جست‌وجوی استاد و پژوهشگر

• Clothing Technology
• CAD Pattern Construction
• Technical Textiles Manufacturing
• +۳ مورد دیگر

Prof. Katerina Rose is a Professor of Clothing Technology & CAD at Reutlingen University's TEXOVERSUM School of Textiles. She leads the Department of Clothing Technology and CAD, focusing on innovative textile design methodologies. Her expertise includes 3D pattern construction, technical textiles manufacturing, and AI-driven garment design. Her research emphasizes digital avatars for clothing simulation, low-cost 3D scanning technologies, and soft tissue modeling. Notable projects include the InBiO initiative for bio-based automotive interiors and the FLAX365 regional textile chain initiative. She holds a patent (DE102020119338A1) for patternless garment cutting methods. Teaching areas: Clothing Technology, CAD Pattern Construction, Technical Textiles Manufacturing Labs: Sewing & CAD Lab, Material Testing Lab, Electronic Textiles Lab Key collaborations: Hometrica Consulting, SciTePress, Browzwear Recent work explores microwave imaging for body dimension capture and AI-enhanced pattern generation, published in journals like Communications in Development and Assembling of Textile Products. Her contributions bridge textile engineering with digital innovation in fashion and medical applications.

• Quantitative Marketing
• Empirical Modeling
• Influencer Marketing
• +۸ مورد دیگر

Maximilian Beichert is an Assistant Professor at Bocconi University, where he conducts research at the intersection of quantitative marketing and information systems. Prior to this, he was a Postdoctoral Researcher at HEC Paris and earned his PhD from the University of Mannheim. His work focuses on influencer marketing, the creator economy, and social influence in digital environments. His research interests include: Empirical Modeling of Marketing Phenomena Large-scale Field Experiments Creator Economy Dynamics Sales-driven Influencer Marketing Digital Marketing and Social Media Analytics Beichert's publications appear in top-tier journals such as the Journal of Marketing and MIT Sloan Management Review . His recent work explores influencer ROI, value chains in the creator economy, and algorithmic selection models. Themes across his research include monetization strategies, gender equity, sustainability, and ethical considerations in digital influence. He frequently presents at leading business schools worldwide, including Columbia, INSEAD, and Copenhagen Business School. His scientific awards include: 2025 Don Lehmann Award (AMA) 2024 AMA/MSI H. Paul Root Award Finalist, 2024 Shelby D. Hunt/Harold H. Maynard Award 2024 Best Dissertation Award (German Association for Direct Selling) 2024 Stiftung Marketing Award (University of Mannheim) Runner-Up, EMAC/Enginius Doctoral Dissertation Competition (2024) 2023 CDSB Doctoral Student Awards for Best Teacher and Best Paper (GESS, University of Mannheim) Best Student Paper Award, WISE 2022 Maximilian actively contributes to academic service as co-chair of the Creator Economy Retreat and the EMAC Creator Economy Special Interest Group. He is also a co-chair of the 'Digital Marketing, Social Media, and Online Platforms' track at the 2026 AMA Winter Academic Conference. He regularly reviews for scholarly journals. His research is supported by industry collaborations with organizations such as CreatorIQ and Typology, which have enabled large-scale field experiments using data from YouTube, Instagram, and TikTok. He has advised or collaborated with multiple researchers and is involved in projects examining influencer lifetime value, gender pay gaps, and ethical challenges like sharenting. He is affiliated with the following institutions: PhD: University of Mannheim Postdoctoral Researcher: HEC Paris Current Faculty: Bocconi University

