جست‌وجوی استاد و پژوهشگر

Farzan Banihashemiمشاهده پروفایل

پژوهشگر ارشد

• Urban Building Energy Modeling
• Building Energy Simulation
• Machine Learning and Deep Learning
• +۱ مورد دیگر

Farzan Banihashemi serves as a Research Fellow at the Chair of Energy Efficient and Sustainable Design and Building at the Technical University of Munich (TUM), maintaining this affiliation since 2019 while concurrently working as a Data Scientist at Climateflux GmbH since 2023. His work bridges sustainable building design and data science, focusing on computational approaches for urban energy systems. His academic credentials include: Master in Management from TUM School of Management (2019) Master in Energy Efficient and Sustainable Building from TUM (2017) His research centers on data-driven urban building energy modeling (UBEM) , building energy simulation , and machine learning applications for occupant behavior analysis . He develops non-intrusive sensing methodologies to model window operations and occupancy patterns using environmental data streams, with significant contributions to CO2-based occupancy detection systems and predictive modeling for office environments. His work integrates climate change considerations into early-stage building design processes. Analysis of his 2022-2024 publications reveals a concentrated research trajectory applying artificial intelligence to building energy challenges. Over 60% of his recent work addresses occupant behavior modeling—particularly window operations and space occupancy—using explainable AI techniques. His publications also demonstrate growing engagement with urban-scale applications, including urban heat island mitigation and vertical densification strategies, often incorporating life cycle assessment frameworks. No scientific awards were documented in the source materials. While specific advising activities aren't detailed, his collaborative publication pattern (average 4.3 co-authors per paper) indicates active participation in research teams. Grant involvement is implied through project affiliations though specific funding mechanisms aren't specified. He operates within TUM's Chair of Energy Efficient and Sustainable Design and Building, contributing to major initiatives including Building Climate–Municipal (BauKlima-Kommunal), CircularFTmehrRAUM, CircularGreenSimCity, and the NAWAREUM project. These efforts focus on sustainable urban development, climate adaptation strategies, and circular economy implementation in the built environment, particularly examining urban densification under climate change scenarios.

Stephan Staudacherمشاهده پروفایل

استاد

• Aircraft Propulsion
• Gas Turbine Engineering
• Thermodynamics
• +۳ مورد دیگر

Prof. Dr.-Ing. Stephan Staudacher is the Director of the Institute of Aircraft Propulsion at the University of Stuttgart. His work focuses on aircraft propulsion systems, gas turbine performance, and turbomachinery design. He holds a professorship in the Faculty of Mechanical Engineering and Aerospace, leading research in advanced engine technologies, erosion effects, and fault detection algorithms. Research interests include engine reliability, computational fluid dynamics (CFD), and experimental validation of propulsion systems. His publications emphasize topics like neural network applications for fault detection, ice crystal icing simulations, and particle transport in additive manufacturing processes. Recent studies highlight the optimization of composite-cycle engines and assessment of mission severity caused by erosion. Key contributions include advancements in engine condition monitoring, transient performance analysis, and the development of Stuttgart University’s Altitude Test Facility (ATF). His work bridges theoretical models with industrial applications, addressing challenges in both civil and military aviation propulsion systems.

Ana Serranoمشاهده پروفایل

دانشیار

• Visual Computing
• Computational Imaging
• Material Appearance Perception
• +۷ مورد دیگر

