Kurt Rothermel is a faculty member at the University of Stuttgart, specifically affiliated with the Institute for Parallel and Distributed Systems (IPVS) within the Faculty of Computer Science, Electrical Engineering, and Information Technology. His research focuses on distributed systems with particular expertise in time-sensitive networking, networked control systems, and complex event processing. Prof. Rothermel's research interests span multiple areas in distributed computing and networking: Distributed Systems and Networked Control Systems Time-Sensitive Networking and Deterministic Networking Quality of Service (QoS) Management and Optimization Complex Event Processing and Stream Analytics Edge Computing and Real-Time Video Analytics Digital Twin Systems and Proximity-based Services His recent publications (2022-2025) demonstrate a strong focus on time-sensitive networking, with numerous papers addressing scheduling algorithms, conflict graph creation, and latency management for time-triggered communication. There's also significant work on load shedding techniques for resource-constrained environments, particularly for real-time video analytics at the edge. His research increasingly incorporates digital twin systems and explores novel approaches for distributed mobile simulation, as evidenced by his "Persival" framework for handling 3D meshes on AR devices. Prof. Rothermel has made substantial contributions to the field of complex event processing, developing multiple shedding strategies (gspice, hSPICE, pspice) to manage resource constraints while maintaining utility. His work bridges theoretical networking concepts with practical applications in industrial settings, particularly evident in his research on networked control systems and time-sensitive software-defined networks.

Andreas HarthView profile

Professor

• Decentralized information systems
• World Wide Web technologies
• Blockchain environments
• +7 more

Prof. Dr. Andreas Harth holds the Chair of Business Information Systems, especially Technical Information Systems, at Friedrich-Alexander University Erlangen-Nuremberg (FAU), where he has been a faculty member since 2018. He also serves as a department head at the Fraunhofer IIS-SCS in Nuremberg. His academic work spans both theoretical research and practical applications in decentralized information systems, with strong connections to industry through numerous collaborative projects. Harth completed an apprenticeship as a banker before studying computer science. He earned his doctorate from the Digital Enterprise Research Institute at the National University of Ireland, Galway, and completed his habilitation at the Karlsruhe Institute of Technology. His academic journey included teaching and research stays at the universities of Heidelberg, Innsbruck, Stanford, and Southern California, providing him with a global perspective on information systems research. His research focuses on developing methods and technologies for decentralized information systems found in the World Wide Web and blockchain environments, with applications in companies. He investigates data integration using Semantic Web and Linked Data technologies, process modeling languages, and their applications in the Internet of Things, Web of Things, and Industry 4.0 contexts. His work bridges theoretical computer science with practical business applications, particularly in data sovereignty and decentralized architectures. Analysis of his recent publications reveals a strong trend toward Solid protocol applications, knowledge graph technologies, and the integration of large language models with semantic web technologies. His research increasingly focuses on practical implementations in enterprise settings, healthcare data management, and manufacturing systems, demonstrating the real-world applicability of his theoretical work. As a member of FAU's research focus on Digitalization and Innovation, Harth collaborates with strategic partners including the Fraunhofer Institute for Information Systems (IIS) and major German industrial companies. His work contributes significantly to FAU's position as one of Germany's most research-intensive universities, particularly in the fields of business informatics and decentralized systems.

• Bioinformatics
• Computational Biology
• Phylogenetics
• +3 more

Daniel Huson is a Professor of Algorithms in Bioinformatics at the University of Tübingen , affiliated with the Faculty of Science and actively contributing to the Computer Science Department . He has held this position since 2002 and previously served as Senior Staff Scientist at Celera Genomics (1999-2002) and Post-Doc at Princeton University and the University of Pennsylvania (1997-99). Education: PhD in Mathematics, Bielefeld University (1990, summa cum laude) Habilitation in Mathematics, Bielefeld University (1997) Studied Mathematics and Physics, University of Washington (1980-86) Research Interests: Designing algorithms for bioinformatics and computational biology Metagenomic data analysis using tools like MEGAN and SplitsTree Phylogenetic networks and evolutionary modeling Microbiome dynamics and industrial bioproduction optimization Development of interactive software for biological data visualization Exploring autocatalytic reaction networks in early biochemistry Scientific Contributions: Developed MEGAN, a widely used metagenome analysis tool Created SplitsTree for phylogenetic network analysis Published extensively on microbiome analysis, metagenomic binning, and evolutionary relationships Contributed to power-to-gas technology and bioelectrochemical systems Awards & Grants: Royal Society of New Zealand International Leader Fellowship (2020-22) PLOS Computational Biology Research Prize (2017) Technology Transfer Prize of the IHK Reutlingen (2016) Co-organizer of major conferences (GCB, RECOMB, ISMB, etc.) Leadership Roles: Head of Computer Science Department (2011-14) Founding member of Computomics (since 2012) Faculty member of IMPRS 'From Molecules to Organisms' (since 2011)

