جست‌وجوی استاد و پژوهشگر

David Bakerمشاهده پروفایل

استاد

• Computational Biology
• Protein Design
• Protein Structure Prediction
• +۷ مورد دیگر

David Baker is a Professor in the Department of Biochemistry at the University of Washington School of Medicine , an investigator with the Howard Hughes Medical Institute , and adjunct faculty in genome sciences, bioengineering, chemical engineering, computer science, and physics. His pioneering work in computational biology has earned him the 2024 Nobel Prize in Chemistry and numerous other accolades. Education: Bachelor of Arts in Biology, Harvard University (1984) Doctor of Philosophy in Biochemistry, University of California, Berkeley (1989) Postdoctoral training in Biophysics, University of California, San Francisco (1993) David's research focuses on ab initio protein structure prediction and design via tools like Rosetta , RoseTTAFold , and the citizen science game Foldit . His group has designed Top7 , the first artificial protein with a novel fold, and advanced AI applications in structural biology. The 15 most recent articles reflect trends in computational methods for protein modeling, AI integration , and crowdsourced science . These works span ab initio prediction , density-guided optimization , and gamified approaches to structure determination. Scientific Awards: Nobel Prize in Chemistry (2024) Breakthrough Prize in Life Sciences (2021) Wiley Prize (2022) BBVA Foundation Frontiers of Knowledge Award (2022) Overton Prize (2002) Feynman Prize in Nanotechnology (2004) David has advised PhD students like Richard Bonneau and mentored postdocs including Brian Kuhlman, Tanja Kortemme, and Jens Meiler. His Institute for Protein Design has received over $11 million from Open Philanthropy (2017) and $3 million (2021). He co-founded biotech companies such as Icosavax and Sana Biotechnology.

Andrés Bruhnمشاهده پروفایل

استاد

• Computer Vision
• Optical Flow
• Scene Flow
• +۵ مورد دیگر

Andrés Bruhn is a Professor for Intelligent Systems and Dean of Computer Science Studies at the University of Stuttgart, where he leads research in the Institute for Visualization and Interactive Systems (VIS). His academic career spans over a decade with significant contributions to computer vision, particularly in optical flow, scene flow, and motion estimation. As Dean of Studies, he oversees academic programs while maintaining an active research agenda focused on cutting-edge computer vision problems. Bruhn's research interests center around computer vision with emphasis on optical flow estimation, scene flow, motion analysis, and adversarial machine learning. His work bridges theoretical foundations with practical applications, developing algorithms that address real-world challenges in motion estimation, image processing, and visual understanding. His research group has pioneered approaches that combine variational methods with deep learning, creating robust systems for motion analysis that can withstand adversarial attacks and challenging environmental conditions. The publication record demonstrates a strong focus on advancing the state-of-the-art in motion estimation, with recent work exploring adversarial attacks on optical flow systems, high-resolution datasets for benchmarking, and multi-frame fusion techniques. His research shows consistent innovation, moving from traditional variational methods to modern deep learning approaches while maintaining mathematical rigor. The work spans both theoretical contributions and practical implementations with real-world applicability. Bruhn has mentored numerous researchers who appear as first authors on publications, including Jenny Schmalfuss, Lukas Mehl, and Azin Jahedi, indicating his commitment to developing the next generation of computer vision researchers. His leadership role as Dean of Studies demonstrates institutional recognition of his expertise and administrative capabilities.

Holger Schwarzمشاهده پروفایل

دانشیار

• Data Management
• Database Systems
• Data Lakes and Lakehouses
• +۶ مورد دیگر

Holger Schwarz is an Associate Professor (Apl. Professor) at the Institute for Parallel and Distributed Systems (IPVS) within the Faculty of Computer Science, Electrical Engineering and Information Technology at the University of Stuttgart. He serves as Head of the Infrastructure Department and is actively involved in research and teaching in the areas of data management, database systems, and data analytics. Professor Schwarz earned his doctorate (Dr. rer. nat.) from the University of Stuttgart in 2003 with a dissertation on "Integration of Data Mining and Online Analytical Processing." He later completed his habilitation (Dr. rer. nat. habil.), qualifying him as a university professor in Germany. His primary research interests focus on data management systems , particularly in the domains of data lakes, lakehouses, enterprise data platforms, and metadata management. Professor Schwarz investigates how to design efficient and scalable data architectures that support modern analytical workloads while addressing challenges in data integration, governance, and democratization. His work bridges theoretical database concepts with practical industrial applications, as evidenced by numerous collaborations with industry partners. Professor Schwarz's recent publications demonstrate a clear trend toward enterprise data management solutions, particularly focusing on data lakehouse architectures, enterprise data marketplaces, and advanced clustering techniques. His research shows a consistent pattern of addressing real-world data management challenges through innovative architectural patterns and algorithmic improvements, with strong emphasis on practical industrial implementation. Professor Schwarz supervises numerous research projects including MetaMan (metadata management in complex data landscapes), DLArchitecture (design of comprehensive data lake architecture), INTERACT (interactive rapid analytic concepts), and VALID-Partition (improving prediction quality using domain knowledge). He also coordinates the University of Stuttgart's projects within the Software Campus initiative and serves as Managing Director of the Technology Partnership Lab and as a Member of the Board of Directors of the Industrial Data Lab. His teaching portfolio includes courses on Advanced Information Management, Database Systems, and Data Science projects across multiple semesters, demonstrating his commitment to educating the next generation of data management professionals.

