جست‌وجوی استاد و پژوهشگر

Mark Heitmannمشاهده پروفایل

استاد

• Artificial Intelligence in Marketing
• Social Media Marketing
• Brand Management
• +۵ مورد دیگر

Prof. Mark Heitmann is a Professor of Marketing & Customer Insight at the University of Hamburg Business School. He holds a visiting appointment at Nova School of Business and Economics. His research focuses on AI-driven marketing strategies, social media analytics, brand equity, and consumer decision-making. He has held academic roles at institutions including the University of St. Gallen and Christian-Albrechts-University in Kiel before joining Hamburg in 2011. Academic Career: Holds a PhD (2004) and post-doctoral Habilitation (2007) from the University of St. Gallen. Visiting researcher at Columbia University and the Max Planck Institute for Human Development. Research Interests: Applications of artificial intelligence in marketing Social media and digital transformation Ethical consumer behavior Brand self-expression and visual design Marketing technology (MarTech) innovations Key Achievements: Over 20 peer-reviewed publications in top journals like Journal of Marketing Research and Harvard Business Review . Award-winning research includes the MSI/H. Paul Root Award and IJRM-EMAC Best Article Award. Active in translating research into scalable commercial solutions through software-as-a-service ventures. Team & Collaborations: Leads a research team including M.Sc. candidates Sammar Rath, Julia Rosada, Maximilian Witte, Tijmen Jansen, Claus Hegmann-Napp, and Magdalena Heynicke. Engages in interdisciplinary projects with industry partners.

Ignacio Ojea Quintanaمشاهده پروفایل

استادیار

• Social Epistemology
• Philosophy of Data Science
• Ethics of Autonomous Decision Making
• +۴ مورد دیگر

Ignacio Ojea Quintana serves as Assistant Professor at Ludwig Maximilian University of Munich's Faculty of Philosophy, Philosophy of Science and Religious Studies within the Chair of Philosophy of Science. He joined LMU in 2022 after a three-year research fellowship at the Australian National University's School of Philosophy. His academic foundation includes a PhD in Philosophy from Columbia University (2019), supervised by Philip Kitcher with focus on formal social epistemology, and prior Masters/BA degrees in Philosophical Logic from the University of Buenos Aires where he collaborated with the Buenos Aires Logic Group. Ojea Quintana's research employs formal methodologies to examine digital technologies' impact on knowledge organization across scientific and public spheres. His work intersects Social Epistemology , Philosophy of Data Science , and Autonomous Systems Ethics , with significant contributions to social media network analysis of controversial movements. Current projects analyze Twitter dynamics in racial justice movements, ethical constraints in AI decision systems, and consensus formation in scientific modeling. His 2021-2022 publications reveal an interdisciplinary trajectory bridging philosophy, computer science, and social sciences. Key trends include computational analysis of online discourse, formal modeling of group rationality under uncertainty, and ethical frameworks for AI systems. Works appear in high-impact venues including Nature Humanities and Social Sciences Communications and the AAAI/ACM Conference on AI, Ethics, and Society. Ojea Quintana maintains active collaborations with the "Humanising Machine Intelligence" initiative (formerly at ANU) and the Buenos Aires Logic Group. His research program demonstrates sustained engagement with technology's societal implications through formal modeling approaches and empirical digital trace analysis.

Toby Jia-Jun Liمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Artificial Intelligence
• Machine Learning
• +۶ مورد دیگر