• Computer Graphics
• Interactive Environments
• Visualization
• +4 more

Prof. Dr. André Hinkenjann is the Founding Director of the Institute for Visual Computing and holds a Research Professorship in Computer Graphics and Interactive Systems at Bonn-Rhein-Sieg University of Applied Sciences. His research spans computer graphics, interactive environments, and visualization, with applications in VR/AR, digital twins, and scientific data analysis. He leads multidisciplinary projects funded by institutions like BMBF and Zukunftsfonds NRW. His research integrates: Computer Graphics : Real-time global illumination, foveated rendering, and GPU optimization Interactive Systems : Haptic interfaces, large-display collaboration, and spatial interaction techniques Applied VR/AR : From trauma therapy to industrial training and cultural heritage preservation Recent publications emphasize mixed-reality interaction, neural rendering, and perceptual optimization, reflecting a consistent focus on bridging theoretical graphics with human-centered applications. His lab frequently contributes to high-impact venues like ACM SIGGRAPH, IEEE VR, and Eurographics. Notable projects under his direction include: PInBiM: Gamified citizen science for museum-based insect research DT4MP: Digital twins for urban/industrial multiphysics simulations GTN: State-wide network advancing game technology in NRW Witality: VR for sensory wine analysis

• Biotechnology
• Process Engineering
• Applied Biosciences
• +2 more

Dr. Klaus Raith serves as a Lecturer in the Department of Applied Biosciences and Process Engineering at Anhalt University of Applied Sciences, where he contributes to teaching and academic activities within this specialized engineering discipline. His position involves delivering instruction in bioscience and process engineering curricula for undergraduate and applied science programs. His research profile centers on interdisciplinary applications at the intersection of biological systems and engineering processes: Biotechnology : Focus on microbial systems and enzymatic processes for industrial applications Process Engineering : Optimization of bioprocessing systems and reaction engineering Applied Biosciences : Integration of biological principles with engineering design for sustainable solutions Environmental Biotechnology : Development of biological treatment systems for waste streams Industrial Bioprocessing : Scale-up methodologies for bioproduct manufacturing Prospective students may contact him directly via institutional email for course-related inquiries or research opportunities within the department's framework. His teaching responsibilities align closely with the department's mission of bridging theoretical bioscience with practical engineering applications in industrial contexts.

• Data Science
• Internet of Things (IoT)
• Visual Analytics
• +10 more

Professor Dirk J. Lehmann is a Professor of Data Science in IoT at Ostfalia University of Applied Sciences, Faculty of Computer Science, where he has been employed since May 2022. He holds significant leadership roles including Deputy Head of the Institute for Information Engineering (since 2024), Research Officer of the Faculty of Computer Science (since 2023), and membership in multiple committees including the Admissions Committee for Digital Technologies and the Digital Technologies Examination Board. Professor Lehmann's extensive academic journey includes: Part-time professorship in Data Science in IoT at Ostfalia University (2020-2022) Senior Specialist for Digitalization, AI, and Visual Analysis at IAV GmbH (2018-2023) Assistant Professor of Visual Data Analysis at Nazarbayev University, Kazakhstan (2017) Visiting professorships at TU Graz, Austria and Universidad Rey Juan Carlos, Spain (2016-2017) Researcher at Otto-von-Guericke University Magdeburg (2009-2017) His research expertise centers on Visual Analytics and Data Science, with particular emphasis on high-dimensional data visualization, categorical data analysis, and IoT applications. Professor Lehmann leads the Data Science in IoT working group, conducting research across three main areas: visual data analysis, distributed data analysis using AI methods, and applied data analysis in geology, climate data, medicine, and industrial processes. His methodological contributions include innovative visualization techniques for complex datasets across multiple domains. Analysis of Professor Lehmann's 15 most recent publications (2017-2025) reveals a consistent focus on advancing visualization techniques for complex data analysis. His work spans categorical data visualization (CatNetVis), biological data analysis (D. Melanogaster research), optimization of star coordinate systems, and interactive exploration methods for large datasets. These publications appear in top venues including IEEE Transactions on Visualization and Computer Graphics and EuroVis, demonstrating both theoretical rigor and practical application across diverse domains from healthcare to environmental science. As an educator, Professor Lehmann teaches a comprehensive range of courses from foundational mathematics to advanced machine learning and visualization techniques. He actively supervises student projects and theses, emphasizing clear project definitions with measurable acceptance criteria. His international collaborations span institutions in Israel, Saudi Arabia, China, Austria, and Spain, reflecting a global research perspective that bridges academic theory with industry applications, particularly through his previous role at IAV GmbH, a Volkswagen subsidiary.

