جستجوی استاد راهنمای دانشگاهی

• Sports Management
• Digital Transformation in Sports
• Sports Entrepreneurship
• +۷ مورد دیگر

Sascha L. Schmidt is a Professor and Chairholder at WHU – Otto Beisheim School of Management, where he leads the Center for Sports and Management (CSM). He is also the Academic Director of the European Sports Business Program and holds affiliations with the Massachusetts Institute of Technology (MIT) and Harvard Business School. His work bridges academic research and practical application in sports and management. WHU – Otto Beisheim School of Management, Chair for Sports and Management Academic Director, European Sports Business Program Lecturer, MIT Sports Entrepreneurship Bootcamp Member, Digital Initiative, Harvard Business School Schmidt’s research centers on the future of sports, with a focus on digital transformation, technology adoption, fan engagement, and strategic innovation in professional sports. His interdisciplinary work integrates insights from economics, psychology, and management to understand how emerging technologies are reshaping the sports industry. He has led multiple Delphi studies forecasting the future of football, winter sports, and sports sponsorship. His recent publications span topics including the metaverse in football, digital transformation in national associations, and eSports strategy. These works, published in journals like Technological Forecasting and Social Change and MIT Sloan Management Review , reflect a strong trend toward technology-driven change and data-informed decision-making in sports. His research often employs foresight methodologies and behavioral insights. Schmidt has made significant contributions beyond traditional academia. He is the editor of 21st Century Sports and developed an online course with MIT xPRO. He also contributes regular columns to Focus and Manager Magazin , translating academic insights for a broader audience. Editor, 21th Century Sports: How Technologies Will Change Sports in The Digital Age Co-developer, MIT xPRO course: Transformational Technologies: Applied Lessons from Sports Author of multiple WHU CSM Delphi studies and industry reports Schmidt advises on strategic initiatives and has collaborated with major sports organizations. His work with Harvard Business School on case studies—such as Bayern Munich in China and TSG Hoffenheim’s analytics revolution—highlights his impact on teaching and real-world strategy. He is actively involved in research funding and collaborative projects, though specific grants are not detailed. He leads the Center for Sports and Management at WHU, which serves as a hub for research, industry collaboration, and executive education in sports business. The center produces influential studies and fosters innovation in sports management practices.

• Information Retrieval
• Digital Libraries
• Informetrics
• +۵ مورد دیگر

Philipp Mayr-Schlegel is a Professor at the University of Göttingen’s Institute of Computer Science, leading the team 'Information & Data Retrieval' at GESIS - Leibniz-Institute for the Social Sciences. His research focuses on interactive information retrieval systems, scholarly recommendation mechanisms, and the integration of bibliometric methods with digital library technologies. University of Göttingen - Institute of Computer Science GESIS - Leibniz-Institute for the Social Sciences His work spans information retrieval , digital libraries , and applied informetrics , with particular emphasis on: Interactive search systems Non-textual ranking algorithms Scholarly document processing Knowledge representation Semantic search technologies User behavior analysis Recent research outputs (2025) include studies on LLMs for scholarly search, bibliometric reproducibility tools, scientific uncertainty annotation, and preprint adoption disparities. He has published extensively in Scientometrics , International Journal on Digital Libraries , and top conference proceedings like ACL and ECIR . As organizer of the International Workshop on Bibliometric-enhanced Information Retrieval (BIR) and Scholarly Document Processing (SDP) series, he has shaped academic discourse through editorial roles at ISSI , JCDL , and SocInfo conferences. His projects have attracted significant national and European funding.

• Biopharmacy
• Pharmaceutical Technology
• Drug Delivery Systems
• +۱۴ مورد دیگر