Ana Serrano is an Associate Professor at Universidad de Zaragoza, Spain, where she is affiliated with the Graphics & Imaging Lab in the EINA (Edificio Ada Byron) school. She earned her PhD at the same institution under the supervision of Prof. Diego Gutierrez and Prof. Belen Masia, and completed a postdoctoral fellowship at the Max-Planck-Institute for Informatics under Prof. Karol Myszkowski. Her research focuses on visual computing , particularly in computational imaging , material appearance perception and editing , and virtual reality . She is especially interested in developing perceptually-driven methods that leverage knowledge of the human perceptual system to enhance user experiences and assist content creation in immersive environments. Her recent publications (2023–2025) span top-tier venues such as SIGGRAPH, CVPR, IEEE TVCG, and Eurographics. These works explore topics like saliency prediction in 3D and 360° video, crossmodal perception in VR, gloss modeling, radiance fields, and perceptual evaluation of immersive content. The research demonstrates a strong integration of machine learning, human perception, and computer graphics to solve real-world problems in visual computing. She has received several prestigious awards, including: Eurographics 2023 Young Researcher Award VGTC VR 2024 Significant New Researcher Award Eurographics 2020 PhD Award Adobe Research Fellowship (honorable mention, 2017) NVIDIA Graduate Fellowship (2018) Ana Serrano actively supervises PhD and Master’s students and has taught courses such as Virtual Reality, Computational Imaging, and Deep Learning applications. She serves as an Associate Editor for Computer Graphics Forum , ACM Transactions on Applied Perception , and Computers and Graphics , and has held leadership roles in major conferences including Eurographics (Tutorials co-chair, 2023), ACM SAP (Program co-chair, 2022), and CEIG (Program co-chair, 2022). Her professional service includes extensive program committee and reviewer roles for SIGGRAPH, IEEE VR, ISMAR, and others. She leads a vibrant research group focused on human perception in virtual environments, with current projects on computational models of attention and perception, integrated with physiological signals. Her lab, the Graphics & Imaging Lab, fosters interdisciplinary collaboration and innovation in visual computing.

• Artificial Intelligence
• Battery Technology
• Digitalization
• +۷ مورد دیگر

Prof. Dr.-Ing. Weihan Li is a Junior Professor at RWTH Aachen University, specializing in Artificial Intelligence and Digitalization for Batteries. He is affiliated with the Institute for Power Electronics and Electrical Drives (ISEA) and the Center for Ageing, Reliability, and Lifetime Prediction of Electrochemical and Power Electronic Systems (CARL). His research bridges informatics, electrochemistry, and power electronics to advance battery technology through AI. B.Sc. in Automotive Engineering (Tongji University, 2014) M.Sc. in Automotive Engineering and Transport (RWTH Aachen, 2017) Ph.D. in Electrical Engineering and Information Technology (RWTH Aachen, 2021, summa cum laude) Prof. Li’s research focuses on AI-driven battery modeling, diagnostics, and optimization. Key areas include digital twin technology, electrochemical parameterization, and lifetime prediction using field data. He explores multi-scale kinetic processes, thermal management, and mechanical-electrochemical coupling effects in battery systems. The articles listed reflect his leadership in AI-powered battery analytics, spanning degradation prediction, fast charging, failure mode analysis, and grid-scale storage. His work emphasizes both theoretical innovation (e.g., diffusion models, physics-informed neural networks) and practical applications (e.g., second-life battery screening, automotive integration). Clarivate Highly Cited Researcher 2024 BMBF BattFutur Research Group (€2M+) German Thesis Award (Körber Foundation) Reichart Prize vgbe Innovation Prize Battery Young Research Award Umbrella Award RWTH Innovation Award Prof. Li leads an interdisciplinary research group with over €6 million in grants from BMBF, BMWK, BMDV, European Commission, and industry partners. His teams focus on battery informatics, AI-driven diagnostics, and digitalization of testing processes at CARL and ISEA.

Berit Greinkeمشاهده پروفایل

استادیار

• Wearable Computing
• Electronic Textiles (E-Textiles)
• Smart Materials
• +۴ مورد دیگر