• Environmental Engineering
• Waste Management
• Biomass Utilization
• +6 more

Professor Matthias Kleinke is a Professor of Environmental Engineering at Rhine-Waal University of Applied Sciences within the Faculty of Life Sciences. Appointed in 2011, he served as Dean of the Faculty from 2013 to 2017 and was recently appointed Adjunct Professor at Nelson Mandela African Institution of Science and Technology (NM-AIST) in Tanzania in 2025. His career spans academic, research, and practical industry experience in environmental management. Professor Kleinke's research interests focus on environmental engineering, waste management, biomass utilization, and circular economy principles. His work consistently emphasizes practical applications and implementation-oriented solutions, bridging theoretical knowledge with real-world environmental challenges. He has supervised numerous theses across three main areas: Environment, Agriculture, and Safety, with students working on topics ranging from waste management optimization to renewable energy systems and workplace safety. His publication record shows a strong focus on contemporary environmental challenges, with recent work examining nutrient circularity, urban waste valorization, bioeconomy transitions, and sustainable agricultural technologies. The most recent publications (2023-2024) demonstrate ongoing research activity in circular economy applications, particularly in food systems and waste management. Professor Kleinke maintains extensive international collaborations, having taught as a visiting lecturer in multiple countries across Africa, Asia, and Europe. His work demonstrates a commitment to both regional environmental challenges in Germany and global sustainability issues, particularly through his growing engagement with African institutions and researchers. His advising approach emphasizes practical, industry-relevant research, with students frequently working on projects connected to real companies and environmental challenges. This applied focus creates valuable opportunities for students to gain hands-on experience while contributing to meaningful environmental solutions.

Johannes PfauView profile

Researcher

• FPGA Architecture
• Reconfigurable Computing
• Digital Beamforming
• +3 more

Dr. Johannes Pfau serves as a Scientific Assistant at the Institute for Information Processing Technology (ITIV) within Karlsruhe Institute of Technology (KIT), working in Prof. Becker's research group. His position combines postdoctoral research in advanced FPGA architectures with teaching responsibilities including System-on-Chip internships and academic advising for specialized engineering tracks. Education: Doctorate (Dissertation) in Electrical Engineering and Information Technology, Karlsruhe Institute of Technology, 2024 Research Interests: Pfau's work centers on reconfigurable computing with three interconnected pillars: (1) Next-generation FPGA architectures using emerging technologies like RFETs that require fundamental toolchain redesigns; (2) Digital beamforming systems for satellite Earth observation that replace analog processing with FPGA-based solutions to enable on-orbit data compression; and (3) High-throughput data acquisition systems for 6G prototyping handling multi-100Gbps streams through RFSoC platforms. His research bridges semiconductor physics, hardware architecture, and practical applications in communications and remote sensing. Publication Trends: Pfau's 15 most recent publications (2021-2024) reveal a strong focus on practical FPGA implementations addressing real-world constraints. His work increasingly integrates power management (7 papers), 6G infrastructure (5 papers), and novel semiconductor technologies (4 papers), with a clear trajectory toward hardware solutions for satellite communications and next-generation wireless systems. The research demonstrates consistent progression from architectural innovations (RFET, V-FPGAs) to applied systems (beamforming, 6G testbeds). Advising and Mentorship: Pfau maintains an active student supervision portfolio with documented guidance of 7+ Bachelor's and Master's theses since 2021. His projects emphasize hands-on hardware development, spanning power management techniques, beamforming filter design, and prosthetic control systems. The academic advising role for specializations 13 and 21 positions him at the intersection of computer science and electrical engineering education. Research Context: As a core member of Prof. Becker's group at ITIV, Pfau contributes to KIT's leadership in reconfigurable systems research. The group maintains strong industry connections through 6G initiatives and satellite technology development, with Pfau's work directly supporting German and European efforts in secure communications infrastructure and Earth observation systems.