Zhongxin Liuمشاهده پروفایل

استادیار

• Intelligent Software Engineering (AI4SE)
• Code Intelligence
• Vulnerability Detection
• +۵ مورد دیگر

Zhongxin Liu is an Assistant Professor at the College of Computer Science and Technology , Zhejiang University , China. He earned his Ph.D. from the same institution in 2021. His research focuses on Intelligent Software Engineering (AI4SE) , leveraging software "big data" to improve code understanding, generation, and security through machine learning techniques. Published in top-tier venues: TSE, TOSEM, ICSE, FSE, ASE, ISSTA Active in academic service: Reviewer for TSE, TOSEM, ASEJ, etc. Visiting Professor at University of Stuttgart (2024-2025) His recent work explores Large Language Models (LLMs) for code intelligence, security hardening, and vulnerability detection. Papers emphasize cross-domain applications, zero-shot learning, and API/code dependency analysis. Scientific awards include: ACM SIGSOFT Distinguished Paper Awards (ASE 2018, 2019, 2020; ISSTA 2025) Zhejiang University Qizhen Scholar (2021) CCF TCSE Doctoral Dissertation Award (2023) Recruiting undergraduate interns, graduate students (MS/Ph.D.), and postdocs for code intelligence research. Contact: liu_zx@zju.edu.cn .

• Soil Science
• Geomorphology
• Geoecology
• +۵ مورد دیگر

Thomas Scholten is Professor of Soil Science and Geomorphology at the Department of Geoscience, Faculty of Science, Eberhard Karls University Tübingen. He has been director of the Institute of Geography at Tübingen University since 2006 and has held various leadership roles including President of the German Soil Science Society (2012-2015) and council member of the European Society for Soil Conservation since 2004. In 2016, he was elected as a member of German National Academy of Science and Engineering (acatech). Since 2017, he has been co-speaker of the Collaborative Research Center (SFB 1070) 'ResourceCultures' and since 2019, he has been a principal investigator in the Cluster of Excellence 'Machine Learning - New Perspectives for Science' at Tübingen University. Chair of Soil Science and Geomorphology (full professor) at Eberhard Karls University Tübingen (2005-present) Director of the Institute of Geography at Tübingen University (2006-present) Co-speaker of the Collaborative Research Center (SFB 1070) 'ResourceCultures' (2017-present) Principal Investigator in the Cluster of Excellence 'Machine Learning' (2019-present) Professor Scholten's research focuses on soil science, environment, geomorphology, geoecology, soil erosion, and machine learning applications in soil science. His fieldwork spans Europe, Africa, and Asia with major projects in South Africa, Swaziland, Sudan, Israel, China, Nepal, Switzerland, and Germany. He has published extensively with 9 books, 228 refereed papers, and 378 conference papers to his name. His recent publications reveal a strong integration of traditional soil science with cutting-edge machine learning techniques, particularly in digital soil mapping, soil erosion prediction, and resource management. The research spans multiple continents and addresses critical environmental challenges through interdisciplinary approaches combining soil science, remote sensing, and computational methods. Member of German National Academy of Science and Engineering (acatech) (2016-present) President of the German Soil Science Society (DBG) (2012-2015) Council member of the European Society for Soil Conservation (ESSC) (since 2004) Editorial board member of Journal of Plant Nutrition and Soil Science, Pedosphere Professor Scholten has received research grants from over 15 institutions, primarily the European Union (EU), the German Research Foundation (DFG), and the German Federal Ministry of Education and Research (BMBF). He serves as a referee for numerous international journals and has advised on scientific policy through various advisory boards and committees. His work has significant implications for sustainable land management and climate change adaptation strategies globally. He leads the Soil Science and Geomorphology work group at the University of Tübingen, with research activities spanning field studies, laboratory analyses, and computational modeling. His team collaborates with researchers across disciplines including geography, ecology, computer science, and archaeology to address complex environmental challenges through the ResourceCultures Collaborative Research Center and other international projects.

