Jonathan T. Barron is a Researcher at Google DeepMind in San Francisco, specializing in Computer Vision , Neural Rendering , and 3D Scene Reconstruction . He earned his PhD at UC Berkeley under Jitendra Malik and has pioneered advancements in NeRF (Neural Radiance Fields) and diffusion-based 3D generation. Research Interests : Computer Vision, Deep Learning, Generative AI, Image Processing, and 3D Reconstruction via Radiance Fields. His work includes Bolt3D for rapid 3D scene generation, CAT3D/CAT4D for text-to-3D/4D, and Zip-NeRF for anti-aliased radiance fields. He has also developed real-time rendering frameworks like SMERF and NeRF-Casting for reflections. Scientific awards: PAMI Young Researcher Award He has served as Area Chair for CVPR, ICCV, and NeurIPS, and his research is widely adopted in applications like Google's Lens Blur , Portrait Mode , and Jump VR .
Nils Ole Tippenhauer is a faculty member at the CISPA Helmholtz Center for Information Security , leading the SCy-Phy research group . His academic journey includes an Assistant Professorship at the Singapore University of Technology and Design (SUTD) (2014–2018), a PhD in Computer Science from ETH Zurich (2012), and a Diploma in Computer Engineering from Hamburg University of Technology (2007). He also holds an exchange study year at the University of Waterloo (2004–2005) supported by a DAAD scholarship. Research Interests focus on practical systems security , particularly Security of Cyber-Physical Systems Industrial Control Systems (ICS) and Industrial IoT (IIoT) Physical-Layer Security and Wireless Security Privacy-Preserving Technologies (e.g., DP3T project) Embedded Systems Security Threat Detection & Defenses His work integrates both theoretical and applied approaches, addressing vulnerabilities in critical infrastructures like water systems and power grids. Recent Publications highlight trends in Anomaly detection evasion in industrial networks Microarchitectural side-channel defenses Localization techniques in cellular networks Security analysis of ICS protocols Data-driven vulnerability assessments for robotics Cyber-physical simulation for infrastructure security Scientific Awards include Best paper at DIMVA'23 Distinguished Paper at ACSAC 2022 Best paper at CPSIOTSEC 2022 Best paper at CPSS 2017 K-H Ditze Award for diploma thesis (2007) SG Mark Institution award (2016) Runner-Up at smart energy hackathon (2013) Advising and Grants feature PhD defenses of Daniele Antonioli and Hamid Reza Ghaeini (2022), co-organizing conferences like WiSec and CPSS , and leading projects such as the National Science Experiment (NSE) with 50,000 mobile sensors in Singapore. He also contributed to the DP3T project for privacy-preserving contact tracing. Labs and Teams include the SCy-Phy research group at CISPA and the development of testbeds like SWaT (Secure Water Treatment), WADI (Water Distribution), and EPIC (Electric Power and Industrial Control) at SUTD. These platforms enable hands-on security research in realistic industrial environments.
Günter Rote is a Professor in the Department of Computer Science at Freie Universität Berlin, specifically within the Theoretical Computer Science group (Arbeitsgruppe Theoretische Informatik). He holds a formal academic title of Professor Dr. and is affiliated with the Faculty of Mathematics and Computer Science. His research focuses on theoretical computer science, computational geometry, algorithms, and discrete mathematics. Key research interests include geometric algorithms, optimization problems (e.g., shortest paths, traveling salesman problems), and algorithm design for parallel computing systems. His work spans topics such as systolic arrays, convex hulls, and combinatorial optimization. Rote’s contributions include foundational studies on computational geometry problems, algorithmic complexity, and practical applications in energy equity and infrastructure design. Publications highlight contributions to solving extremal equations, polygon transformations, and the quadratic assignment problem. He has been active in academic leadership, mentoring students, and contributing to computational science communities. His email is rote@inf.fu-berlin.de, and his office is located at Takustraße 9 in Berlin.
Prof. Dr. Fabian Gieseke is a Professor and Chair of Machine Learning and Data Engineering at the University of Münster. He holds a PhD in Computer Science from Carl von Ossietzky University of Oldenburg and a dual degree in Mathematics and Computer Science from the University of Münster. His research focuses on Machine Learning, High-Performance Computing, and their applications in Geosciences, Smart Cities, and Astrophysics. Education: PhD in Computer Science (2012), Carl von Ossietzky University of Oldenburg University studies in Mathematics and Computer Science (2006–2011), University of Münster Research Interests: Data Mining and Machine Learning High-Performance Computing & Distributed Systems Deep Learning Applications in Environmental Science and Astrophysics Geospatial Data Analysis using Satellite Imagery Publications Trends: His recent work emphasizes large-scale environmental monitoring via deep learning, including canopy height estimation, forest biomass prediction, and national-scale tree counting. He also explores interactive systems for geospatial data retrieval and optimization of machine learning models for resource-constrained environments. Advising & Grants: Supervised over 30 theses on topics like satellite image analysis, deep learning on microcontrollers, and data marketplaces for smart grids. Active in securing grants for interdisciplinary projects combining AI with Earth observation. Labs/Teams: Leads the Machine Learning and Data Engineering group at the University of Münster, focusing on scalable AI solutions for real-world challenges in science and industry.