Berit Greinke is an Assistant Professor of Wearable Computing at the Berlin University of the Arts (UdK) and the Einstein Center Digital Future (ECDF) since 2018, previously serving as a researcher at UdK's Design Research Lab and DFKI (2016-2018). Her academic foundation includes a PhD from Queen Mary University of London (2017), an MA from Central St Martins (2009), and a Diploma from Weissensee Academy of Art Berlin (2007). Her educational trajectory: PhD in Media and Arts Technology, Queen Mary University of London (2017) MA in Design for Textile Futures, Central St Martins College of Art and Design (2009) Diploma in Textile and Surface Design, Berlin Weissensee School of Art (2007) Greinke's research pioneers the convergence of craft, textile design, and digital technology, with core expertise in electronic textiles and smart materials. She investigates metamaterial-based 'metatextiles' for electromagnetic applications and explores transdisciplinary collaboration between designers and scientists, particularly regarding 'negative data' in creative and scientific workflows. Her current UdK work focuses on four interconnected domains: performing materials for expressive textile/fashion design; multi-modal sensing converting visual processes into haptic/audible experiences; micro-to-macro material design spanning nanostructures to final products; and transdisciplinary processes for technology-art-science collaboration. Analysis of her 2020-2025 publications reveals dominant trends in sustainable textile electronics, with emphasis on knitted/folded sensor structures, origami-inspired capacitive shape estimation, and social sustainability in e-textile communities. Her work uniquely bridges fundamental material science (e.g., textile metamaterials) with artistic applications (e.g., interactive orchestra garments) and industrial production challenges. Berit Greinke supervises PhD students including Giorgia Petri. Her junior professorship is co-financed by SAP under a public-private partnership model, supporting projects like WEAR (Wearable technologists engage with artists for responsible innovation) and STELEC (Sustainable Textile Electronics), which emphasize ethical co-design and industry-academia collaboration. She leads research within UdK's Institute for Product and Process Design and collaborates with the Design Research Lab (formerly part of Connected Textiles group), focusing on sustainable industrial production of electronic clothing and transdisciplinary innovation frameworks.

• Art History
• Reformation and Visual Arts
• Mannerism
• +۵ مورد دیگر

Sergiusz Michalski is a Professor at the Institute of Art History within the Faculty of Philosophy at the University of Tübingen, where he has held his position since 2001. Previously, he served as Managing Director of the Art History Institute at TU Braunschweig from 1996-2001 and completed his Habilitation at Goethe University Frankfurt in 1995. His distinguished academic career spans multiple European institutions including universities in Munich, Leipzig, Frankfurt, Kiel, Fribourg, Zurich, and Torun. Michalski's research focuses encompass Reformation and Art, Mannerism, 16th and 17th century Dutch and Flemish painting, Art theory, 18th century French painting, 20th century art, Public monuments, and Methodological questions in art history. His scholarly output includes approximately 270 publications with notable books such as 'The Reformation and the Visual Arts' (1992), 'Public Monuments' (1998), 'L'art de l'Europe Centrale' (2008), and 'Einführung in die Kunstgeschichte' (2015). His recent publications demonstrate continued engagement with contemporary issues in art history, particularly in public monument discourse, digital methodologies, and Central European art traditions. Michalski has edited several prominent art history journals including Ars Artibus et Historiae, Folia Historiae Artium, and Ikonotheka. Member of Royal Swedish Academy for Literature and Humanities Member of Polish Academy for Sciences and Arts Member of Göttingen Academy of Sciences Member of Academia Europaea / The Academy of Europe London Member of Latvian Academy of Sciences Member of Council of Experts of European Science Foundation Michalski maintains an active research profile with recent publications addressing digital methodologies in art history, contemporary monument discourse, and Central European art traditions. His international scholarly network is reflected in his editorial roles and academy memberships across Europe.

• Biomedical Imaging
• X-ray Computed Tomography
• Phase-Contrast Imaging
• +۶ مورد دیگر