Verena Schoenmuellerمشاهده پروفایل

استادیار

• Marketing
• Digital Marketing
• Consumer Behavior
• +۷ مورد دیگر

Verena Schoenmueller is an Assistant Professor in the Department of Marketing at ESADE Business School, Ramon Llull University. Her research sits at the intersection of digital marketing, consumer behavior, and social media dynamics, with a focus on authenticity, polarization, and user-generated content. Her primary research interests include: Digital and Social Media Marketing Consumer Behavior in Online Environments Brand Authenticity and Trust Political and Preference Polarization Online Reviews and Sentiment Analysis Subscription Service Dynamics Dr. Schoenmueller’s recent publications explore the spread of fake news, the behavioral consequences of deplatforming, and the psychological underpinnings of extreme online reviews. Her work frequently appears in top marketing journals such as the Journal of Marketing Research and Marketing Science , and she regularly presents at leading conferences including EMAC and ISMS. The overarching trend in her research is understanding how digital platforms shape consumer cognition, emotion, and decision-making in increasingly polarized environments. She earned her PhD in Business Administration from the University of Basel, a Master in Business Administration from ESSEC, and completed her undergraduate studies in Business and Economics at the University of Mannheim. While no formal list of advisees is provided, her role as a Contracted Doctoral Professor indicates active involvement in PhD-level teaching and supervision. She has not received any explicitly mentioned scientific awards. There is no indication of part-time status or retirement. Her research has implications for brand strategy, platform governance, and public policy around digital misinformation and consumer protection.

• In-flight ice accretion
• Numerical simulation and optimization of electro-thermal ice protection systems (ETIPS)
• Icing wind tunnel testing and measurement techniques
• +۶ مورد دیگر

Mariachiara Gallia is a Research Fellow at the Institute of Fluid Mechanics , Technische Universität Braunschweig , Germany. She specializes in in-flight ice accretion and numerical simulation of electro-thermal ice protection systems (ETIPS) for aerospace applications. Research Focus: Ice accretion modeling, robust optimization, uncertainty quantification, CFD, machine learning for fluid dynamics, ice roughness characterization. Projects: Participated in the European ICE-GENESIS project; currently co-supervises Ph.D. students in the MSCA DN-JD TRACES project. Education: Holds a Ph.D. in Aerospace Engineering from Politecnico di Milano, Italy. Her work spans numerical frameworks for ice protection systems, icing wind tunnel testing , and roughness effects on heat transfer . Key publications address robust optimization under uncertain cloud conditions, machine learning in fluid dynamics, and modular ETIPS designs for wind turbines.

Ihtiyor Bobojonovمشاهده پروفایل

پژوهشگر

• Agricultural Economics
• Climate Change
• Risk Management
• +۴ مورد دیگر

Dr. Ihtiyor Bobojonov is a Researcher at the Leibniz Institute of Agricultural Development in Transition and Emerging Economies (IAMO) , where he has worked since 2012. His research focuses on climate change adaptation , agricultural insurance , and supply chain dynamics in transition economies, particularly Central Asia. He completed his PhD at the University of Bonn , analyzing crop and water allocation under uncertainty in Uzbekistan, and received the ZEF Doctoral Thesis Prize (2007–2009). His work addresses agricultural market potentials in CIS countries, emphasizing supply chain transformation 's impact on producer welfare and insurance market development for climate resilience. He leads IAMO’s Central Asia International Research Group and coordinates the German-Uzbek Chair on Central Asian Agricultural Economics at Tashkent International Agricultural University. His methodological expertise spans bioeconomic modeling , machine learning , and experimental economics , with applications in weather index insurance and remote sensing for yield estimation. Key scientific awards include ZEF’s best thesis prize. His 15 most recent articles (2025–2020) explore topics across agricultural insurance markets , climate risk mitigation , wheat yield modeling , and peer influence on adaptation strategies , with empirical studies in Uzbekistan, Kyrgyzstan, and Mongolia. Research projects like KlimALEZ and DETECCT highlight his commitment to building climate-resilient agrifood systems through innovative financial instruments and digital technologies .

Nathan Weisمشاهده پروفایل

پژوهشگر

• Political Economy of Industrial Policy
• Digitalization in Work and Production
• Electromobility Transition
• +۳ مورد دیگر

Nathan Weis is a Visiting Researcher at the Wissenschaftszentrum Berlin für Sozialforschung (WZB) within the Research Group Globalization, Work, and Production. He holds a scholarship from the Hans-Böckler-Foundation in the doctoral program 'Good Work in a Transformative World.' Institution: WZB Berlin Role: Visiting Researcher Research Focus: His work critically examines industrial policy measures and digitalization's political economy, particularly analyzing: Electromobility transition in the automotive sector Regional dynamics and worker initiatives State-corporate collaboration in technological shifts Digitization's impact on labor and production Publication Trends: Recent works explore digitalization's ideological dimensions, electromobility's structural challenges, and geopolitical implications of technological shifts across Europe and Africa. Scientific Awards: Hans-Böckler-Foundation scholarship Collaborations: Frequently collaborates with Peter Schadt and other scholars on political economy topics, contributing to edited volumes and academic journals. Contact: nathan.weis@wzb.eu , Reichpietschufer 50, Berlin

