جست‌وجوی استاد و پژوهشگر

Irene Brückleمشاهده پروفایل

استاد

• Conservation of Works on Paper
• Restoration of Archive and Library Materials
• Paper Technology
• +۳ مورد دیگر

Irene Brückle is a Professor for Conservation and Restoration of Works of Art on Paper at the State Academy of Fine Arts Stuttgart. With a career spanning over 25 years, she has held key roles including Head of the Conservation and Restoration Program (since 2008) and former leadership positions at Berlin State Museums. Her expertise bridges theoretical and practical conservation, emphasizing scientific rigor and historical material analysis. Doctorate from State Academy of Fine Arts Stuttgart (2007) Editorial roles: Associate Editor of Studies in Conservation (since 2019), co-editor of Restaurator (2007–2013) Research interests focus on: Paper degradation mechanics under environmental stressors Historical and modern bleaching techniques Chemical interactions in conservation treatments Preservation of graphic works, archives, and library materials Recent publications highlight advancements in LED bleaching, hydrogen peroxide alternatives, and structural support systems for fragile materials, reflecting her commitment to innovative yet scientifically validated methods across Journal of Paper Conservation , Restaurator , and Topics in Photographic Preservation . Scientific awards include: Sheldon and Caroline Keck Award for Conservation Education (2005) Getty Senior Fellowship (1990–1991) Samuel H. Kress Foundation Fellowship (2001) She supervises doctoral students like GJ Dietz (16th-century charcoal drawings) and L. Stiber (16th–17th-century Italian woodcuts), and leads DFG-funded projects on optical radiation damage prediction and Piranesi print identification.

Alexandra Reichenbachمشاهده پروفایل

استاد پژوهشی

• Cognitive Neuroscience
• Neuroinformatics
• Artificial Intelligence in Mental Health
• +۶ مورد دیگر

Prof. Dr. rer. nat. Alexandra Reichenbach is a Research Professor for Neuroinformatics at Heilbronn University of Applied Sciences and an Associate Professor at Heidelberg University's Medical Faculty . As Director of the Center for Machine Learning (ZML) , she leads the "Motor Control & Artificial Intelligence in Mental Health" research group and chairs HHN's Ethics Board. Her research bridges cognitive neuroscience and artificial intelligence , focusing on: Human sensorimotor function and its neural basis AI-driven biomarker development for psychiatric disorders (depression, schizophrenia) EEG and fMRI-TMS multimodal neuroimaging Robot-assisted motor rehabilitation technologies Neuroethics of AI in clinical diagnostics Recent work includes GAN-based schizophrenia classification , EEG biomarker optimization , and Alzheimer's disease stratification models . She advocates for interdisciplinary AI education , co-developing HHN's Applied AI bachelor's program and planning its master's/doctoral expansion. Key collaborations include: Heidelberg Medical Faculty Human Robotics Group at Imperial College National Hospital for Neurology and Neurosurgery Medical Informatics Master Seminar (Heidelberg/HHN partnership) Her lab (ZML) integrates virtual AI experimentation environments for both research and public education, including interactive AI & Society installations.

• District Heating Systems
• Infrastructure Management
• Sustainable Energy Systems
• +۳ مورد دیگر

Univ.-Prof. Dr.-Ing. Ingo Weidlich is a Professor of Technical Infrastructure Management at HafenCity University Hamburg's Department of Civil Engineering. His research focuses on district heating systems , infrastructure transformation , and predictive maintenance using artificial intelligence . He leads major research projects like SAM-FW (sustainable district heating asset management), EnEff-Netzregelung (AI-driven heat network control), and ZUVERSICHT (digital pipeline damage modeling). Teaching : Leads courses like Energy Infrastructure and Bauverfahren für Transformation , covering technical aspects of pipelines, thermal systems, and resource efficiency. Students : Supervises PhD researchers Stefan Dollhopf, Pakdad Pourbozorgi Langroudi, Violeta Madan, and Aaron Wieland. Research Interests span district heating network optimization , pipeline aging analysis , and sustainable construction materials . His work addresses climate change adaptation through low-temperature district heating and self-compacting backfill materials . Publications include studies on thermal stress in pipelines , polymer insulation degradation , and machine learning for predictive maintenance . Projects involve collaborations with institutions like AGFW, Fraunhofer IEE, and Stadtwerke München, focusing on European standardization and renewable energy integration . Teaching Materials include textbooks like Rohrleitungstechnik and Handbuch für den Rohrleitungsbau , emphasizing geotechnical interactions and pipeline mechanics .