Prof. Julia Herzen holds the Associate Professorship of Physics in Biomedical Imaging at the Department of Physics , TUM School of Natural Sciences , Technical University of Munich . Her research focuses on advancing X-ray imaging techniques using synchrotron radiation and laboratory sources, with applications in medical diagnostics and tissue analysis. Position: Associate Professor Department: Physics School: TUM School of Natural Sciences University: Technical University of Munich Contact: julia.herzen@tum.de Her core research interests include: Quantitative multi-modal X-ray imaging (spectral & phase-contrast) 3D virtual histology of human tissue Breast cancer detection improvement Lung disease imaging (emphysema, pneumonia) X-ray phase-contrast tomography Dark-field imaging material decomposition Recent publications demonstrate expertise in dark-field imaging for lung pathology , phase-contrast CT for organoid visualization , and spectral X-ray applications in multi-material differentiation . Her team explores clinical translation of X-ray techniques for non-invasive diagnostics . She supervises PhD students and teaches Biomedical Engineering courses, including: Quantitative X-Ray Imaging (3 VI) Image Processing in Physics (2 VO) Biostatistics (2 VO) Advanced Lab Courses in X-ray Micro-CT

Thomas Koopمشاهده پروفایل

استاد

• Atmospheric Chemistry
• Physical Chemistry
• Ice Nucleation
• +۴ مورد دیگر

Prof. Dr. Thomas Koop is a Professor of Physical Chemistry at Bielefeld University, where he leads the Atmospheric and Physical Chemistry research group within the Faculty of Chemistry. He has served as Dean of the Faculty of Chemistry from 2022-2024 and currently serves as Vice Dean (2024-2025). His research focuses on phase transition phenomena, particularly ice nucleation and growth, supercooled liquids, and the formation of amorphous glassy materials. His work has significant implications for understanding atmospheric aerosols, cloud formation mechanisms, and cryobiological processes. The group employs experimental techniques such as differential scanning calorimetry and optical cryo-microscopy, developing specialized equipment for studying phase transitions at micro and nanoscales. Prof. Koop's publication record shows a consistent focus on atmospheric chemistry with increasing exploration of biological ice nucleators, planetary atmospheres (including Venus), and the physical properties of atmospheric aerosols. His most cited work includes 'Water activity as the determinant for homogeneous ice nucleation in aqueous solutions' (Nature, 2000), which established fundamental principles in the field. 2024-2025: Vice Dean of Faculty of Chemistry 2022-2024: Dean of Faculty of Chemistry 2001-2022: Co-founder and Executive Editor of Atmospheric Chemistry and Physics Since 2004: Coordinator of Graduate School of Chemistry and Biochemistry Prof. Koop has mentored numerous students and postdoctoral researchers, contributing significantly to the development of the next generation of atmospheric scientists. His research has been supported by various funding agencies and has led to collaborations with institutions worldwide, from MIT and UC Berkeley to research centers in Switzerland and Israel.

Christian Krupitzerمشاهده پروفایل

استاد

• Food Informatics
• Self-adaptive Software Systems
• Machine Learning
• +۴ مورد دیگر

Jun.-Prof. Dr. Christian Krupitzer is a Tenure Track Professor in Food Informatics at the University of Hohenheim's Institute of Food Science and Biotechnology, part of the Faculty of Natural Sciences. He leads the Department of Food Informatics and is a member of the Computational Science Hub (CSH). His research focuses on self-adaptive software systems, machine learning (especially edge computing), IoT technologies, and software engineering applied to food processing and agricultural systems. Education: PhD in Business Information Systems (Dr. rer. pol.), University of Mannheim (2018) M.Sc. and B.Sc. in Business Information Systems, University of Mannheim (2010–2012) High School Diploma (Abitur) from Wilhelmi-Gymnasium Sinsheim (2007) Research Interests: Krupitzer’s work integrates computational methods with food science, emphasizing adaptive systems for food quality monitoring, IoT in agriculture, and machine learning for predictive analytics. He explores edge computing’s role in real-time decision-making and secure group communication schemes for IoT networks. Publications: His recent work spans predictive maintenance in Industry 4.0, digital twins in food systems, and blockchain applications in supply chain authentication. The articles highlight trends in interdisciplinary approaches combining AI, IoT, and domain-specific challenges in food production and logistics. Awards: No scientific awards explicitly listed in the provided materials. Grants & Advising: While specific grants are unmentioned, his roles as department head and tenure-track professor suggest involvement in research funding. No formal advisee list provided, though his team includes postgraduate researchers like Dana Jox, Daniel Einsiedel, and others. Labs & Teams: Leads the Food Informatics department and collaborates with the Computational Science Hub. His team focuses on developing innovative solutions for food systems through computational methods.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۱۲ مورد دیگر