Jason J. Jungمشاهده پروفایل

استاد

• Computer Science
• Knowledge Engineering
• Social Media Analysis
• +۳ مورد دیگر

Jason J. Jung is a Professor in the Department of Computer Engineering at Chung-Ang University, Seoul, Korea. His academic work focuses on knowledge engineering , social media analytics , and data mining within the Knowledge Engineering Laboratory. Research Interests : Computer Science, Social Knowledge, Data Modeling, Sentiment Analysis Projects : IoT-based cultural systems, real-time social event detection, transmedia storytelling models The 15 most recent publications (2014-2018) demonstrate expertise in social network analysis , multimodal data processing , and context-aware systems applied to urban services, cultural tourism, and digital storytelling. Key trends include real-time analytics , trust modeling , and collaborative frameworks for O2O services. Professional activities include editorial contributions, invited talks, and patent developments. Students at all levels (PhD/MSc/BSc) conduct research under his supervision at the Knowledge Engineering Laboratory. Personal interests include travel, film, painting, literature, and music.

• Geoinformatics
• Computer Graphics
• Computer Vision
• +۵ مورد دیگر

Prof. Dr. rer. nat. habil. Stephan Kopf is a faculty member at the Faculty of Spatial Information, where he holds the Professorship in Informatics and Geoinformatics. He actively contributes to research in geographic information systems (GIS), computer graphics, computer vision, and multimedia technologies. His academic leadership roles include serving as Dean and as a member of the Faculty Council, with advisory roles in the Senate. His research spans crowd simulation , image/video retargeting , augmented reality platforms , and interactive learning systems . He focuses on algorithm development for GIS, temporal effects in re-captured video, and scalable solutions for classroom interactivity. His work frequently integrates machine learning, mobile computing, and geospatial data. For teaching, he oversees courses such as Internet Technologies, Informatics, and Programming in degree programs like Geoinformatics/Management and Surveying. He supervises theses involving programming-centric topics like mobile app development , VR applications , and astronomical analysis of geospatial data .

• Artificial Intelligence
• Data Science
• Computer Vision
• +۶ مورد دیگر

Niklas Beuter is a Professor of Artificial Intelligence and Data Science at TH Lübeck, Germany, within the Department of Electrical Engineering and Computer Science. He has been in this position since 2023, contributing to both research and education in AI and computer vision. His educational background includes a Diplom in Computer Science with a focus on robotics from Universität Bielefeld, completed with distinction, followed by a Ph.D. from the same institution in 2011. His doctoral research centered on 3D human detection and tracking for mobile robotic platforms, supporting situation awareness in dynamic environments. Beuter's research is deeply rooted in artificial intelligence, computer vision, and robotics , with a focus on dynamic 3D scene analysis, human-robot interaction, and autonomous systems . His work bridges theoretical models with real-world applications, particularly in autonomous driving and intelligent robotic perception. He has led research teams in industry, demonstrating strong leadership in applied AI. The trend in his publications reflects a consistent focus on perception systems for robots and vehicles , evolving from foundational work in 3D reconstruction and gesture-based interaction to advanced topics like pedestrian intent forecasting using deep learning. His contributions span top conferences such as IEEE ICRA, CVPR, and Intelligent Vehicles, indicating sustained engagement with the core AI and robotics communities. While no formal scientific awards are listed in the provided text, his leadership roles and publication record reflect significant professional recognition. He actively supervises student theses and invites students to register for thesis topics via email, indicating an ongoing commitment to mentoring. Although no specific grants are mentioned, his industrial and academic research leadership suggests involvement in funded projects. He is a member of research groups including CoSA and serves as Deputy Head of ISy, showing active participation in institutional research organization. His research has been conducted in collaboration with teams at Universität Bielefeld, Daimler Research Center, and Robert Bosch GmbH, reflecting a strong interdisciplinary and industry-academia network. His work continues to influence both academic research and industrial applications in AI and autonomous systems.