Prof. Dr. Claus-Michael Lehr is a faculty member at Saarland University, affiliated with the Faculty of Natural Sciences and Technology and the Department of Pharmaceutical Science. He holds the Professorship for Biopharmacy and Pharmaceutical Technology and leads a research group at the Helmholtz-Institut für Pharmazeutische Forschung Saarland (HIPS) in Saarbrücken, Germany. His research focuses on biological barriers and advanced drug delivery systems . Key areas include the use of epithelial cell cultures from the intestine, lung, skin, and eye to model drug absorption and barrier function. His team investigates transport mechanisms of active substances across these barriers and develops modern delivery vehicles such as nanoparticles and liposomes , with applications in pulmonary delivery, targeted intestinal therapy, and non-viral gene transfer. The research also emphasizes predicting drug absorption , assessing biocompatibility , understanding clearance processes , and advancing in vitro models to replace animal experiments. This work contributes significantly to optimizing drug formulations for improved efficacy and safety. The absence of recent publications in the provided text limits trend analysis, but the focus areas suggest strong interdisciplinary work at the intersection of pharmaceutics, nanotechnology, and cellular physiology. Scientific Awards: No awards mentioned in the provided text. Prof. Lehr leads an active research group at HIPS, where he supervises scientific projects and likely mentors graduate students, though no specific advisees are listed. There is no mention of external grants, but his affiliation with Helmholtz suggests involvement in nationally funded research programs. His work contributes to translational pharmaceutical research with a strong ethical emphasis on reducing animal experimentation. The research group operates within the Helmholtz-Institut für Pharmazeutische Forschung Saarland (HIPS), specifically in the Department of Drug Delivery (Abteilung Wirkstofftransport), located on the Saarland University campus. This collaborative environment integrates academic and applied pharmaceutical research, leveraging institutional partnerships for innovation in drug development.

Volkmar Wirthمشاهده پروفایل

استاد

• Rossby wave packets
• forecast errors
• tropopause dynamics
• +۵ مورد دیگر

Volkmar Wirth is a full Professor of Theoretical Meteorology and Atmospheric Physics at the Institute for Atmospheric Physics, Johannes Gutenberg-University Mainz. His research focuses on Rossby wave packets, forecast error dynamics, tropopause behavior, mountain meteorology, and tropical cyclone processes. Full Professor since 2000 Specialist in midlatitude waveguidability and extreme weather predictability Active in mountain meteorology (banner clouds) and hurricane dynamics Teaching includes graduate courses on atmospheric hydrodynamics, predictability, and potential vorticity applications. He supervises project assignments involving numerical modeling in FORTRAN-90 and leads meteorology practicals with time series analysis experiments. Recent publications analyze Rossby wave propagation in changing climates, temperature extremes, and waveguide limitations. His group collaborates extensively on "Waves to Weather" predictability research. Current affiliations: Johannes Gutenberg-University Mainz , Institute for Atmospheric Physics.

Florian Haasمشاهده پروفایل

مدرس ارشد

• Linguistics
• Corpus Linguistics
• Historical Linguistics
• +۵ مورد دیگر

Florian Haas is a Senior Lecturer in Linguistics at the Institute for English and American Studies , Friedrich Schiller University Jena , where he has taught since 2009 across BA, MA, and teacher training programs. His research focuses on recent morphosyntactic changes in English , contrastive linguistics , typology , and usage-based construction grammar , with a notable Habilitation thesis on the history of human impersonal pronouns in English. Education : PhD in Linguistics (2008, Free University of Berlin, summa cum laude), MA in European Master's Degree in Linguistics (2002), MA in English Studies (2002). His research interests span corpus-driven analysis of language change, cross-linguistic contrasts (particularly English-German), and cognitive approaches to grammar. His publications emphasize diachronic shifts in pronouns, genre-specific linguistic patterns, and constructionist analyses of syntax. He has supervised numerous student theses on topics like political framing, bilingualism, and sociolinguistic variation in English. Academic service includes roles as Erasmus coordinator, reviewer for journals like Journal of Pragmatics , and memberships in societies such as the Association for Linguistic Typology .

• Behavioral Economics
• Insurance
• Risk Management
• +۴ مورد دیگر

Johannes Jaspersen is a Professor of Behavioral Risk Management and Insurance at the Munich School of Management , part of Ludwig Maximilian University of Munich (LMU Munich) . As an applied economist, his research bridges theoretical and experimental economics with applications to insurance, prevention, decision analysis, risk theory, and national security. His work often combines behavioral economics with rigorous empirical and theoretical methodologies. Research Interests: Behavioral Economics, Insurance Demand, Risk Perception, Experimental Methods, Decision Theory, National Security His recent publications focus on probability weighting, moral hazard, flood risk hedging, and behavioral aspects of insurance demand. These studies demonstrate his commitment to understanding how individuals and organizations make decisions under uncertainty. Key trends in his research include: Behavioral biases in insurance choices Impact of liquidity constraints on risk decisions Heuristic thinking in risk management Operational research applications to security Natural experiments in insurance markets Methodological innovations in risk elicitation