Toby Jia-Jun Li is an Assistant Professor in the Department of Computer Science and Engineering at the University of Notre Dame, where he leads the SaNDwich Lab. He also serves as the Director of the Human-Centered Responsible AI Lab in the Lucy Family Institute for Data & Society and is a Faculty Fellow at the Institute for Educational Initiatives (IEI). Previously, he was affiliated with Carnegie Mellon University's Human-Computer Interaction Institute (HCII) and GroupLens Research. Dr. Li's research spans the intersection of Human-Computer Interaction (HCI), End-User Software Engineering, Machine Learning (ML), and Natural Language Processing (NLP), with recent work focusing on addressing societal challenges in the future of work through human-AI collaborative approaches. His work has resulted in over 40 publications at premier venues including CHI, UIST, CSCW, ACL, and ICSE, with 8 papers winning Best Paper or Honorable Mention awards. His recent publications demonstrate a strong focus on human-AI collaboration across various domains, including code understanding, privacy, accessibility, and creative tools. The work shows a trajectory toward increasingly sophisticated integration of human-centered design with AI capabilities, particularly using large language models to enhance human productivity and address societal challenges. Google Research Scholar Award recipient Recipient of Yahoo! Fellowship ($100,000/year) Best Paper Award at UIST 2020 Best Paper Honorable Mention Award at CHI 2021 Best Paper Award at CSCW 2024 Best Paper Award at CHI 2025 Dr. Li actively mentors Ph.D. students and has established collaborations with Google, Microsoft Research, IBM Research, Adobe, Verizon, and J.P. Morgan. His research has been supported by NSF, Google Research Scholar Program, AnalytiXIN Initiative, Yahoo! InMind project, and J.P. Morgan. He is currently recruiting Ph.D. students and undergraduate researchers for his SaNDwich Lab, which focuses on developing interactive systems to empower individuals to create, configure, and extend AI-powered computing systems.

Mathias Christmannمشاهده پروفایل

استاد

• Organic Chemistry
• Natural Product Synthesis
• Organocatalysis
• +۶ مورد دیگر

Prof. Dr. Mathias Christmann is a faculty member at the Institute of Chemistry and Biochemistry, Freie Universität Berlin , leading the research group in Organic Chemistry . His work focuses on strategic and methodological challenges in synthetic chemistry, particularly in total synthesis, organocatalysis, and renewable resource transformations. Position: Professor Contact: mathias.christmann@fu-berlin.de Location: Takustr. 3, Room 24.16, 14195 Berlin Research Interests include: Natural product-inspired small molecule synthesis for biological pathway modulation Minimizing C-C bond formations through selective functionalization of terpene building blocks Organocatalytic and metal-catalyzed reactions in multistep sequences Flow chemistry applications for scalable and sustainable synthesis Biological evaluation of TRPC channel agonists/antagonists for cancer therapy Publication Trends highlight expertise in total synthesis of complex terpenoids, organocatalysis for stereocontrolled reactions, flow chemistry for late-stage transformations, and TRPC4/5 channel modulation in renal cancer studies. His group pioneers asymmetric desymmetrization , photo-oxidation protocols , and electrosynthesis methods with minimal reagent waste. Advisees include PhD candidates Jan-Hendrik Dickoff , Mayar Elbendary , Nadine Kreidt , Tobias Olbrisch , Kamar Shakeri , and Zhen Wang , focusing on terpene-based drug discovery and catalytic reaction design.

Vincent Fortuinمشاهده پروفایل

استادیار

• Bayesian Deep Learning
• Uncertainty Quantification
• Probabilistic Inference
• +۵ مورد دیگر