Robert Kleinمشاهده پروفایل

استاد

• Operations Research
• Revenue Management
• Logistics Optimization
• +۴ مورد دیگر

Prof. Dr. Robert Klein is a Professor at the University of Augsburg within the Faculty of Business and Economics . He holds the Chair of Analytics & Optimization , focusing on the application of mathematical models from operations research to solve real-world decision problems. Research Interests: Pricing and revenue management, last-mile logistics, mobility-on-demand systems, integration of demand management and vehicle routing, discrete choice analysis, integer programming, and approximate dynamic programming. Teaching: Undergraduate mathematics for business, advanced courses in operations research, logistics, and revenue management. His chair offers seminars on Smart Logistics & Mobility and supervises bachelor’s and master’s theses. Publications: Over 20 years, he has co-authored 25+ peer-reviewed articles in journals like Transportation Science , European Journal of Operational Research , and OR Spectrum . His work spans theoretical advancements and practical applications in revenue management and logistics. Students: Supervised 15+ PhD students including David Fleckenstein (2025), Julia Heger (2025), and Jochen Mackert (2019). Collaborations: Works with IBM on mathematical software applications and has co-edited textbooks such as Decision Optimization with IBM ILOG CPLEX (2022).

Laxman Dhulipalaمشاهده پروفایل

استادیار

• Parallel Algorithms
• Graph Processing
• Parallel Clustering
• +۷ مورد دیگر

Laxman Dhulipala is an Assistant Professor in the Department of Computer Science at the University of Maryland, College Park, and a research scientist at Google Research in the Graph Mining team. He holds a Ph.D. from Carnegie Mellon University, advised by Guy Blelloch, and was a postdoctoral researcher at MIT with Julian Shun. Ph.D., Carnegie Mellon University Postdoctoral Research, MIT His research focuses on efficient parallel algorithms, particularly for graph processing and clustering. He explores theoretical and practical models of parallel computation aligned with modern hardware. His work spans parallel graph algorithms, computational geometry, and scalable systems for massive datasets. The recent publications demonstrate a strong trend in scalable and dynamic graph algorithms, with a focus on hierarchical clustering, connectivity, and benchmarking. Key themes include batch-dynamic updates, memory-efficient data structures, and practical parallel implementations for massive-scale problems. Many works appear in top venues such as SPAA, VLDB, NeurIPS, and SIGMOD. Best Paper Award at VLDB'25 Best Paper Award at SPAA'22 Best Paper Runner Up at VLDB'22 Distinguished Paper Award at PLDI'19 Best Paper Award at SPAA'18 Memorable Paper Award Finalist at NVMW'20 Honorable Mention, CMU SCS Dissertation Award Nominated for ACM Dissertation Award Dhulipala has advised and collaborated with numerous students and researchers, including Quinten De Man, Shangdi Yu, Jessica Shi, and others, contributing to influential projects such as Aspen, ParGeo, GBBS, and ParlayLib. He has received recognition for both theoretical and practical contributions to parallel computing. He teaches courses such as CMSC858N (Scalable Parallel Algorithms and Data Structures) and CMSC451 (Design and Analysis of Computer Algorithms). He is actively involved in building tools and frameworks for parallel algorithm development and evaluation, including benchmark suites and graph processing systems. His dual affiliation with academia and Google Research enables impactful, scalable research bridging theory and practice.

• Permafrost Dynamics
• Arctic Environments
• Climate Change Impacts
• +۳ مورد دیگر

Guido Grosse is a prominent researcher specializing in permafrost dynamics, Arctic environments, and climate change impacts. His work explores geomorphological processes, carbon cycling, and remote sensing applications in polar regions. Research Interests: Quantifying permafrost degradation and its implications for Arctic landscapes Analyzing methane emissions from thermokarst lakes and their climate feedback mechanisms Developing remote sensing techniques to monitor high-latitude environmental changes Studying thermo-erosional valleys and fluvio-thermal interactions in ice-rich permafrost Assessing the vulnerability of permafrost landforms under global warming Investigating submerged talik refreezing in Siberian lake-lagoon systems Collaborative Networks: Guido has co-authored studies with experts from institutions like the Alfred Wegener Institute, University of Alaska Fairbanks, and Stockholm University. His recent publications integrate multi-sensor satellite data for enhanced environmental time series analysis.