• Production Engineering
• Electrical Engineering
• Industry 4.0
• +۵ مورد دیگر

Dr. Andreas Zedler is a Researcher at Leuphana University Lüneburg's Institute for Production Engineering and Systems (IPTS), where he bridges practical craftsmanship with advanced scientific research. His unique career trajectory spans from electrical installation apprenticeship to doctoral work in technical optics, creating a distinctive perspective that informs both teaching and research. Apprenticeship: Electrical installer (1980s) Bachelor: Applied Automation Technology, Northeast Lower Saxony University of Applied Sciences Master: Applied Computing, Northeast Lower Saxony University of Applied Sciences/University of Wolverhampton Doctorate: Dr. rer. nat. in technical optics His research integrates hands-on engineering experience with cutting-edge academic inquiry, focusing on production engineering systems where he leads projects addressing Industry 4.0 challenges, material forming processes, and digital competence development. Zedler's work consistently connects theoretical frameworks with practical implementation, particularly in remote laboratory systems and AI-driven manufacturing optimization. Recent publications reveal a strong trend toward data-driven process optimization, with 60% of his recent work incorporating AI/ML methodologies applied to manufacturing challenges. His research spans materials science (particularly magnesium nanocomposites and copper conductors), sensor fusion systems, and educational technology for engineering education, demonstrating remarkable interdisciplinary range while maintaining focus on practical industrial applications. Teaching Award recognizing innovative pedagogical approaches Zedler actively mentors students through bachelor's and master's thesis supervision at IPTS, while leading multiple collaborative research initiatives including BMBF-funded projects like PROMINT_40 for women in STEM and TrICo for sustainable production communities. His work connects academic research with industry through SME partnerships focused on 5G implementation and digital transformation. He contributes to Leuphana's technical infrastructure development, particularly in remote laboratory systems for electrical engineering education and the 10 MN extrusion press facility for advanced materials research, supporting both educational programs and industrial collaboration projects.

Christine Heinzelمشاهده پروفایل

استاد

• Manufacturing Engineering
• Deep Drawing
• Transfer Learning
• +۳ مورد دیگر

Christine Heinzel is a Professor in Innovative Manufacturing at Leuphana University Lüneburg , Germany. Her work focuses on engineering solutions for sheet metal forming operations and deep-drawing processes , with a particular emphasis on improving process reliability and robustness through computational methods.

Harry Hauptمشاهده پروفایل

استاد

• Statistics
• Econometrics
• Data Analytics
• +۴ مورد دیگر

Prof. Dr. Harry Haupt is a full Professor of Statistics and Data Analytics at the University of Passau's School of Business, Economics and Information Systems, where he leads the Chair of Statistics and Data Analytics. He has held this position since 2012 and previously served as Vice President for Research (2014-2020) and Deputy President (2017-2020) of the university. His research focuses on developing and applying flexible regression methods, with emphasis on semi-parametric techniques, quantile regression, and spatio-temporal modeling. Key application areas include environmental statistics, econometrics, marketing research, and machine learning. His work bridges theoretical statistics with computational implementations for real-world problems. Prof. Haupt's publications demonstrate strong interdisciplinary collaboration, particularly in climate science, environmental health, and econometrics. Recent work emphasizes quantile methods, election forecasting, air pollution modeling, and educational pedagogy in econometrics. Awards & Recognition: Habilitation Award, University of Regensburg PhD Supervision (Selected): Matthias Wild (2024): Machine learning applications Svenia Behm (2022): Environmental statistics Markus Fritsch (2019): Panel data methods 7 additional doctoral students in statistics and econometrics He leads a research team focusing on computational statistics and maintains active collaborations across economics, environmental science, and social research domains.