Patricia Martinkovaمشاهده پروفایل

دانشیار

• Psychometrics
• Statistical Modeling
• Educational Measurement
• +۶ مورد دیگر

Patricia Martinkova is an Associate Professor at the Faculty of Education, Charles University , a Senior Researcher leading the Department of Statistical Modelling at the Institute of Computer Science, Czech Academy of Sciences , and an Affiliate Associate Professor at the University of Washington (Statistics and Social Sciences). She is also the founder of the Computational Psychometrics Group and the Center for Educational Measurement and Psychometrics at Charles University. Her research focuses on advanced psychometric models and estimators for granular insights in education, psychology, and health, with emphasis on inter-rater reliability , differential item functioning (DIF) , and reproducible research via tools like ShinyItemAnalysis . She has developed software packages ( difNLR , SIAmodules , SIAtools ) and authored the book Computational Aspects of Psychometric Methods. With R (2023). Recent projects include the 2025–2027 EduCoDe (Czech Science Foundation) and 2024–2028 Digital Technologies and Wellbeing (EU-funded). She has received recognition as a Fulbright Alumna (2013–2015) and organized the IMPS 2024 conference (570+ participants). Teaching includes courses on Statistical Methods in Psychometrics and Item Response Theory , incorporating active learning and R-based tools.

Christoph Tholenمشاهده پروفایل

استاد

• Machine Learning
• Remote Sensing
• Marine Environmental Monitoring
• +۳ مورد دیگر

Christoph Tholen is a Professor at the German Research Center for Artificial Intelligence (DFKI) , leading the Marine Perception unit. His work focuses on applying AI to maritime challenges, with expertise in remote sensing, environmental monitoring, and machine learning for aquatic systems. Research Interests Development of AI-driven solutions for marine pollution detection Multi-platform/multi-sensor remote sensing integration Modeling photosynthetically active radiation in aquatic environments Location-independent neural network architectures Long-term monitoring of waterway pollutants Environmental data fusion techniques Projects XAI4SFAS : Intelligent assistance systems for semi-autonomous ship navigation APLASTIC-Q-Canada : Machine Learning identification of pollutants in Canadian waterways PlasticObs_plus : Airborne multi-sensor monitoring for oceanic plastic detection MATE : Maritime traffic emissions monitoring network Collaborations Works with mariNom GmbH and Jade Hochschule Wilhelmshaven/Oldenburg/Elsfleth on aquatic imaging data, plastic pollution analysis, and maritime emissions research.

Bastian Welschمشاهده پروفایل

استاد

• Geothermal Energy
• Renewable Energy Systems
• Borehole Thermal Energy Storage
• +۳ مورد دیگر

Prof. Dr.-Ing. Bastian Welsch serves as a Professor in the Department of Civil and Environmental Engineering at Bochum University of Applied Sciences, where he holds key leadership roles including Head of the Renewable Energy Systems program, Chairman of the Renewable Energy Systems Committee, and member of both the Departmental Council and founding board of the Energy Transition Institute (EnWI). His academic focus centers on geothermal energy systems and renewable energy integration within sustainable infrastructure frameworks. Welsch's research expertise spans medium-deep borehole thermal energy storage, geothermal probe modeling, and renewable energy system optimization. His work addresses critical challenges in seasonal heat storage, district heating integration, and groundwater interaction with geothermal systems. He has pioneered simulation tools like BASIMO for optimizing borehole heat exchanger arrays and investigated permeability changes affecting regulatory approvals. His research bridges technical engineering with environmental and economic sustainability assessments. Analysis of his 15 most recent publications (2015-2020) reveals a strong trajectory toward practical implementation of geothermal storage solutions, with increasing emphasis on economic viability, environmental impact metrics, and integration with 4th generation district heating grids. His work consistently combines numerical modeling with real-world system design, demonstrating growing sophistication in optimization algorithms and multi-system coupling approaches. As an educator, Welsch teaches across both bachelor's and master's programs, covering foundational courses like Geology and Georesources alongside specialized subjects including Geothermal Energy Systems, Renewable Energies and Energy Supply, and advanced Geothermal Systems courses focusing on heating/cooling storage and electricity generation. He maintains regular consultation hours for students during academic terms.