Jeff Huangمشاهده پروفایل

دانشیار

• Programming Languages
• Software Engineering
• Concurrency
• +۱ مورد دیگر

Jeff Huang is an Associate Professor in the Department of Computer Science and Engineering at Texas A&M University, specializing in programming languages and software engineering with a focus on concurrency and runtime verification. His research develops advanced program analysis techniques and tools to enhance software performance and reliability. Programming Languages Software Engineering Concurrency Runtime Verification His work has been recognized with prestigious awards including the ACM SIGSOFT Early Career Researcher Award, NSF CAREER Award, Google Faculty Research Award, and DARPA Young Faculty Award. Notably, his research has earned multiple SIGPLAN Research Highlights and PLDI Distinguished Paper Awards. ACM SIGSOFT Early Career Researcher Award NSF CAREER Award Google Faculty Research Award Mozilla Research Award Facebook Research Award DARPA Young Faculty Award ACM SIGSOFT Outstanding Dissertation Award ACM SIGPLAN PLDI Distinguished Paper Award SIGPLAN Research Highlights Jeff Huang actively contributes to academic communities as a committee member in venues like SPLASH, ICSE, ISSTA, and PLDI. He has authored influential papers on concurrency bug detection, pointer analysis, and language translation tools, spanning both theoretical foundations and practical implementations.

Monika Unterreinerمشاهده پروفایل

مدرس

• Music Education
• Educational Equity
• Recognition Theory
• +۷ مورد دیگر

Dr. Monika Unterreiner serves as a part-time Lecturer in specialist practice at the Chair of Music Education within the Institute for Music Research at the University of Würzburg's Faculty of Philosophy. Since September 2022, she has contributed to music teacher education while maintaining connections to school practice. Education: MA in music education, modern and contemporary history, and history didactics from Ludwig Maximilian University of Munich Studies in school music at the University of Music and Performing Arts Munich Completed doctoral project in music education and school pedagogy in 2021 through the Bavarian State Ministry's 'Support for Young Academics' program Completed teaching internship in 2012 Dr. Unterreiner's research centers on recognition theory in music education, exploring how recognition mechanisms operate in heterogeneous classroom settings across primary, secondary, and special education contexts. Her work bridges theory and practice through design-based research approaches, with growing emphasis on digital media integration and AI applications in music education. She investigates community music practices, popular music didactics, and prejudice-conscious teaching approaches that address cultural participation and educational equity. Analysis of her recent publications (2020-2025) reveals a clear trajectory from foundational work on recognition theory toward contemporary challenges of digital transformation in music education. Her scholarship increasingly examines AI music generators, digital-analog tensions in teaching practice, and critical perspectives on whiteness and recognition in music classrooms. This evolution demonstrates her responsiveness to technological shifts while maintaining commitment to inclusive educational practices. As a practitioner-scholar, Dr. Unterreiner maintains strong connections between university teacher education and school practice. Her background as a secondary school teacher (2010-2017, 2020-2022) informs her research on bridging the gap between academic training and classroom realities. Her work with refugee populations and community music initiatives reflects commitment to music's role in social inclusion.

• Social Network Analysis
• Misinformation Detection
• Human Mobility Modeling
• +۴ مورد دیگر

Jussara M. Almeida is an established computer science researcher specializing in social network analysis, misinformation detection, and human mobility modeling. Her extensive publication record (1996–2025) demonstrates active research in web science, political communication on messaging platforms (WhatsApp/Telegram), and cloud systems. She frequently collaborates with Brazilian institutions and international partners on large-scale data projects. Research Focus: Her core interests include: Modeling information diffusion in encrypted messaging apps (WhatsApp/Telegram) Predicting human mobility patterns and privacy implications Analyzing political discourse and election-related coordination online Developing computational methods for misinformation detection Optimizing cloud/edge computing performance Publication Trends: Recent work (2021-2025) shows intensified focus on: Telegram's role in political mobilization and information dissemination Advanced techniques for identifying fake news websites and image-based misinformation Privacy-preserving mobility analysis and edge computing Child safety in live-streaming platforms Collaborations & Impact: Key collaborators include Marcos André Gonçalves, Fabrício Benevenuto, and Marco Mellia. Her research provides critical insights into real-world problems like election integrity, platform governance, and user privacy.