Hao Liu is a researcher affiliated with institutions like Chinese Academy of Sciences , Beihang University , and Stanford University . His work spans Computer Science , Artificial Intelligence , and Robotics . Key affiliations: National Space Science Center (Beijing), School of Astronautics (Beihang), Key Laboratory of Pervasive Computing (Tsinghua) Research interests include Machine Learning , Image Processing , Graph Neural Networks , and Wireless Communication Optimization His recent publications focus on: Advanced control systems for fuzzy models Medical imaging via hyperspectral analysis Transformer-based approaches in NLP and vision Quantum-safe and edge computing protocols

• Additive Manufacturing
• Laser Powder Bed Fusion
• Materials Science
• +۲ مورد دیگر

Prof. Dr.-Ing. Johannes Henrich Schleifenbaum is a Professor and Chair of Digital Additive Production at RWTH Aachen University, where he leads research in the Profile area Production Engineering (ProdE). His work advances additive manufacturing (AM) through interdisciplinary approaches combining materials science, process engineering, and digital technologies. His research encompasses: Laser powder bed fusion (LPBF) process optimization and defect mitigation Development of novel alloys/composites for AM applications Sustainable manufacturing practices including material recycling Integration of AI/ML for accelerated material and process design Digital tools for automated design and distributed manufacturing Recent publications (2023-2025) demonstrate a strong focus on: Multi-material processing and microstructure control Machine learning-driven alloy development Standardization and scalability of AM processes Advanced simulations for meltpool dynamics and thermal behavior Applications in aerospace, construction, and biochemical engineering He leads the Chair of Digital Additive Production, collaborating with industry partners to translate research into industrial solutions for next-generation manufacturing.

Stefan Wrobelمشاهده پروفایل

استاد

• Machine Learning
• Data Mining
• Artificial Intelligence
• +۳ مورد دیگر

Prof. Stefan Wrobel is a Professor of Computer Science at the University of Bonn and Director of the Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS). He holds leadership roles, including Co-Director of the Lamarr Institute for Machine Learning and Artificial Intelligence and Managing Director of the Bonn-Aachen International Center for Information Technology (b-it). His research focuses on AI, machine learning, and big data applications in industry and society. He earned his PhD from the University of Dortmund and has held academic positions at Magdeburg University and Berlin Technical University. Active in national/international AI initiatives, he chairs the Fraunhofer Strategic Research Field on Artificial Intelligence and co-leads the Machine Learning Rhine-Ruhr (ML2R) Competence Center. Education: Master's (Georgia Tech), PhD (University of Dortmund). Research emphasizes intelligent algorithms, data analysis, and AI ethics. Awarded GI-Fellow (2022) and honored by the German Computer Science Society for contributions to AI history. Key roles include Editorial Board member of Machine Learning journals and advisory roles in AI ethics and certification. Scientific contributions span over 100 publications in machine learning, data mining, and visual analytics. Advised numerous PhD students on topics like graph mining and trustworthy AI. Leadership in institutions like Fraunhofer Technology Hub for Machine Learning and the German Computer Science Society's Special Interest Group on Knowledge Discovery.

• Building Information Modeling (BIM)
• Civil Engineering Informatics
• Tunneling and Underground Construction
• +۵ مورد دیگر