Dr. Vincent Fortuin is a tenure-track Assistant Professor at the Technical University of Munich (TUM) and a research group leader at Helmholtz AI in Munich. He leads the Efficient Learning and Probabilistic Inference for Science (ELPIS) group and holds multiple prestigious fellowships including the Branco Weiss Fellowship. His academic affiliations include the TUM School of Computation, Information and Technology, the Konrad Zuse School of Excellence in Reliable AI, and the Munich Center for Machine Learning. Dr. Fortuin earned his BSc in Molecular Life Sciences from the University of Hamburg (2012-2015), followed by an MSc in Computational Biology and Bioinformatics from ETH Zürich (2015-2017), where he received the ETH Excellence Scholarship and the Willi Studer Prize. He completed his PhD in Machine Learning at ETH Zürich (2017-2021) under the supervision of Gunnar Rätsch and Andreas Krause, supported by a Swiss Data Science Center PhD Fellowship. Prior to joining TUM, he was a Research Fellow at St. John's College, University of Cambridge (2022-2023). His research focuses on the intersection of Bayesian statistics and deep learning, specifically developing methods for more robust, data-efficient AI systems with reliable uncertainty estimates. His work addresses critical limitations in standard deep learning approaches, particularly their tendency to be overconfident in predictions and require large datasets for training. He investigates better priors and more efficient inference techniques for Bayesian deep learning, deep generative modeling, meta-learning, and PAC-Bayesian theory, with applications in scientific and biomedical domains. Dr. Fortuin's recent publications demonstrate a consistent focus on improving uncertainty quantification in deep learning systems, with increasing emphasis on practical applications in scientific contexts. His work spans from theoretical foundations of Bayesian deep learning to practical implementations in protein design, materials science, and medical applications. A notable trend is his exploration of how to make Bayesian methods more scalable and applicable to modern large-scale AI systems while maintaining theoretical guarantees. Branco Weiss Fellowship (2023) St John's College Research Fellowship (2022) Swiss National Science Foundation Postdoc.Mobility Fellowship (2022) Swiss Data Science Center PhD Fellowship (2018) ETH Excellence Scholarship (2015) Willi Studer Award (2018) Dr. Fortuin actively supervises PhD and Master's students through his ELPIS research group at Helmholtz AI. He serves as a regular reviewer and area chair for major machine learning conferences and is an action editor for TMLR. He co-organizes the Symposium on Advances in Approximate Bayesian Inference (AABI) and the ICBINB initiative, demonstrating his commitment to advancing the field through community building. His research group receives funding from multiple sources including Helmholtz AI, the Branco Weiss Fellowship, and collaborations with international institutions. Dr. Fortuin leads the Efficient Learning and Probabilistic Inference for Science (ELPIS) group at Helmholtz AI, which focuses on fundamental machine learning research motivated by real-world scientific problems. The group collaborates extensively with researchers across Helmholtz centers and international institutions, particularly in biomedical applications where reliable uncertainty estimates are crucial.

Yolanda Gilمشاهده پروفایل

استاد پژوهشی

• Knowledge capture
• Semantic Workflows
• Ontology Tools
• +۷ مورد دیگر

Dr. Yolanda Gil is a Research Professor in Computer Science and Spatial Sciences at the University of Southern California, where she serves as Principal Scientist and Senior Director for Strategic Initiatives in Artificial Intelligence and Data Science at the Information Sciences Institute (ISI). She is also the Director of AI and Data Science Initiatives in the Viterbi School of Engineering and leads the USC Center for Knowledge-Guided Interdisciplinary Data Science (CKIDS). Dr. Gil received her Licenciatura in Computer Science from the Polytechnic University of Madrid and her M.S. and Ph.D. in Computer Science from Carnegie Mellon University, with a focus on artificial intelligence and cognitive science. Her research focuses on developing AI approaches that use knowledge to accelerate scientific discovery processes. Her key research interests include knowledge capture and representation, semantic workflows, ontology tools, scientific discovery methods, task-based collaboration, provenance tracking, knowledge networks, reproducibility in science, and machine learning for data analysis. She collaborates with scientists across multiple domains to improve how scientific knowledge is created, shared, and used. Dr. Gil's work has significant impact across multiple scientific domains including climate science, neuroscience, and omics research. Her projects demonstrate her commitment to building knowledge-guided systems that transform how scientists conduct research. She has pioneered approaches to capture the provenance of scientific experiments and to automate the analysis of complex scientific data. Fellow of the Association for Computing Machinery (ACM) Fellow of the Association for the Advancement of Science (AAAS) Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) 24th President of the Association for the Advancement of Artificial Intelligence Co-chair of the CRA/AAAI 20-Year Artificial Intelligence Research Roadmap for the US Initiator and leader of the W3C Provenance Group that resulted in a widely-used standard for web trust As an educator and leader, Dr. Gil directs the Data Science Program in Computer Science and serves as Co-Director of multiple joint MSc programs including Communication Data Science, Spatial Data Science, Environmental Data Science, Public Policy Data Science, and Healthcare Data Science. She also leads the new dual degree USC-Tsinghua University on Communication Data Science. Her leadership extends to mentoring numerous students and researchers in AI and data science. Through the USC Center for Knowledge-Guided Interdisciplinary Data Science (CKIDS), Dr. Gil organizes DataFest events each semester, fostering collaboration and innovation in data science across disciplines.

