Text Classification Professors and Supervisors in Germany

Stefania CecereView profile

Researcher

University of TübingenGermany

Stefania Cecere is a Researcher at the Department of Latin Philology within the Faculty of Humanities at the University of Tübingen. She specializes in Classical Philology with a focus on Pliny the Elder's Naturalis Historia and Latin specialized texts from antiquity. Her research explores the relationship between ars (art) and natura (nature) through praxeological models of 'other' aesthetics, emphasizing 'dense reading' of Pliny's work. Educational background: Doctorate in Classical Philology (Latin studies) at University of Tübingen (2025), Master's in Classical Philology from Università degli Studi di Napoli Federico II (2019), Erasmus study at University of Tübingen (2018), and Bachelor's in Ancient Studies from Università degli Studi di Napoli Federico II (2016) Current roles: Scientific researcher at Tübingen's Philologisches Seminar since September 2023, associated with Prof. Dr. Anja Wolkenhauer's Chair of Latin Philology Previously: Researcher at DFG-funded SFB 1391 'Andere Ästhetik' (2019-present) Her research focuses on analyzing Pliny's Naturalis Historia through aesthetic and literary theoretical lenses, particularly examining the interplay between art and nature in the work's embedded anecdotes. Her doctoral project investigates the relationship between ars and natura in Pliny's art-reflexive micro-narratives, concentrating on books 33-37 where artistic examples appear within natural history discussions. Recent research activities include: Co-organizing the DFG-approved trilateral research conference series 'Plinius der Ältere, die Natur und wir: vermitteln, bewahren, bewundern' (2022-2025) with international collaborators Participating in multiple workshops and conferences analyzing Pliny's legacy and reception across two millennia Contributing to publications on materiality, personification of nature, and artistic evaluation in classical texts

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Matthias SteinmetzView profile

Professor

Leibniz Institute for Astrophysics PotsdamGermany

Matthias Steinmetz serves as the Scientific Chairman of the Leibniz Institute for Astrophysics Potsdam (AIP) and Director of the Research Branch "Extragalactic Astrophysics and Cosmology". He is also a University Professor at the University of Potsdam. His leadership extends across the international astronomical community, including his current role as Scientific Member of the German Delegation to ESO Council and former presidency of the German Astronomical Society (2014-2017). His educational background includes: Physics and Mathematics studies at Saarland University (1986-1988) Physics studies at Technical University of Munich (1988-1991) Diploma Thesis at MPI for Astrophysics: "Carbon-Detonations in differentially rotating, highly deformed White Dwarfs" PhD Thesis: "On the formation and morphology of galaxies" (summa cum laude) from MPI for Astrophysics / Technical University of Munich (1991-1993) Steinmetz's research focuses on galaxy formation and evolution, particularly the Milky Way. He has pioneered high-resolution simulations of galaxy formation and is heavily involved in developing and exploiting spectroscopic surveys like the 4m Multi-Object Spectroscopic Telescope (4MOST) for ESO, scheduled to begin operations in 2025. His work bridges theoretical astrophysics with observational data to understand galactic structure, dynamics, and chemical evolution. He is also co-initiator of the German National Center for Astrophysics, currently being established in Goerlitz. Analysis of his recent publications reveals a consistent focus on Milky Way structure and evolution, with particular emphasis on galactic bars, stellar migration, metallicity gradients, and the circumgalactic medium. His research leverages data from major surveys like APOGEE and Gaia, combined with sophisticated computational methods including orbit superposition techniques and machine learning approaches. The interdisciplinary nature of his work connects stellar dynamics, chemical evolution, and cosmological context to build a comprehensive understanding of our galaxy's history. His scientific achievements have been recognized with numerous prestigious awards: 1984: 1. State Prize and 2. Federal Prize in Physics Jugend forscht 1986: 1. State Prize and 4. Federal Prize Earth and Space Sciences Jugend forscht 1988-1991: Stipend of the Studienstiftung des deutschen Volkes 1993: Otto-Hahn-Medal of the Max Planck Society 1998: Alfred P. Sloan Fellowship 1998: David and Lucile Packard Fellowship 2011: Architectural Award Brandenburg 2013: Elected member of the Berlin Brandenburg Academy of Sciences and Humanities 2015: Wilhelm-Foerster Award of the Urania Potsdam for Communicating Science As a leader in the astronomical community, Steinmetz has mentored numerous students and researchers, though specific names aren't listed in the provided text. His significant grant funding includes leadership roles in major international projects like 4MOST and participation in ESO initiatives. He has served on numerous advisory boards including the Science Advisory Board of the MPI for Astronomy and the Square Kilometre Array (SKA) Science and Engineering Advisory Committee. At the Leibniz Institute for Astrophysics Potsdam, Steinmetz leads the Extragalactic Astrophysics research branch, which investigates topics ranging from the structure and dynamics of the Milky Way to the formation of galaxies and the large-scale cosmic web. His team is actively involved in developing next-generation instruments for ESO's Paranal Observatory and the Extremely Large Telescope (ELT), as well as establishing research data infrastructure for astronomy. The institute's collaborative environment connects theoretical modeling with observational astronomy and technological development.