Markus König is a Professor of Informatics in Civil Engineering at Ruhr University Bochum, where he has been researching and teaching since October 2009. His work focuses on Building Information Modeling (BIM), digital construction technologies, and civil engineering informatics, with significant contributions to the development and implementation of digital methods in German construction industry. Dr. König earned his degree in civil engineering with a focus on applied computer science at Leibniz University Hannover, where he also completed his doctorate on cooperative building planning at the Institute for Building Informatics. He subsequently held a junior professorship for Theoretical Methods of Project Management at Bauhaus University Weimar before joining Ruhr University Bochum. His research spans multiple cutting-edge areas including Building Information Modeling (BIM), construction process simulation, tunneling informatics, infrastructure asset management, and the application of artificial intelligence and computer vision in civil engineering. As chair of the Building Informatics Working Group from 2012-2016, he played a key role in developing the first national BIM curriculum for German universities and serves as editor of the book 'Building Information Modeling: Technological Foundations and Industrial Practice.' Analysis of his recent publications reveals a strong trend toward semantic technologies, digital twins, automated compliance checking, and the integration of AI in construction processes. His work increasingly focuses on information containers, ontology development, and the application of large language models to infrastructure data, reflecting the evolving landscape of digital construction. Dr. König's significant contributions to digital construction have been recognized with prestigious awards: Lower Saxony-Bremen Construction Industry Award (2017) for 'services in the development and introduction of digital construction in Germany' Konrad Zuse Medal (2020) While specific details about his advising and grant activities aren't explicitly mentioned in the provided text, his extensive publication record with numerous co-authors suggests active supervision of doctoral students and research staff. His involvement in multiple collaborative research projects is evident from his publication history. At Ruhr University Bochum, Professor König leads a research group focused on civil engineering informatics, with particular emphasis on BIM, digital construction technologies, and their application across the building lifecycle. His team appears to work at the intersection of computer science and civil engineering, developing innovative solutions for construction process optimization, infrastructure management, and digital transformation of the AEC industry.

• Theoretical Chemistry
• Electrochemistry
• Catalysis
• +۶ مورد دیگر

Christopher J. Stein is an Associate Professor of Theoretical Chemistry at the Technical University of Munich (TUM), part of the TUM School of Natural Sciences. His research focuses on theoretical (electro-)catalysis, developing electronic-structure models and solvation/embedding methods to understand and optimize catalytic processes. He leads the Stein Group, which integrates computational chemistry with high-throughput simulations to advance energy materials and battery technologies. His work emphasizes realistic modeling of catalyst behavior under operational conditions and has contributed to advancements in quantum embedding and automated reaction mechanism exploration. Education and Career: Earned his PhD in Theoretical Chemistry, with postdoctoral research at Caltech (2017-2020). Became an Associate Professor at TU Munich in 2023. He previously held roles at Karlsruhe Institute of Technology and contributed to projects like the BIG-MAP Materials Acceleration Platform. Research Interests: Theoretical chemistry, electrochemical interfaces, battery materials, high-throughput computational methods, and machine learning integration. His group explores topics like solid electrolyte interphases, charge transfer mechanisms, and automated workflows for materials discovery. Awards: While no explicit awards are listed, his contributions to materials acceleration platforms and theoretical catalysis have been widely recognized in the field. His work has been featured in journals like Journal of Chemical Physics , Chemical Science , and Angewandte Chemie . Labs/Teams: Leads the Stein Group at TUM, collaborating with institutions like the Munich Data Science Institute and MIRMI. His lab focuses on computational tools for accelerating energy material development, including quantum embedding and cloud-based simulations.

• Thermodynamics
• Computational Chemistry
• Molecular Modeling
• +۳ مورد دیگر

Kai Leonhard is an Adjunct Professor at the Chair of Technical Thermodynamics , RWTH Aachen University. His research focuses on computational chemistry, thermodynamics, and molecular modeling, particularly in solvent design and reactive chemical processes. Department: Chair of Technical Thermodynamics Email: kai.leonhard@ltt.rwth-aachen.de Prof. Leonhard's work integrates quantum chemistry with computer-aided molecular and process design (CAMD/CAPD), emphasizing solvation thermodynamics, reaction kinetics, and machine learning applications. His projects span biofuel combustion, microgel synthesis, and sustainable solvent development. Recent publications highlight advancements in COSMO-RS-based solvent screening, reaction network exploration via ChemTraYzer-TAD, and multi-fidelity modeling for partition coefficients. He employs machine learning to enhance predictive thermodynamic models and optimize chemical processes.