Elena Simperlمشاهده پروفایل

استاد

• Human-centric AI
• Knowledge Graphs
• Knowledge Engineering
• +۷ مورد دیگر

Elena Simperl is a Professor of Computer Science and Deputy Head of Department for Enterprise and Engagement at King's College London's Department of Informatics. She co-directs the King's Institute for Artificial Intelligence and serves as Director of Research for the Open Data Institute. As a Hans Fischer Senior Fellow at the Technical University of Munich's Institute for Advanced Study, she leads the Trustworthy Knowledge Graphs focus group and contributes to advancing human-centric AI research across European institutions. Professor Simperl obtained her doctoral degree in Computer Science from the Free University of Berlin and her diploma from the Technical University of Munich. Prior to joining King's, she held academic positions in Germany, Austria, and at the University of Southampton, and was a Turing Fellow. Her career trajectory demonstrates consistent leadership in bridging academic research with practical applications in data ecosystems. Her research sits at the critical intersection of AI and social computing, focusing on human-centric approaches to building sociotechnical systems that integrate data, algorithms, and human capabilities. She investigates how to make knowledge engineering more accessible, how to leverage collective intelligence for data quality improvement, and how to design participatory AI systems that address societal challenges like misinformation. Her work spans knowledge graphs, semantic technologies, crowdsourcing, and open data, with particular emphasis on the social dimensions of data-intensive systems and the governance frameworks needed for trustworthy AI deployment. Analysis of her recent publications reveals a strong evolution toward integrating large language models with traditional knowledge engineering practices while maintaining human oversight. There's a clear trajectory from foundational work on knowledge representation toward increasingly applied research addressing real-world challenges in media ecosystems, citizen science, and data governance, with growing attention to policy implications of AI technologies. Fellow of the British Computer Society Fellow of the Royal Society of Arts Hans Fischer Senior Fellow at TUM-IAS (2023) Ranked among top 100 most influential scholars in knowledge engineering of the last decade Included in Women in AI 2000 ranking Professor Simperl has led 14 major European and national research projects totaling millions in funding, including MediaFutures (a Horizon 2020 program tackling online misinformation), QROWD, ODINE, Data Pitch, and ACTION. She currently co-chairs the Croissant working group in ML Commons developing data standards for AI, and serves as president of the Semantic Web Science Association. Her research has directly influenced the development of data ecosystems supporting startups and citizen science initiatives across Europe, demonstrating exceptional ability to translate theoretical advances into practical impact. As Director of Research at the Open Data Institute, she oversees initiatives connecting data entrepreneurs with artists and civic organizations. Her leadership in the MediaFutures project established a data-driven innovation hub that supported 51 startups/SMEs and 43 artists through three open calls, creating a sustainable model for arts-technology collaborations addressing media challenges. Her work with the ODINE project helped create a European ecosystem for data-driven startups, demonstrating her commitment to building practical applications of open data principles.