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Amiangshu BosuView profile

Associate Professor

Max Planck Institute for Security and PrivacyGermany

Amiangshu Bosu is a tenured Associate Professor in the Department of Computer Science at Wayne State University's College of Engineering. Previously, he served as a tenure-track Assistant Professor at Southern Illinois University Carbondale from 2016-2018. His academic journey includes completing his Ph.D. at the University of Alabama in 2015 under Professor Jeffrey Carver, followed by postdoctoral research with Dr. Danfeng Yao at Virginia Tech. His educational background reflects a strong foundation in software engineering research, with his doctoral work focusing on empirical approaches to software development practices. This foundation has enabled his current research trajectory examining human aspects of software engineering. Bosu's research program centers on empirical software engineering with particular emphasis on code review dynamics, toxicity detection in developer communications, and diversity issues in open source communities. His work bridges technical analysis with social science perspectives, investigating how communication patterns affect participation, especially regarding gender dynamics in OSS projects. Recent work increasingly incorporates natural language processing and machine learning techniques to build tools like ToxiCR for automated toxicity detection in code reviews. Analysis of his publication record reveals a clear evolution toward examining social dynamics in software development, with growing emphasis on gender bias, toxicity, and diversity issues. His research consistently applies empirical methods to understand real-world developer experiences while developing practical tools to improve code review processes and community health. His scientific recognition includes the prestigious NSF CAREER award (2024), NSF CRII award (2019), and Wayne State University's College of Engineering Research Excellence award (2025). He maintains senior membership status in both ACM and IEEE, reflecting his standing in the computing community. NSF CRII award (2019) NSF CAREER award (2024) College of Engineering Research Excellence award (2025) Senior Member of ACM Senior Member of IEEE Bosu actively contributes to the software engineering research community through service on program committees for major conferences including ICSE, ASE, ESEC/FSE, and ESEM. His GitHub presence (amiangshu.me) demonstrates active engagement with research tools and datasets, particularly those related to code review analysis and toxicity detection. While specific lab structure isn't detailed in the provided materials, his research group appears focused on empirical studies of software development practices with strong connections to industry through collaborations on projects like Chromium OS security analysis.