• Biomedical Engineering
• Machine Learning
• Wearable Technology
• +۳ مورد دیگر

Muhammad Awais Bin Altaf is a researcher specializing in biomedical engineering, machine learning, and wearable technology. His work focuses on low-power embedded systems for neurological and cardiovascular monitoring, including EEG processors for seizure detection and PPG-based blood pressure classification. He has collaborated extensively with co-authors like Wala Saadeh and Jerald Yoo on IEEE journals and conferences. His research interests include Biomedical signal processing Wearable health devices Machine learning for medical diagnostics Energy-efficient hardware design Neurological disorder detection Embedded systems for clinical applications Recent publications highlight trends in shallow neural networks, autoencoders, and hardware acceleration for real-time health monitoring. Key subfields span seizure prediction, stress detection, and impedance-adaptive sensors. Collaborations include institutions in Germany, Finland, and Pakistan. His work often integrates open-source toolflows and industry-standard chip design techniques, emphasizing practical implementations for wearable environments. Contributions to HDR imaging algorithms and biomedical SoCs demonstrate interdisciplinary expertise in signal processing and healthcare technology.

• Soil Science
• Environmental Engineering
• Carbon Sequestration
• +۴ مورد دیگر

Philippe C. Baveye is a Professor at Rensselaer Polytechnic Institute, affiliated with the Department of Biological Sciences. He holds an MS in Rational Mechanics from Johns Hopkins University and an Agricultural Engineering degree from the Catholic University of Louvain (Belgium). His research spans interdisciplinary domains including soil science, environmental engineering, and climate change mitigation. His recent work focuses on ecosystem-scale soil carbon modeling, biochar economics, and environmental risks associated with enhanced rock weathering. He has contributed to debates on agricultural sustainability, scientific ethics, and the distinction between soil carbon storage and sequestration. His interdisciplinary approach integrates colloidal chemistry, continuum mechanics, and microbial dynamics. 2023: Ecosystem-scale soil carbon dynamics modeling 2023: Biochar application cost analysis 2023: Soil carbon vs. sequestration definitions 2023: Toxic trace element accumulation in soils 2022: Scientific integrity and conflict of interest Philippe Baveye actively collaborates with researchers across Europe, Brazil, and Asia, with 242,643 total profile views and 240 publications. His editorial contributions include 37 edited publications and 9 edited research topics.

• Data Mining
• Database Systems
• Spatial Databases
• +۵ مورد دیگر

Yubao Liu is a Professor at Sun Yat-sen University's School of Data and Computer Science, Department of Computer Science, with a prolific research career spanning over two decades in computer science. His work demonstrates significant contributions to database systems, data mining, and spatio-temporal analysis. Professor Liu's research interests focus on Data Mining , Database Systems , Traffic Flow Prediction , and Graph Neural Networks . His recent work has concentrated on developing advanced techniques for large-scale traffic flow prediction, crowd flow analysis, and spatio-temporal modeling using deep learning approaches. His research bridges theoretical computer science with practical applications in transportation systems and urban computing. Liu's publication record shows consistent high-impact contributions, with recent work emphasizing graph-based neural network architectures for traffic forecasting problems. His research demonstrates a clear evolution from foundational database work to cutting-edge applications of deep learning in transportation and social network analysis. Professor Liu has collaborated extensively with researchers including Weiyang Kong, Kaiqi Wu, Sen Zhang, Genan Dai, and Youming Ge, indicating a strong research group focused on spatio-temporal data analysis and deep learning applications. His academic advising is evident through publications where his students appear as first authors, suggesting an active mentorship role in training the next generation of computer scientists specializing in data-intensive applications.