Yangruibo Dingمشاهده پروفایل

استادیار

• Software Engineering
• Large Language Models
• Agentic Systems
• +۷ مورد دیگر

Yangruibo Ding is an incoming Assistant Professor in the Department of Computer Science at the University of California, Los Angeles (UCLA), and currently serves as a Postdoctoral Scientist at AWS Agentic AI. He has held significant research positions at Google DeepMind, Amazon AWS AI Labs, and IBM Research, establishing himself as a leading researcher in software engineering with a focus on large language models for code. His research focuses on developing large language models (LLMs) and agentic systems for software engineering. He specializes in training LLMs with advanced symbolic reasoning capabilities for debugging, testing, program analysis, and verification. His work aims to build efficient, collaborative agentic systems for complex software development and maintenance tasks, with particular emphasis on code generation, vulnerability detection, and execution-aware pre-training techniques. Dr. Ding's publication record reveals a strong trajectory toward enhancing code intelligence through comprehensive semantics reasoning and self-refinement approaches. His research spans multiple dimensions of software engineering including code completion, vulnerability detection, model evaluation, and cross-file context understanding, with applications across various programming languages and development environments. Dr. Ding has received numerous prestigious awards recognizing his contributions to the field: IBM Ph.D. Fellowship Award (2022-2024) ACM SIGSOFT Distinguished Paper Award (2023) IEEE TSE Best Paper Award Runner-up (2022) Ph.D. Service Award, Columbia CS (2025) NSF Student Travel Award for ESEC/FSE'23 (2023) ACM SIGSOFT CAPS Travel Grant (2023) NSF Travel Award for ICSE'22 (2022) As he establishes his research group at UCLA, Dr. Ding is actively seeking students with strong coding skills and experience in large language models, program analysis, verification, or security. He serves on program committees for major conferences including ICSE (2026), ASE (2024, 2025), and ESEC/FSE Artifacts Track (2023), and regularly reviews for top-tier conferences and journals in AI and software engineering. His research is conducted through collaborations with leading industry teams including AWS Agentic AI, Google DeepMind's Learning4Code team, and IBM Research's AI for Code team, creating a robust network of industry-academia partnerships that drive innovation in software engineering research.

Michael Gröschelمشاهده پروفایل

استاد

• Business Process Management
• Digital Transformation
• Business Models
• +۳ مورد دیگر

Prof. Dr. Michael Gröschel is a Professor of Business Informatics at the Faculty of Computer Science, Mannheim University of Technology. His expertise spans Business Process Management (BPMN, Process Mining), Digital Transformation, and innovative Business Models. He teaches courses on BPM, project management, and e-business, often collaborating with industry clients through student projects. As a consultant, he specializes in BPMN training and IT-driven business strategy. His work emphasizes practical applications of IT tools like RPA and low-code platforms. Recent publications focus on RPA bot performance evaluation, AI in automotive trade, and business model-IT alignment. Prof. Gröschel’s research bridges academic insights with real-world challenges, particularly in leveraging technology for business innovation. He has authored books and articles on business intelligence tools, mobile business strategies, and digital customer care. His consulting services include executive coaching for academic career advancement and enterprise IT management best practices. Office: Building A, Room 007c | Phone: +49 621 292-6764 | Professional website available for further engagement opportunities.

• Computer Science
• Software Engineering
• Artificial Intelligence
• +۵ مورد دیگر

Dongwoo Kim is a researcher affiliated with Hanyang University, ERICA Campus (Department of Electronics and Communication Engineering) and has previously collaborated with institutions like POSTECH , Chungnam National University , and Microsoft . His work spans interdisciplinary domains in Computer Science and Engineering . Hanyang University, ERICA Campus - Department of Electronics and Communication Engineering POSTECH - Power Analog Electronics & Semiconductor Devices Lab Microsoft Chungnam National University Kim's research focuses on formal verification of automotive control software, deep learning applications in environmental monitoring, 3D modeling for indoor positioning, and machine learning for signal processing. His recent publications highlight advancements in graph neural networks (GNNs), including analyzing oversmoothing and gradient dynamics, as well as developing geometric vision-language models with domain-agnostic encoders. His 15 most recent articles (2023-2025) address topics like: Optimizing hybrid electric vehicle engine performance 3D modeling for indoor localization GNN training stability UAV-based environmental monitoring Algorithm difficulty prediction for programming problems Millimeter-wave antenna design Kim collaborates with researchers in software engineering , signal processing , and environmental science domains. His work intersects formal methods , applied machine learning , and embedded systems research.