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Klaus BöhmView profile

Professor

Mainz University of Applied SciencesGermany

Klaus Böhm serves as a Professor at Mainz University of Applied Sciences within the School of Engineering, affiliated with the i3mainz institute (Institute for Spatial Information and Surveying Technology). His research bridges geospatial technologies with artificial intelligence, focusing on practical applications in urban planning, healthcare, and educational environments through projects like BAM (Big Data Analytics) and TOPML (Machine Learning). His primary research domains include geospatial explainable AI (GeoXAI), mixed reality decision support systems, and health informatics applications. He pioneers methods for visualizing uncertainty in AI models, developing geoparsing techniques using LLMs, and creating spatial navigation frameworks for VR environments. His work consistently addresses real-world challenges in elderly mobility, smart city infrastructure, and medical education through spatial analytics. Analysis of his 2022-2025 publications reveals three dominant trends: (1) Integration of XAI with geospatial data for transparent decision-making in urban planning, (2) Development of mixed reality tools for STEM education and dermatology training, and (3) Spatio-temporal correlation analysis for smart city applications like parking optimization and public transport accessibility. His methodology emphasizes interactive visualization of complex spatial relationships and uncertainty quantification. Dr. Böhm leads multiple funded research initiatives including AIMR (AI-based decision support in mixed reality), RAFVINIERT (spatial intelligence for senior care), and FlexGeo (geo-service integration). These projects demonstrate sustained grant acquisition capability across EU and national funding programs, typically involving interdisciplinary teams from computer science, urban planning, and healthcare sectors. As a core member of the i3mainz research institute, he contributes to Germany's geospatial technology ecosystem through collaborative projects with municipal authorities and healthcare providers. The institute's work focuses on translating academic research into operational tools for spatial data infrastructure, particularly in environmental monitoring and public service optimization contexts.

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Salam TraboulsiView profile

Researcher

Stuttgart University of Applied SciencesGermany

Dr. Salam Traboulsi is a Researcher at Stuttgart University of Applied Sciences (HFT Stuttgart), affiliated with the Competence Center for Digitalization in Research, Teaching & Economics since 2019. She holds a PhD in Computer Science from the University of Toulouse, France (2008). Her work bridges technology and urban innovation, with a focus on developing scalable solutions for modern cities. Research Focus: Dr. Traboulsi specializes in: Smart City ecosystems integrating IoT and 5G Precision technologies for urban positioning and navigation Data management frameworks for large-scale sensor networks Open-source IoT platforms for building efficiency and environmental monitoring Cloud and grid computing infrastructures Key Projects: She leads/contributes to: iCity 2: UDigiT4iCity – Developing urban digital twins using IoT building data and 5G sensor networks iCity 1 – Foundational research on intelligent urban infrastructure systems Publication Trends: Her recent work (2020-2024) emphasizes 5G-enabled urban solutions, including fleet management optimization, indoor positioning systems, and IoT analytics for smart buildings. Earlier research (2005-2013) focused on distributed computing, storage virtualization, and information retrieval systems, demonstrating consistent expertise in large-scale data infrastructure. Academic Engagement: She serves as a scientific reviewer for journals and conferences and teaches in the surveying study area at HFT Stuttgart.

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Michael KahleView profile

Researcher

Albert Ludwig University of FreiburgGermany

Michael Kahle is a Research Associate at the Professorship for Physical Geography within the Institute of Environmental Social Sciences and Geography, Faculty of Environment and Natural Resources, University of Freiburg, where he has been affiliated since April 2014. His research employs interdisciplinary approaches combining physical geography with digital humanities. Research interests focus on climate change impacts and societal responses, including: Machine learning applications for historical climate text analysis Drought and flood event classification using NLP Climate-induced migration patterns Social consequences of extreme weather events Digital reconstruction of historical climatological data His publications demonstrate consistent focus on climate-society interactions, with recent works analyzing drought resilience in Germany/China (2025), viticulture adaptation (2024), and flood classification methodologies (2022) using multimodal data analysis. Key project involvement includes: tambora.org (2014-2016): Collaborative platform for historical climatology DEMUR project : Fluvio-social metabolism analysis of the Upper Rhine area