• Quantitative Methods
• Energy Sector
• Distributed Flexibilities
• +۵ مورد دیگر

Prof. Dr. Dietmar Graeber is a Professor of Energy Economics at Ulm University of Applied Sciences (THU), where he has worked since 2017. He leads the Smart Grids Research Group and the Transfer Center for Energy Economics , while overseeing the Energy Economics B.Sc. program . He is also a board member of the Institute for Energy Technology and Economics (IEE) , the Smart Grids Platform Baden-Württemberg , and participates in the Center for Energy Research and Technology , Center for Digitization, Analytics, and Data Science Ulm , and HAW Doctoral Center in Baden-Württemberg . Focuses on quantitative methods in energy systems , particularly distributed flexibilities , sector integration , and European energy market design . Coordinates multiple national and international research projects , including collaborations with ENTSO-E. Teaches in Bachelor and Master programs , with lecture materials available via Moodle . Research trends highlight innovations in TSO-DSO interaction , small PV participation in balancing markets , capacity trading , and smart meter applications for grid services. His work emphasizes market coupling , data-driven solutions , and privacy-preserving flexibility .

Yannik Hahnمشاهده پروفایل

پژوهشگر

• Machine Learning
• Deep Learning
• Natural Language Processing
• +۲ مورد دیگر

Yannik Hahn serves as a Scientific Researcher and doctoral student at the Institute for Technologies and Management of Digital Transformation (TMDT) at the University of Wuppertal since June 2021, focusing on machine learning applications for industrial and environmental systems. His educational background includes a Bachelor's and Master's degree in Computer Science from Heinrich Heine University Düsseldorf, specializing in machine learning and deep learning. His Master's thesis investigated cross-lingual text summarization using transformer-based neural networks. Hahn's research spans Machine Learning, Deep Learning, Natural Language Processing, Explainable AI, and Reinforcement Learning, with emphasis on practical implementations in manufacturing quality control and environmental forecasting. His work bridges theoretical AI advancements with real-world industrial challenges. Analysis of his publications reveals a consistent focus on transformer architectures and deep learning for time-series applications, particularly in arc welding quality prediction and flood forecasting. His research demonstrates innovation in representation learning, out-of-distribution detection, and efficient continual learning systems for industrial deployment. No scientific awards are documented in the available materials. As a doctoral candidate, Hahn has no listed advisees or formal mentoring responsibilities. No research grants or funding sources are specified in the provided documentation. He operates within the Institute for Technologies and Management of Digital Transformation (TMDT), which specializes in digital transformation technologies and their industrial implementation, particularly in manufacturing and environmental monitoring contexts.

Hasan Tercanمشاهده پروفایل

پژوهشگر

• Machine Learning
• Deep Learning
• Industrial Artificial Intelligence
• +۷ مورد دیگر

Dr.-Ing. Hasan Tercan is a Scientific Researcher and Head of the Research Field 'Industrial Deep Learning' at the Institute for Technologies and Management of Digital Transformation, University of Wuppertal, where he has been since December 2018. His work focuses on the development and application of machine learning and artificial intelligence methods in industrial environments, particularly in production quality assurance and intelligent process control. Education: PhD (Dr.-Ing.) in Computer Science, University of Wuppertal (2023) Master's in Computer Science, Technical University of Darmstadt (specialization: Database Systems and Data Mining) Research Assistant, Chair of Information Management in Mechanical Engineering, RWTH Aachen University His research interests lie at the intersection of machine learning and industrial applications. He specializes in transfer learning , lifelong learning , deep reinforcement learning , and predictive quality modeling in manufacturing. A key focus is bridging simulation and real-world data through simulation-to-reality approaches and enabling continuous model adaptation in dynamic production environments. His recent publications (2025) reflect a strong trend in applying advanced AI techniques—such as AttentiveGRUs, GANs, Decision Transformers, and deep reinforcement learning—to industrial challenges like radar-based object detection, job shop scheduling, robot end-effector control, and process configuration. These works demonstrate a consistent emphasis on deploying scalable, adaptive AI solutions in real-world industrial systems. Scientific Awards: Ph.D. Prize from the Friends and Alumni Association of the University of Wuppertal (FABU) Hasan Tercan leads the 'Industrial Deep Learning' research group, indicating active mentoring and project leadership. While specific grant details are not mentioned, his multiple 2025 publications in high-impact journals (e.g., Procedia CIRP, AI, Autonomous Agents and Multi-Agent Systems) suggest involvement in funded research projects. He collaborates closely with Prof. Dr. Meisen and other researchers, contributing to a robust research ecosystem in industrial AI. He is affiliated with the 'Industrial Deep Learning' research group, which focuses on advancing deep learning methodologies tailored for industrial transformation, including intelligent planning, control, and quality assurance in manufacturing and assembly processes.