Matthias MüllerView profile

Professor

• Cognitive Neuroscience
• Attention Research
• Visual Perception
• +4 more

Matthias Müller is a Professor and Chair of General Psychology and Methodology at the University of Leipzig, where he has held his position since April 2003. He is affiliated with the Faculty of Biosciences, Pharmacy and Psychology, and has previously served as Dean (2008-2011) and Vice Dean (2005-2008) of this faculty. He also served as Head of the Psychological Institute and board member of the Center for Cognitive Neuroscience at the University of Leipzig. University: University of Leipzig Faculty: Faculty of Biosciences, Pharmacy and Psychology Department: Department of General Psychology and Methodology Position: Chair/Professor since 2003 Previous leadership roles: Dean (2008-2011), Vice Dean (2005-2008) Professor Müller's research focuses on selective attention within and between sensory modalities, with particular emphasis on how the human perceptual system processes incomplete yet extensive streams of sensory information. His work primarily employs EEG experiments to investigate attention mechanisms. His current research interests include neural dynamics of attentional resource allocation, alpha-band fluctuations in attention processes, visual search performance, and the interaction between visuospatial and feature-based attention. Analysis of his recent publications reveals a strong focus on the neural mechanisms underlying attention processes, particularly using EEG methodology. His work consistently examines how attention modulates neural activity in the visual cortex, with recent studies investigating emotional scene processing, spatial attention mechanisms, visual search paradigms, and the relationship between motor activity and visual processing. Professor Müller has received multiple research grants from the German Research Foundation (DFG), with current projects running through 2027. His research portfolio includes studies on signal suppression hypothesis, neural dynamics of distraction, temporal neural dynamics of amplification and suppression, and attention shifting mechanisms. As an educator, Professor Müller teaches General Psychology courses focusing on attention, learning, memory, emotion, and motivation, with special emphasis on cognitive neuroscience perspectives. His teaching methodology incorporates EEG, fMRI, PET, and brain stimulation techniques.

• Climate Modeling
• Hydrological Cycle
• Land-Atmosphere Interactions
• +6 more

Lai-yung Ruby Leung is a Battelle Fellow at Pacific Northwest National Laboratory (PNNL) working in Earth Systems Analysis & Modeling. She serves as Chief Scientist of the Energy Exascale Earth System Model (E3SM) supported by the U.S. Department of Energy, leading major efforts to develop state-of-the-art capabilities for modeling human-Earth system processes on high-performance computers. Dr. Leung's research broadly spans climate and hydrological cycle modeling with expertise in land-atmosphere interactions, orographic processes, monsoon climate, and climate extremes. Dr. Leung earned her educational credentials from prestigious institutions: Ph.D., Atmospheric Science, Texas A&M University M.S., Atmospheric Science, Texas A&M University B.S. (Honors), Physics & Statistics, Chinese University of Hong Kong Her research interests focus on regional and global climate modeling , land-atmosphere interactions , and the regional hydrologic cycle . She investigates orographic precipitation mechanisms, climate extremes, climate variability and change, and aerosol-cloud interactions. Her work integrates advanced modeling techniques with observational data to understand complex Earth system processes, with research featured in Science , Popular Science , Wall Street Journal , and National Public Radio . Dr. Leung has published over 500 peer-reviewed papers and serves as an editor for the American Meteorological Society's Journal of Hydrometeorology . Analysis of Dr. Leung's recent publications reveals her leadership in developing and applying the Energy Exascale Earth System Model (E3SM), with significant contributions to understanding mesoscale convective systems, soil moisture dynamics, urban hydrology, and climate extremes. Her work demonstrates increasing integration of machine learning techniques with traditional climate modeling approaches, particularly in model evaluation frameworks and high-resolution simulations. She maintains strong focus on practical applications of climate science for understanding water resources, extreme weather events, and climate change impacts. Dr. Leung's scientific recognition includes: Election to the National Academy of Engineering (NAE) Election to the Washington State Academy of Sciences (WSAS) Fellow of the American Geophysical Union (AGU) Fellow of the American Meteorological Society (AMS) Fellow of the American Association for the Advancement of Science (AAAS) AMS Hydrologic Sciences Medal (2022) U.S. Department of Energy Office of Science Distinguished Scientist Fellow (2021) Reuter's Hot List of top 1,000 most influential climate scientists (2021) AGU Jacob Bjerknes Lecture (2020) AGU Bert Bolin Global Environmental Change Award (2019) As Chief Scientist of E3SM, Dr. Leung leads major research initiatives funded by the Department of Energy and has organized key workshops sponsored by DOE, NSF, NOAA, and NASA. She has served on numerous advisory panels and National Academies committees that define future priorities in Digital Twin, AI/ML, climate modeling, hydroclimate, and water cycle research. Her professional service includes membership on the Board on Atmospheric Sciences and Climate of the National Academies, council membership with the American Meteorological Society, and editorial roles for prominent journals. Dr. Leung directs research within PNNL's Earth Systems Analysis & Modeling group, collaborating with national and international climate research teams. She leads efforts to advance the Energy Exascale Earth System Model (E3SM), which represents cutting-edge capabilities in modeling human-Earth system processes. Her work connects with multiple PNNL research areas including atmospheric science, global change, and coastal science, contributing to the laboratory's mission of addressing complex environmental challenges through scientific innovation.