Artem Tsikiridisمشاهده پروفایل

پژوهشگر

• Machine Learning
• Game Theory
• Market Design
• +۲ مورد دیگر

Artem Tsikiridis is a researcher at the Decision Sciences & Systems group within the Department of Computer Science at the Technical University of Munich. His work focuses on Machine Learning , Game Theory , and Market Design , with applications in Social Choice Theory and Optimization . Contact: Room 01.10.0xx, Boltzmannstr. 3, Munich, Germany | Phone: +49 (0) 89 289 - 17xxx | Email: email@in.tum.de Artem contributes to courses such as Algorithmic Game Theory , Computational Social Choice , and Operations Research , reflecting his expertise in computational methods for decision-making and economic systems. His research aligns with the group’s emphasis on interdisciplinary approaches to optimization, learning, and market design.

Volkert Paulsenمشاهده پروفایل

مدرس ارشد

• Financial Mathematics
• Stochastic Analysis
• Optimal Stopping
• +۵ مورد دیگر

Volkert Paulsen is a Senior Lecturer at the Institute of Mathematical Stochastics at the University of Münster. His career spans institutions including the University of Kiel, where he completed his Habilitation (2000), Dissertation (1994), and Diplomarbeit (1989). He has taught extensively in Financial Mathematics , Stochastic Analysis , and Mathematical Statistics , supervising over 50 Bachelor, Master, and Diploma theses on topics such as risk modeling, portfolio optimization, and derivative valuation. Research Interests: Paulsen's work focuses on Financial Mathematics (continuous-time models, American options, unit-linked insurance), Stochastic Analysis (optimal stopping, martingale methods), and Risk Modeling (credit risk, extreme value statistics). His publications include foundational studies on nonlinear observation costs in optimal stopping problems and stochastic approaches to portfolio management. Scientific Contributions: His research spans journal articles in Stochastic Processes and their Applications and Journal of Applied Probability , with recent seminar topics covering Lévy Processes , Copula Modeling , and Stochastic Volatility . He employs R for statistical applications and integrates mathematical theory with practical finance and insurance contexts. Contact: Email: Volkert.Paulsen@uni-muenster.de Room: 130.010, Orléans-Ring 10, 48149 Münster Phone: +49 251 83-33771

• Marketing
• Consumer Behavior
• Digital Marketing
• +۳ مورد دیگر

Janis Witte serves as a Research Associate at the Chair of Business Administration, specializing in Marketing, within the Faculty of Business Administration and Economics at Heinrich Heine University Düsseldorf. Employed since December 2020, he contributes to the faculty's reputation for diverse specializations and innovative teaching that blends traditional lectures with digital elements and practical tutorials. Education: Dual Bachelor of Business Administration with Marketing focus (2015-2018) at Hochschule Osnabrück, featuring integrated vocational training in trade marketing at a consumer goods company. Master of Technology-oriented Management (2018-2020) at Technische Universität Braunschweig, specializing in Marketing, Service Management, and Law, with concurrent roles as student assistant at a service management chair and working student at Volkswagen Financial Services AG. His research centers on ethical challenges in digital environments, particularly analyzing dark patterns and user manipulation techniques in online interfaces. Current projects investigate how deceptive design practices influence consumer behavior, measure perceived manipulation, and explore trust dynamics in human-AI systems. This work bridges marketing theory with practical implications for digital ethics and regulatory compliance. Publication trends from 2022-2024 reveal escalating focus on dark patterns' societal impact, evolving from foundational definitions to empirical consequence analysis and human oversight in algorithmic systems. His interdisciplinary output spans marketing, information systems, and consumer psychology venues, demonstrating methodological rigor in measuring manipulation effects while addressing urgent digital marketplace concerns. As part of Prof. Peter Kenning's research team, Witte leverages Düsseldorf's strategic location near major corporations and cultural institutions. The faculty's extensive doctoral community fosters cross-disciplinary collaboration, enriching his work on digital consumer behavior through connections with economics, computer science, and business ethics scholars.