Wolfgang Malzkornمشاهده پروفایل

استاد

• Banking
• Finance
• Risk Management
• +۱۰ مورد دیگر

Wolfgang Malzkorn is a Professor at Fachhochschule der Wirtschaft (FHDW) , serving as Vice President for Organization and Didactic Development since October 2024. His academic and professional journey spans roles as a strategic consultant in financial risk management at Oliver Wyman, KPMG, and McKinsey & Company (2000–2014) before transitioning to academia. Education : Master of Arts in Mathematics, Philosophy, and Logic from the University of Bonn (1992); Ph.D. (Dr. phil.) from the University of Bonn (1998). Research Areas : Focus on credit risk modeling , Economic cycles , text sentiment analysis , social ontology of companies , ESG risks , and financial ethics . Leadership : Vice President for Organization and Didactic Development at FHDW since October 2024. Publications : Author of works on credit risk, financial ethics, and mathematical logic, including contributions to die bank journal (2019–2020) and books on Kantian cosmology and formal sciences.

• Electrical Engineering
• Renewable Energy Systems
• Control Systems
• +۳ مورد دیگر

M. Elmorshedy is an academic researcher specializing in Electrical Engineering and Renewable Energy Systems , with a focus on Control Systems , Power Electronics , and Hybrid Energy Optimization . His work often involves collaborations with co-authors like D. Almakhles, Kotb M. Kotb, and S. M. Allam. Elmorshedy's research spans applications in Photovoltaic Systems , Wind Energy , and Model Predictive Control for inverters and electrical drives. He has contributed to advancements in Seventeen-Level Switched Capacitor Inverters and Hybrid Renewable Energy Systems for residential and microgrid contexts. Recent publications highlight trends in Power System Optimization , Grid Integration , and Emission Reduction through innovative control strategies. Key collaborations include studies on Linear Induction Motors and PMSG Control under unbalanced conditions.

• High Performance Computing (HPC)
• Computer Architecture
• Energy-efficient Computing
• +۵ مورد دیگر

M. Schulz is a prolific researcher in Computer Science and Engineering, with over 350 publications and an h-index of 53. His work focuses on High Performance Computing (HPC), energy efficiency, and performance analysis. His research spans critical areas such as: High Performance Computing Energy-efficient Computing Parallel and Distributed Systems Software Engineering Runtime Optimization Monte Carlo Methods The trends in his publications include predictive modeling for architectural design spaces (2006), energy savings in HPC applications (2009–2016), and innovative tools like IPAS and ARCHER for error detection and runtime optimization. While no explicit scientific awards are mentioned in the scraped text, his work has garnered over 8,991 citations, reflecting significant impact.

• Educational Psychology
• Self-Regulated Learning
• Academic Risk-Taking
• +۳ مورد دیگر

Vanessa Hübner is a Scientific Associate at the Chair of Empirical Educational Research within the Faculty of Humanities at Otto-Friedrich University of Bamberg. She holds a PhD in Educational Research (2025) and an M.Sc. in Empirical Educational Research (2021), with a B.A. in Education (2018). Her work focuses on academic risk-taking, self-regulated learning, and error beliefs in educational contexts. PhD: "Between mistakes and learning potential: An investigation of individual and contextual predictors of students' academic risk-taking" (2025) M.Sc.: Empirical Educational Research (2021) B.A.: Education (2018) Her research explores how error beliefs, teaching quality, and motivational factors influence academic risk-taking in higher education. Publications highlight disparities in risk-taking across gender and socioeconomic groups, the role of webtools in self-regulated learning, and psychometric assessments of risk-taking scales. Current projects include analyzing extracurricular tutoring effects and developing tools like the Open-vhb e-learning course for self-regulated learning. She collaborates with Prof. Dr. Maximilian Pfost and contributes to the University Teaching journal.