• Robotics
• Industrial Automation
• Control Systems
• +۶ مورد دیگر

Petter Falkman is a researcher at Chalmers University of Technology, specializing in robotics, industrial automation, and control systems. His work bridges theoretical advancements with practical applications in manufacturing, leveraging technologies like digital twins, eye tracking, and virtual reality. Key Research Areas: Robotics, Industrial Automation, Control Systems, Digital Twins, Human-Computer Interaction, Machine Learning. Collaborations: Frequently works with Bengt Lennartson, Kristofer Bengtsson, Martin Dahl, and colleagues across institutions. Publication Trends: Recent articles focus on gaze-based human intention prediction, ROS2 control architectures, and compositional automated planning. His work integrates machine learning with industrial control systems, emphasizing event-driven design and virtual commissioning. Methodologies: Develops frameworks like EPypes for data pipelines, contributes to STEP AP214 model generation, and explores energy optimization in multi-robot systems.

• Software Performance Engineering
• Microservice Architectures
• Cyber-Physical Systems
• +۳ مورد دیگر

Catia Trubiani is a faculty member at the Gran Sasso Science Institute in L'Aquila, Italy, specializing in software performance engineering, architectural analysis, and cyber-physical systems. Her work bridges theoretical modeling with practical applications, focusing on performance antipatterns, uncertainty quantification, and DevOps practices. In research , she explores performance modeling of microservices, federated learning systems, and cyber-physical systems, with a strong emphasis on architectural decision-making under uncertainty. Her recent articles analyze performance regression testing, aging detection in networks, and anti-pattern correlation in distributed systems, reflecting her interest in robust, scalable software solutions. She collaborates extensively with researchers like Raffaela Mirandola , Alberto Avritzer , and Riccardo Pinciroli , contributing to tools and frameworks such as PLUS (Performance Learning for Uncertainty of Software) and VisArch (Visualisation of Performance-Based Architectural Refactorings). Her work has been published in journals including IEEE Transactions on Software Engineering and Future Generation Computer Systems , as well as conferences like ICSE, ECSA, and ICPE.

Felix Schindlerمشاهده پروفایل

پژوهشگر

• Numerical Analysis
• Machine Learning
• Scientific Computing
• +۳ مورد دیگر

Felix Schindler is a Researcher at the Institute for Analysis and Numerical Analysis , part of the Department of Mathematics and Computer Science at the University of Münster . His work bridges numerical analysis, machine learning, and scientific computing, with a focus on model reduction for partial differential equations (PDEs), adaptive algorithms, and computational efficiency. Research Interests include: Numerical analysis of parametric and multiscale PDEs Localized reduced basis methods (LRBM) and adaptive enrichment Integration of model order reduction (MOR) with machine learning (ML) Conservative flux reconstruction techniques Development of software libraries like dune-xt and pyMOR Recent Publications highlight trends in applying deep kernel models for surrogate modeling, localized training strategies for PDE-constrained optimization, and hybrid full/reduced-order pipelines for reactive flow prediction. His work emphasizes certified error control, hierarchical adaptivity, and cross-disciplinary computational frameworks. Collaborations span institutions such as AIMS Senegal, Springer Nature, and DUNE project teams. He actively contributes to conferences like GAMM, ENUMATH, and Algoritmy.

• Uncertainty Quantification
• Data Assimilation
• Machine Learning
• +۴ مورد دیگر

Dr. Truong Vinh Hoang is a Researcher at the RWTH Aachen University , affiliated with the Chair of Mathematics for Uncertainty Quantification . His work focuses on integrating machine learning with data assimilation techniques for nonlinear dynamical systems . He has presented at multiple international conferences and seminars on these topics. Specializes in Bayesian methods and stochastic numerics Developed ML-EnCMF (Machine Learning-Ensemble Conditional Mean Filter) for non-linear data assimilation Applied techniques to Lorenz-63 and Lorenz-96 systems under chaotic regimes Contributed to localized neural network architectures for high-dimensional state tracking His research trends from 2020-2022 show increasing emphasis on deep learning-based filtering and Bayesian optimization for systems with non-Gaussian dynamics . Notably, he implemented variance reduction techniques to improve filter stability with small ensemble sizes. All publications demonstrate practical applications in computational science and stochastic modeling . Dr. Hoang is part of the MATH4UQ team at RWTH Aachen University, contributing to cutting-edge research in uncertainty quantification and nonlinear data assimilation .