• Freshwater Ecology
• River Biogeochemistry
• Carbon Cycling in Aquatic Ecosystems
• +4 more

Gabriel Singer is a Professor of Ecology at the University of Innsbruck, Austria, holding this position since December 2019. His research spans multiple European river systems with significant collaborations through past affiliations at the University of Vienna and Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB) in Berlin. Professor Singer's research focuses on river network biogeochemistry, particularly carbon cycling dynamics in freshwater ecosystems. His work examines how climate change-induced drying, fragmentation, and human alterations impact greenhouse gas emissions, organic matter processing, and biodiversity. Key study systems include the Vjosa River in Albania (Europe's last wild river) and European intermittent streams, where he investigates microbial reworking of dissolved organic matter, leaf-litter decomposition across aquatic-terrestrial interfaces, and geodiversity controls on algal communities. Analysis of his 2021-2025 publication record reveals a strategic shift toward climate change impacts on river networks, with increasing emphasis on policy-relevant outcomes like the EU Nature Restoration Law. His work consistently bridges fundamental biogeochemistry with applied river management, maintaining strong output in high-impact journals including Limnology and Oceanography, Nature Communications, and Biogeosciences. As a full Professor, Singer leads research projects such as DRYvER (Securing Biodiversity in Drying River Networks) and mentors students through field-intensive studies. His international collaborations span 15+ institutions across 10 European countries, reflecting his role in pan-European freshwater research networks. Professor Singer's team operates at the frontier of river network science, combining cutting-edge sensor technologies with traditional field ecology to address urgent questions about climate resilience in freshwater ecosystems. Current work focuses on scaling experimental findings to river network levels and translating biogeochemical insights into river restoration frameworks.

• Sustainable Materials
• Biomass Processing
• Green Chemistry
• +2 more

Dr. Topias Kilpinen is a Postdoctoral Researcher in the Department of Sustainable and Bio-inspired Materials at the Max Planck Institute of Colloids and Interfaces (Potsdam, Germany), focusing on sustainable hemicellulose extraction from biomass under Prof. Silvia Vignolini's leadership since 2025. His academic foundation includes: Bachelor of Science in Chemical Engineering, Aalto University (2016) Master of Science in Chemical Engineering, Aalto University (2019) PhD in Natural Sciences (Bioproduction Technology), Aalto University (2024) Dr. Kilpinen's research pioneers environmentally friendly hemicellulose isolation techniques, targeting the 25% biomass fraction currently wasted due to unsustainable extraction processes. His work develops gas-solid hydrolysis systems using gaseous hydrogen chloride at low pressure to achieve >90% sugar yields, while creating controllable polymeric hemicellulose streams for renewable material applications. This bridges green chemistry and advanced materials science to enable circular bioeconomy solutions. As a postdoctoral researcher, he operates within Prof. Vignolini's research ecosystem without independent student supervision or principal investigator grant responsibilities. His ORCID profile (https://orcid.org/0009-0005-4379-7907) documents ongoing scholarly contributions to sustainable materials science.