Antonello Monti is a Professor and Director of the Institute for Automation of Complex Power Systems at RWTH Aachen University. His research focuses on modern power systems, including smart grid technologies, hybrid AC-DC grids, and quantum computing applications in energy systems. Recent publications demonstrate innovations in grid resilience, EV charging optimization, quantum-assisted power system planning, and advanced simulation techniques. His team develops open-source tools like JuliaGrid for power system analysis and validates concepts through real-time testing platforms. Research addresses energy transition challenges including renewable integration, grid modernization, cyber-physical security, and next-generation optimization methods combining quantum computing with traditional power engineering approaches.
Yuanbo Xiangli is a postdoctoral researcher at Cornell University , advised by Prof. Noah Snavely. Previously, he obtained his Ph.D. from the Multimedia Lab in the Department of Information Engineering at the Chinese University of Hong Kong (CUHK) , supervised by Prof. Dahua Lin. His research focuses on 3D computer vision and deep generative modeling for urban scene reconstruction. 3D scene reconstruction from sparse images Neural rendering and Gaussian splatting Deep generative modeling for urban environments Multi-source geospatial data processing City-scale modeling and synthetic datasets His recent work includes advanced NeRF extensions (BungeeNeRF, GridNeRF), Gaussian splatting enhancements (GSDF, Scaffold-GS), and urban scene datasets (MatrixCity, OmniCity). A pioneer in combining classical vision techniques with modern deep learning approaches. ICLR 2020 Spotlight Award Collaborates with leading researchers in photorealistic rendering, including Noah Snavely and Dahua Lin. Develops systems enabling efficient 3D reconstruction from diverse data sources like satellite imagery and street-level panoramas.
Prof. Dr. Holger Kantz serves as Head of the research unit "Nonlinear Dynamics and Time Series analysis" at the Max Planck Institute for the Physics of Complex Systems in Dresden, Germany. He also holds an Adjunct Professorship (Honorprofessor) in Statistical Physics at the Institute of Theoretical Physics within the Department of Physics at the Technical University Dresden. Dr. Kantz's research spans multiple disciplines within nonlinear dynamics and statistical physics. His work focuses on time series analysis, nonlinear dynamics, stochastic processes, and complex systems. He has made significant contributions to understanding anomalous diffusion, extreme events prediction, and the statistical properties of chaotic systems. His research has applications in atmospheric science, climate modeling, power grid dynamics, and biological systems. Analysis of Dr. Kantz's recent publications reveals a strong interdisciplinary approach connecting statistical physics with climate science, energy systems, and scientometrics. His work demonstrates sophisticated applications of stochastic modeling to real-world complex systems, with particular attention to anomalous diffusion processes, extreme events, and predictability limits in chaotic systems. The publications show increasing methodological sophistication in handling nonstationary time series and developing predictive models for rare events. Dr. Kantz leads a research group focused on nonlinear dynamics and time series analysis at the Max Planck Institute. His work has significant implications for understanding and predicting complex phenomena across multiple scientific domains, from climate dynamics to power grid stability, with practical applications in risk assessment and system reliability.
Prof. Dr.-Ing. Weihan Li is a Junior Professor at RWTH Aachen University, specializing in Artificial Intelligence and Digitalization for Batteries. He is affiliated with the Institute for Power Electronics and Electrical Drives (ISEA) and the Center for Ageing, Reliability, and Lifetime Prediction of Electrochemical and Power Electronic Systems (CARL). His research bridges informatics, electrochemistry, and power electronics to advance battery technology through AI. B.Sc. in Automotive Engineering (Tongji University, 2014) M.Sc. in Automotive Engineering and Transport (RWTH Aachen, 2017) Ph.D. in Electrical Engineering and Information Technology (RWTH Aachen, 2021, summa cum laude) Prof. Li’s research focuses on AI-driven battery modeling, diagnostics, and optimization. Key areas include digital twin technology, electrochemical parameterization, and lifetime prediction using field data. He explores multi-scale kinetic processes, thermal management, and mechanical-electrochemical coupling effects in battery systems. The articles listed reflect his leadership in AI-powered battery analytics, spanning degradation prediction, fast charging, failure mode analysis, and grid-scale storage. His work emphasizes both theoretical innovation (e.g., diffusion models, physics-informed neural networks) and practical applications (e.g., second-life battery screening, automotive integration). Clarivate Highly Cited Researcher 2024 BMBF BattFutur Research Group (€2M+) German Thesis Award (Körber Foundation) Reichart Prize vgbe Innovation Prize Battery Young Research Award Umbrella Award RWTH Innovation Award Prof. Li leads an interdisciplinary research group with over €6 million in grants from BMBF, BMWK, BMDV, European Commission, and industry partners. His teams focus on battery informatics, AI-driven diagnostics, and digitalization of testing processes at CARL and ISEA.