Tobias Windischمشاهده پروفایل

استاد

• Machine Learning
• Computer Vision
• Reinforcement Learning
• +۴ مورد دیگر

Prof. Dr. Tobias Windisch is a Professor at the University of Applied Sciences Kempten, where he serves as head of the Institute for Machine Vision within the Faculty of Mechanical Engineering. He leads the Optical 3D Measurement and Computer Vision Laboratory (3D visionlab) and oversees research activities focused on machine learning applications for industrial automation. Dr. Windisch received his PhD in mathematics from OvGU Magdeburg under the supervision of Thomas Kahle, and holds an Honors Master's degree in mathematics from TU Munich within the elite TopMath program. Prior to his academic career, he worked on machine learning projects for Robert Bosch GmbH and Daimler TSS GmbH (now Mercedes-Benz Tech Innovation). His research spans machine learning, computer vision, and optical sensing with a strong focus on industrial applications. Windisch's work primarily explores how reinforcement learning can be combined with optical sensing to develop intelligent control strategies for manufacturing processes. His team develops mechanical processes built around machine learning models to further automate industrial applications using data from optical sensors. The research has practical applications in automotive production, quality control, and precision manufacturing. Analysis of his recent publications reveals a strong trend toward practical implementations of machine learning in industrial settings, with particular emphasis on reinforcement learning for process optimization, drift detection in high-dimensional data, and causal structure learning for manufacturing analytics. His work bridges theoretical machine learning with real-world industrial challenges. As a dedicated educator and research leader, Windisch maintains high standards for academic integrity and excellence. He believes in creating an environment where students can focus deeply, think boldly, and innovate through meaningful research. Dr. Windisch leads a dynamic research group with numerous Master's and Bachelor's students working on cutting-edge projects including reinforcement learning for active alignment, drift detection in sensory data, latent drift detection with Autoencoders, and representation learning for industrial processes. His laboratory, the 3D visionlab, serves as the physical hub for this research. The Institute for Machine Vision under his leadership develops practical tools and frameworks such as relign, lineflow, and driftbench that are openly available on GitHub, demonstrating his commitment to reproducible research and practical applications.

Jan C. Fransooمشاهده پروفایل

استاد

• Supply Chain Management
• Logistics
• Operations Management
• +۹ مورد دیگر

Jan C. Fransoo is Professor of Operations and Logistics Management at the Tilburg School of Economics and Management, Tilburg University. He maintains significant affiliations with MIT's Center for Transportation and Logistics as a Research Affiliate and with Technische Universiteit Eindhoven as a Visiting Professor. His research bridges academic rigor and practical application through extensive collaborations with multinational corporations, technology startups, and intergovernmental organizations including the World Bank and Interamerican Development Bank. His educational background includes: PhD in Production Control and Demand Management in Capacitated Flow Process Industries, Technische Universiteit Eindhoven (1989-1993) Master's Degree in Industrial Engineering and Management Science, Technische Universiteit Eindhoven (1984-1989) Professor Fransoo's research focuses on supply chain and operations management , with pioneering work on "nanostores" - his term for the 50 million mom-and-pop stores serving populations in developing regions. He also conducts significant research in urban logistics, omnichannel retail, and human-AI collaboration in supply chain decision-making. His methodology combines model-based and empirical quantitative approaches with practical field research, often developed in close partnership with industry stakeholders across multiple continents. His recent publications reveal a strong trend toward addressing real-world supply chain challenges in developing economies, particularly focusing on nanostore operations, financial constraints affecting small retailers, and the role of technology in enhancing supply chain resilience. His work consistently bridges theoretical innovation with practical applicability, as evidenced by his leadership in the Dutch national COVID-19 vaccination program deployment. Among his notable recognitions: M&SOM Journal Meritorious Service Award (2016) Salzberg Medallion (2022) University Medal from Eindhoven University of Technology (2017) Paper selected for virtual special issue in Transportation Science (2021) Professor Fransoo has supervised over 30 PhD students throughout his career, with current advisees researching nanostore logistics, human-AI decision making, and public health operations. His research is supported by collaborations with major organizations including ASML, ABInbev, Grupo Bimbo, and the World Bank. Notably, in 2021 he led a volunteer team that significantly accelerated the Dutch national vaccination campaign. He actively contributes to national logistics policy through Dinalog (the Dutch Institute for Advanced Logistics) and serves on the Independent Advisory Committee for the National Mobility Vision 2050. His current research continues to explore the complex dynamics of retail supply chains in developing economies and the transformative potential of digital technologies in global logistics operations.