• Educational Psychology
• Teacher Education
• Pedagogy
• +۳ مورد دیگر

Prof. Dr. Kathleen Stürmer is a faculty member at the University of Tübingen, affiliated with the Tübingen School of Education (TüSE) and the Hector Institute for Empirical Educational Research . As Deputy Director of TüSE for Internationalization since 2021, she leads initiatives to enhance global collaboration in teacher education. Research Focus: Teacher professional vision, simulation-based learning environments, diagnostic competence development, and technology integration in classrooms. Methodologies: Eye-tracking studies, meta-analytic reviews, and longitudinal analyses of teacher training efficacy. Key Projects: Observer (video-based diagnostic tool), Di-MaL (simulation framework for pedagogical diagnostics), and quality initiatives in digital distance teaching during the pandemic. Her recent publications highlight trends in educational technology (AI, tablets), teacher cognition (professional vision, attention processes), and structural innovations in teacher education programs. She actively develops standardized instruments for measuring pedagogical expertise and explores the impact of individual and contextual factors on instructional quality. Labs & Teams: She collaborates with the Hector Institute for Empirical Educational Research and leads internationalization efforts at TüSE, focusing on interdisciplinary frameworks for diagnostic competence across professions like teaching and medicine.

Martin Schmidtمشاهده پروفایل

استاد

• Mathematical Optimization
• Energy Systems
• Mixed-Integer Nonlinear Optimization
• +۳ مورد دیگر

Martin Schmidt is a Full Professor (W3) for Nonlinear Optimization at the Department of Mathematics, Trier University, since 2019. He has held leadership roles in research training groups and international committees, focusing on mathematical modeling and optimization of energy systems, gas networks, and market equilibria. His work bridges mixed-integer nonlinear optimization , bilevel optimization , and robust methods with applications to real-world energy challenges. Education: PhD in Mathematics (2013), Diplom in Mathematics (2008), both from Leibniz University Hannover. Editorial Roles: Editorial Board member of Journal of Optimization Theory and Applications and Optimization Letters , Associate Editor for OR Spectrum and EURO Journal on Computational Optimization . His research integrates complex physical systems (e.g., gas transmission networks) with game-theoretic models to analyze energy markets. Recent publications emphasize robust optimization , decomposition techniques , and machine learning integration in bilevel frameworks. Awards highlight his contributions to gas market feasibility , linear bilevel optimization , and practical applications in energy systems. Collaborations span institutions like Universidad Zaragoza, Sapienza University, and Forschungszentrum Jülich.

• Bioenergy
• Biogas Technology
• Anaerobic Digestion
• +۳ مورد دیگر

Andreas Lemmer serves as a Privatdozent (equivalent to Associate Professor) at the University of Hohenheim, where he holds a scientific staff position at the State Institute for Agricultural Engineering and Bioenergy. He actively teaches core courses including Fundamentals of Agricultural Engineering, Process Technology of Biogas Production and Utilization, and Project Design of Plants for Renewable Resources for the upcoming Winter Semester 2025/26. His research centers on advancing bioenergy systems through biogas optimization and renewable fuel production. Key focus areas include enhancing methane yield from challenging feedstocks like horse manure using mechanical pretreatment, developing machine learning models for anaerobic digestion stability prediction, and creating resource-efficient bio-LNG production chains. His work bridges agricultural engineering, environmental technology, and sustainable resource management with strong practical implementation in full-scale biogas facilities. Lemmer's recent publications demonstrate a clear trajectory toward industrial-scale bioenergy solutions, particularly in integrating agricultural residues into circular economy models and optimizing process economics for grassland biomass utilization. His work consistently addresses real-world implementation challenges in biogas technology and renewable fuel production chains. He leads significant research initiatives including the Hohenheimer Biogasforum 2023 and industrial research projects on bio-LNG/CNG production chains for bus operations using manure and organic residues. Current projects focus on resource-efficient bio-LNG production processes developed in collaboration with the State Institute for Agricultural Engineering and Bioenergy and the Field of Agricultural Engineering in the Tropics and Subtropics.

• Forest Management
• Ecology
• Biomass Estimation
• +۷ مورد دیگر

Klaus von Gadow is a Professor with a focus on forest ecology and management. He has supervised numerous doctoral theses across diverse topics in forestry, including GIS visualization, biomass estimation, and silvicultural strategies. Research Areas : Forest Management, Ecology, Biomass Estimation, GIS Applications, Population Genetics, and Tropical Forestry. Advisory Role : Supervised 18 theses from 2000–2015, covering topics like invasive species monitoring, dry savanna ecosystems, and fire succession. Key Projects : Development of k-NN methods for biomass analysis, simulation of mixed-species forest treatment pathways, and sustainable management of tropical watersheds. Trends in Publications : Recent works emphasize ecological resilience, technical innovations in forestry machinery, and data-driven forest planning. Earlier articles focus on genetic studies and post-fire succession dynamics. Advising Legacy : His supervised research has driven advancements in forest inventory systems, silvicultural modeling, and sustainable resource use.