Prof. Dr. Biliana Yontcheva is Professor of Economics at the University of Hamburg's Faculty of Business, Economics and Social Sciences, specializing in Health Economics and Empirical Methods. Her research explores market outcomes through spatial econometrics, price transmission dynamics, and competition analysis across diverse sectors including healthcare, gasoline markets, and professional services. Focus on empirical modeling of market structures Expertise in spatial competition and entry models Key contributions to understanding asymmetric cost pass-through Analyzes consumer information effects on pricing Recent publications examine market delineation methodologies , vertical integration impacts , and income inequality-product variety relationships . Collaborates with researchers across Europe on topics like transition economy dynamics and regulatory frameworks. The team includes academic assistant Birte Stadtlich at the Economics Department.
Prof. Dr. Matthias Weidlich is a faculty member at Humboldt University of Berlin within the Institute of Computer Science under the Faculty of Mathematics and Natural Sciences . His research focuses on Process Mining , Complex Event Processing , and Data Privacy with applications in Business Process Management and Scientific Workflows . Research Interests: Business Process Management and Process Mining Complex Event Processing and Stream Data Analysis Data Privacy and Security in Process Systems Scientific Workflow Systems and User Behavior Heterogeneous Network Embeddings Algorithm Design and Optimization Recent Publications (2023-2025) demonstrate expertise in: Efficient stream processing techniques Privacy-preserving process mining frameworks Scientific workflow analysis tools Graph neural network applications Multi-modal data integration Adaptive querying systems Contact: Office: Unter den Linden 6, 10099 Berlin Phone: 030 2093-41277 Email: matthias.weidlich@hu-berlin.de Web: hu.berlin/data
Kevin Schneider is a Laboratory Fellow at Pacific Northwest National Laboratory (PNNL), a Research Professor at Washington State University (WSU), and an Affiliate Associate Professor at the University of Washington. As manager of PNNL's Office of Electricity Subsector, he leads business development, client relations, and strategic investments in R&D for the grid sector, overseeing portfolios in component design, system modeling, hierarchical controls, secure communications, and energy storage. Dr. Schneider is internationally recognized for his expertise in power system analysis, planning, and operations. His research focuses on improving grid reliability and system flexibility by harnessing advanced grid concepts at the edge of power systems, including microgrids, energy storage, electric vehicles, distributed energy resources, and smart home appliances. At WSU, he is a researcher for the WSU and PNNL Advanced Grid Institute (AGI), implementing layered control architectures to enhance operational flexibility of critical power systems. His work spans multiple disciplines within electrical engineering and power systems, with strong emphasis on practical applications for grid modernization, particularly in grid resilience, microgrid operations, and integration of distributed energy resources. Dr. Schneider is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), where he has served in multiple technical leadership roles. His scientific contributions have been recognized with significant awards: Presidential Early Career Award for Scientists and Engineers (PCASE), 2019 Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Dr. Schneider earned his B.S. in Physics and M.S. and Ph.D. in Electrical Engineering from the University of Washington. He is a licensed Professional Engineer in Washington State. His research has resulted in numerous patents related to power grid technologies, including several focused on voltage and frequency stability of distribution systems. His work has substantial implications for grid modernization efforts and the development of more resilient power systems in the face of climate change and other challenges.