• Information Systems
• Data Management
• Semantic Web
• +۵ مورد دیگر

Thomas Riechert is a Professor at the Leipzig University of Applied Sciences (HTWK Leipzig), specifically within the Faculty of Computer Science and Media. He serves as Dean of Media Informatics, Chairman of the Media Informatics Study Commission, and Academic Advisor for Media Informatics. Additionally, he is a Member of the Faculty Council, Faculty representative in the IT committee, and Library Commission. He also acts as Spokesperson of the Institute of Computer Science at the HTWK. Appointed in 2014 in the field of information systems and data management, Riechert holds a doctorate from the University of Leipzig (2012, magna cum laude) and graduated as a computer scientist from TU Dresden in 2000. Professor Riechert's research focuses on information systems, data management, Semantic Web technologies, knowledge engineering, and Linked Data. His work bridges computer science with digital humanities, particularly in creating knowledge graphs for historical research. He has made significant contributions to RDF vocabulary management, ontology editing tools, and academic history databases. His research demonstrates a strong emphasis on practical applications of semantic technologies in information management systems. Analysis of his recent publications reveals a consistent trajectory in semantic web technologies applied to knowledge representation and historical data. His work shows progression from foundational semantic technologies toward increasingly sophisticated applications in digital humanities, particularly in academic history research. The Heloise project appears to be a major focus, developing common research models for collaborative historical research using Linked Open Data. His publications span both technical aspects of semantic technologies and their application in humanities contexts. Professor Riechert actively contributes to academic community building through conference organization and student engagement. His leadership roles in the Faculty of Computer Science and Media demonstrate his commitment to shaping computer science education. His research integrates practical software development with theoretical advancements in knowledge representation. As Dean of Media Informatics, Riechert oversees academic programs and research initiatives in this field. His work with the Heloise network demonstrates leadership in interdisciplinary research connecting computer science with historical scholarship. His office hours are held on Mondays from 10:00 to 11:00 in room ZU 407 at HTWK Leipzig.

André Fiebigمشاهده پروفایل

پژوهشگر

• Psychoacoustics
• Soundscape Research
• Noise Effects
• +۷ مورد دیگر

Dr. phil. André Fiebig is a Permanent Research Associate and PostDoc at the Institute of Fluid Mechanics and Technical Acoustics (ISTA) within Faculty V - Transportation and Mechanical Systems at Technical University of Berlin. From January 2019 to December 2024, he served as a Visiting Professor responsible for the field of psychoacoustics, funded by the HEAD Genuit Foundation. Since January 2025, he has been leading the 'Psychoacoustics and Noise Effects' working group at the Department of Technical Acoustics. His research spans multiple areas within psychoacoustics and soundscape studies, including fundamentals and modeling of psychoacoustic sensation variables, binaural psychoacoustics, assessment of ambient noise and soundscapes, and psychoacoustic evaluation of sound insulation measures. His work also addresses cognitive stimulus integration of auditory sensations, auditory recreation, acoustic quality of stay, characterization of quiet areas, and measuring sound-induced emotions. Analysis of his recent publications reveals a strong focus on urban soundscapes, noise-conscious behavior in transportation, and the development of methodological frameworks for soundscape assessment. His work often integrates psychoacoustic principles with environmental considerations, particularly examining the relationship between sound environments and human health. Recent research shows increasing emphasis on cross-cultural studies of noise perception and the development of standardized assessment methodologies. Dr. Fiebig is involved in the EARS (Education and Applied Research on Soundscapes) initiative and has contributed to numerous collaborative research projects examining the intersection of urban planning, environmental acoustics, and human perception. His work frequently appears in major acoustics conferences and journals, demonstrating his active role in advancing the field of psychoacoustics and soundscape research. His laboratory work focuses on psychoacoustic testing methodologies, soundscape assessment techniques, and the development of evaluation instruments for noise protection measures. The 'Psychoacoustics and Noise Effects' working group under his leadership conducts research on both theoretical aspects of sound perception and practical applications for urban noise management.

Werner Langمشاهده پروفایل

استاد

• Sustainable Building
• Energy-Efficient Design
• Building with Positive Footprint
• +۷ مورد دیگر