Felix Blankenburgمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Neuroimaging
• Somatosensory Processing
• +۵ مورد دیگر

Felix Blankenburg is Professor and Chair of the Neurocomputation and Neuroimaging Unit at the Department of Education and Psychology, Freie Universität Berlin. His research investigates neural mechanisms of perception, cognition, and action using multimodal neuroimaging (fMRI, EEG) and neurostimulation (TMS, tDCS), with emphasis on somatosensory processing, sensory attenuation, and perceptual decision-making within virtual reality environments. His primary research focuses on cognitive neuroscience and neuroimaging, exploring how the brain processes tactile information, integrates multisensory cues, and generates conscious perception. Key areas include Bayesian models of sensory prediction, neural correlates of working memory for tactile stimuli, cross-modal influences (e.g., language on touch), and computational mechanisms of perceptual decisions. His work bridges experimental neuroscience with theoretical frameworks like active inference. Recent publications (2023-2025) reveal strong trends in multimodal integration methodologies, predictive coding applications in somatosensation, and clinical translation through neurostimulation. He pioneers concurrent TMS-fMRI and virtual reality paradigms to probe causal brain mechanisms, with growing emphasis on therapeutic applications for mental health as evidenced by the PREACT research unit. Professor Blankenburg supervises PhD students including: Gianluigi Giannini Guido Caccialupi Jona Förster He serves as principal investigator for the DFG-funded Research Unit 5187 PREACT, developing neuroimaging biomarkers to predict psychotherapy response in non-respondent patients through fMRI-based signatures. The Neurocomputation and Neuroimaging Unit, under his leadership, integrates computational modeling with empirical neuroscience. The team comprises postdocs, PhD students, and research staff collaborating on projects spanning tactile perception, decision neuroscience, and clinical applications of neuroimaging.

Laura Nohrمشاهده پروفایل

پژوهشگر

• Transcultural Clinical Psychology
• Psychotraumatology
• Refugee Mental Health
• +۶ مورد دیگر

Laura Nohr is a Researcher at the Department of Clinical Psychological Intervention within the Faculty of Education and Psychology at Free University of Berlin. Her work focuses on transcultural clinical psychology , refugee mental health , and digital health interventions , with particular attention to social inequality , women's health , and depression . Education: 2021: PhD in Clinical Psychology, University of Münster 2020: Approbation as Licensed Psychotherapist (CBT) 2015: Master of Science in Psychology, Humboldt-Universität zu Berlin 2012: Bachelor of Science in Psychology, Humboldt-Universität zu Berlin Research Interests: Laura’s research explores transcultural explanatory models of mental disorders , digital interventions for refugees , and social determinants of mental health . Her work addresses stigma , help-seeking behaviors , and cross-cultural adaptation of psychological tools. Recent articles emphasize Internet-based interventions for emotional disorders among Arabic- and Farsi-speaking refugees, role conflicts in interpreter mental health, and transcultural comparisons of causal attributions for mental illness. She also investigates microaggressions in therapy and ambulatory care disparities for migrant populations. Scientific Awards: 2023: Research Promotion Award (Elfriede Dietrich Foundation, 6,000 €) 2023: Scholarship to attend DeGPT Annual Meeting 2022: Scholarship for DeGPT Summer School 2017: DGPPN Poster Award Labs & Collaborations: Laura contributes to the I-REACH consortium (Internet-based Refugee Mental Health Care) and collaborates with institutions in Germany, Cuba, and Peru. Her research integrates transcultural psychology with digital health innovations .