Prof. Dr. Barbara Praetorius is a leading scholar in sustainability economics at HTW Berlin since 2017. She co-chaired Germany's Coal Commission ("Kommission Wachstum, Strukturwandel und Beschäftigung") and serves on advisory boards for Berliner Wasserbetriebe and VERBUND AG. Her work bridges climate policy, energy economics, and social equity, with a focus on Germany and the Global South. Research Themes: Climate economics, decarbonization pathways, renewable energy integration, and sustainable development in emerging economies. Policy Influence: Regular contributor to national climate policy debates, particularly on carbon pricing and coal phase-out strategies. Academic Roles: Professor at HTW Berlin's Department 3: Economics and Law since 2017, previously Deputy Director of Agora Energiewende (2014-2017). Recent Publications emphasize plug-in solar systems' socio-economic impacts, just coal transitions in Hesse, and ecological industrial policy frameworks. Her 2024 work on energy market transformation highlights the need for policy innovation and market redesign. Scientific Recognition : Ranked among Germany's most influential female economists by FAZ Active in EU energy policy advisory roles Recipient of BMBF research funding for international projects
Prof. Dr. Christian Plessl is a W3 Professor of High-Performance Computing at the Institute of Computer Science, University of Paderborn. He leads the Paderborn Center for Parallel Computing (PC²), a national HPC center within the NHR alliance. His roles include Director of PC², Board Member of the NHR association, and member of the Sonderforschungsbereich 901. Education: PhD (Dr. sc. ETH) in Computer Engineering, ETH Zürich (2006) MSc in Electrical Engineering, ETH Zürich (2001) Postdoc at ETH Zürich (2007–2011) Research Interests: Architecture and tools for high-performance parallel and reconfigurable computing, FPGA acceleration, quantum chemistry, scientific computing, adaptive systems, and energy-efficient HPC solutions. Key projects include EKI-App (FPGA-based neural networks), FPGA4XPCS (X-ray spectroscopy), and HighPerMeshes (unstructured grid frameworks). Publications: Over 100 peer-reviewed works, focusing on FPGA acceleration, HPC frameworks, and quantum computing. Recent trends emphasize energy-efficient neural networks, FPGA-based quantum computing, and scalable HPC algorithms. Awards: Best Paper Awards at HEART 2023, ReConFig 2012/2014 Paderborn University Research Awards (2018, 2009) SEW-EURODRIVE Student Award (2001) Grants & Projects: Principal investigator in DFG, BMBF, and EU-funded projects. Collaborates with AMD/Xilinx, Intel/Altera, and Fujitsu. Leads initiatives like PerficienCC (custom computing) and HighPerMeshes. Labs/Teams: Directs the High-Performance Computing group at PC², focusing on FPGA supercomputing and HPC infrastructure. Active in the NHR alliance for national HPC coordination.
Prof. Dr. Tobias Brandt serves as a Full Professor and Chair of Digital Innovation and the Public Sector at the University of Münster's School of Business and Economics. His academic journey includes roles as Assistant Professor at Rotterdam School of Management (2016-2021) and Research Assistant at the University of Freiburg (2011-2015). He co-founded Geospin GmbH in 2016 and holds memberships in VHB, INFORMS, and AIS. Research Interests: Brandt focuses on digital innovation in public sectors, sustainable urban systems, e-government, and platform ecosystems. His work bridges information systems and operational research to address challenges in mobility, energy, and public service delivery. Recent projects include developing tools for sustainable urban planning, digital platforms for elderly care, and leveraging AI for crisis management. Notable Projects: Current initiatives include the PIONEER II Master's program on public innovation, SMARD-Gov (LLMs for government decision-making), and comuneo (digital sustainability management platform). Completed projects include INNO4S (integrating sustainability in business education) and studies on pandemic-driven digitalization in public administration. Awards: RSM Teaching Award (2020), Daniel H. Wagner Prize (2020), IBM Faculty Award (2016). Grants: €5M+ secured from EU Erasmus+, DFG, and German Federal Ministry of Research. Labs/Teams: Leads the Chair of Digital Innovation & Public Sector, collaborating with ERCIS (European Research Center for Information Systems). Active in GovTech and digital sustainability initiatives.
Dr. Christoph Trinkl serves as Head of the Institute of new Energy Systems (InES) at Technische Hochschule Ingolstadt, a position he has held since 2008. His work focuses on renewable energy technologies and sustainable energy systems development, with particular expertise in solar thermal applications and system integration. His research interests include: Green Technologies Renewable Energy Technologies Solar Energy Engineering Solar Heating and Cooling Renewable Energy Systems for Industrial, Domestic and Mobility Applications Technology Transfer and Network Management Dr. Trinkl's educational background includes a PhD in Engineering from De Montfort University Leicester's Institute of Energy and Sustainable Development (UK) in 2007, following his work as a researcher at Technische Hochschule Ingolstadt from 2001-2007. His degree course in Mechanical Engineering and Business (1997-2001) provided the foundation for his interdisciplinary approach to energy systems. His recent publications demonstrate a strong focus on practical applications of renewable energy technologies, particularly in solar thermal systems, heat pump integration, and district heating networks. His research spans from fundamental engineering analysis of collector technologies to large-scale system integration and optimization, with increasing emphasis on real-world implementation challenges and optimization techniques including AI-driven approaches. Dr. Trinkl's extensive publication record spanning over two decades shows an evolution from fundamental collector technology research to broader energy system integration, addressing both technical and practical implementation considerations across diverse contexts from industrial applications to rural energy access solutions.