Prof. Dr.-Ing. Werner Lang serves as Vice President for Sustainable Transformation and holds the Chair of Energy Efficient and Sustainable Design and Building (ENPB) at the Technical University of Munich (TUM), within the TUM School of Engineering and Design. Previously, he was Professor of Sustainable Building and Director of the Center for Sustainable Development at the University of Texas School of Architecture in Austin (2008-2010). Lang also directs the Oskar von Miller Forum and is a partner at Lang Hugger Rampp GmbH Architekten in Munich. Lang's research focuses on developing strategies for buildings with positive environmental footprints through regenerative energy systems, renewable materials, and closed material cycles. His work emphasizes comprehensive life cycle analysis considering ecological, economic, and social aspects. Current research areas include climate-resilient urban neighborhoods, circular economy in construction, and sustainable building materials. The ENPB institute conducts numerous research projects such as Building Climate-Municipal, CircularFTmehrRAUM, and Urban Green Infrastructure. Lang's publications reveal a strong trend toward life cycle assessment, multi-criteria decision-making, and computational approaches for sustainable building design. His recent work integrates machine learning with building performance analysis and focuses on practical implementation of circular economy principles in urban contexts, with increasing emphasis on quantifying environmental benefits of urban green infrastructure. TUM Sustainability Award 2022 Doce et Delecta (Second Prize for Best Teaching), 2019 Bayerischer Energiepreis 2014 International Building Skin Tech Award (2008) Promotionspreis der TUM (2000) Lang leads the Institute of Energy-Efficient and Sustainable Design and Building with numerous research grants including projects like Building.Lab+, NAWAREUM, and ECO+. His team includes researchers working on topics ranging from urban mining to life cycle assessment tools. The institute maintains several products and startups including MoMeBo, Bilanzlabor, and EnergyML that translate research into practical applications for the building industry.

Katrin Gillerمشاهده پروفایل

استاد

• Nutritional Sciences
• Animal Nutrition
• Molecular Nutrition
• +۳ مورد دیگر

Prof. Dr. habil. Katrin Giller leads the Department of Molecular Nutrition Science (140a) at the University of Hohenheim, Garbenstraße 30, Bio Building I, Room 151, Stuttgart. Her research focuses on livestock nutrition, with specific interests in methane mitigation, antioxidant mechanisms, and metabolic syndrome in agricultural animals. Department: Molecular Nutrition Science (140a) Contact: katrin.giller@uni-hohenheim.de Office Hours: By appointment Her work spans nutritional biochemistry , ruminal fermentation , and sustainable livestock systems , often examining interactions between dietary compounds (e.g., spirulina, polyphenols, n-3 fatty acids) and animal physiology. Recent studies investigate antioxidant gene expression , transgenerational metabolic impacts , and feed efficiency . Current advisees include B.Sc. Viola Gauly, Fernando Giugno, Jana Kornherr, Mira Kühn, Daniel Obermüller, and Helen Pötzsch. The department's website details research projects, teaching events, and publications.

• Fatigue strength of aluminum structures
• Fracture mechanics
• Railway bridge assessment
• +۴ مورد دیگر

Dorina Siebert is a Researcher at the Chair of Metal Construction within the School of Engineering at the Technical University of Munich. She has been working as a research assistant at the Chair since 2019, contributing to various research projects related to steel and aluminum construction, fracture mechanics, and additive manufacturing in construction. Education: M.Sc. in Civil Engineering from Technical University of Munich (2012-2019) Affiliation: Chair of Metal Construction, School of Engineering, Technical University of Munich Contact: dorina.siebert@tum.de, Room 0101.Z1.038, +49 (89) 289-22527 Dorina's research primarily focuses on the fatigue strength of aluminum structures, fracture mechanics in railway bridges, and the application of additive manufacturing techniques in construction. Her work on powder bed-based laser beam melting of metal has significant implications for modern construction methods. She also investigates safe operating time intervals for historic steel bridges and has contributed to the development of a mobile vehicle barrier, demonstrating the practical applications of her theoretical work. Her publication record shows a strong trend toward computational and experimental analysis of material behavior under stress, particularly in aluminum alloys and steel structures. She has published extensively on fatigue properties, fracture mechanics calculations, and additive manufacturing applications, with a clear progression toward more complex modeling techniques and practical engineering solutions. Her work bridges theoretical computational models with real-world infrastructure challenges. Dorina teaches courses including 'Constructing with aluminum' for the Summer semester 2025 and 'Fracture mechanics and fatigue' for the Winter semester 2024/25. She also leads a seminar on plate buckling and steel bridge construction, sharing her specialized knowledge with engineering students. Her teaching directly reflects her research expertise, creating a strong connection between theoretical knowledge and practical application for her students.