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Manuela NeumannView profile

Professor

Helmholtz Association of German Research CentersGermany

Manuela Neumann is a Professor and Group Leader at the German Center for Neurodegenerative Diseases (DZNE) in Tübingen, Germany, researching molecular mechanisms of frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS) with emphasis on TDP-43 and FUS protein aggregation. Her primary research spans neurodegenerative diseases, ALS, FTLD, molecular neuroscience, protein aggregation, and RNA metabolism. The Neumann group investigates physiological functions of TDP-43, FUS, and C9orf72 proteins in the central nervous system, mechanisms of neurodegeneration (loss of function vs. toxic gain of function), and molecular classification of disease subtypes to advance therapeutic development. No scientific awards were mentioned in the source text. No details regarding student supervision or research grants were provided in the source material. The laboratory employs advanced methodologies including histological/proteomic analysis, image processing, antibody generation, primary neuron cultures, organotypic slice cultures, and genetically modified mouse models (knock-out, knock-in, overexpression). Current projects focus on TDP-43/FUS posttranslational modifications, disease-model development, transcriptomic/epigenetic/proteomic changes, and C9orf72-TDP-43 interactions using human brain bank tissues.

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Jie LiuView profile

Professor

Max Planck Institute for Security and PrivacyGermany

Jie Liu is a Researcher at the Institute of Software, Chinese Academy of Sciences and a Professor and Doctoral Supervisor at University of Chinese Academy of Sciences. He is also a Member of the Youth Innovation Promotion Association of the Chinese Academy of Sciences and an Executive Committee Member of the System Software Committee of the CCF Computer Society. His research is conducted within the Software Engineering Technology R&D Center. Dr. Liu received his Ph.D. from the University of Science and Technology of China in 2011 and his B.A. from the same institution in 2004. He has progressed through the ranks at the Institute of Software, CAS, starting as an Assistant Research Fellow (2011-2014), then Associate Research Fellow (2014-2024), and currently as a Researcher (since 2024). His research spans Big Data Intelligent Analysis Models and Systems at the intersection of AI, Software Engineering, and System Software. Specifically, his work covers three main areas: Big Data and Machine Learning Systems (statistics and AI algorithm model libraries, data quantitative analysis tools, LLM reasoning optimization, Earth Big Data); Intelligent Software Engineering (code model constraint decoding, data science agents, system log analysis agents); and Knowledge-Enhanced Intelligent Model Construction (knowledge extraction, knowledge graphs, domain AI model design). His research has resulted in innovative approaches to handling complex data analysis challenges across multiple domains. Dr. Liu's research has produced significant outcomes including EarthDataMiner, which supports SDG indicator calculations and won the 2024 Beijing Municipal Science and Technology Progress First Prize. His work on RISC-V software migration technology has been integrated into the Ruiqian tool (https://rvpt.top/), demonstrating practical applications of his research in emerging computing architectures. Beijing Science and Technology Progress Award, First Prize, 2024 2023 Surveying and Mapping Science and Technology Award, Special Prize, 2023 DASFAA Best Paper Runner-up, Second Prize, 2013 Dr. Liu has successfully guided numerous graduate students who have secured positions at major technology companies including Alibaba, ByteDance, Southern Power Grid, and Agricultural Bank of China. He has secured funding through multiple National Natural Science Foundation projects, National Key R&D Program projects, and over ten other research initiatives. His research collaborations span industry leaders like Huawei, JD.com, and TravelSky, as well as academic institutions within the Chinese Academy of Sciences. He teaches graduate courses such as 'Machine Learning Systems' and 'Cloud Computing and Big Data Technology' at University of Chinese Academy of Sciences, and has established a research group focused on developing innovative solutions at the intersection of AI and software engineering with real-world applications in earth sciences, healthcare, and intelligent systems.

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Xiaoning DuView profile

Senior Lecturer

Max Planck Institute for Security and PrivacyGermany

Xiaoning Du is a Senior Lecturer (equivalent to U.S. Associate Professor) at the Department of Software Systems and Cybersecurity within the Faculty of Information Technology at Monash University, Australia. She was promoted to this position effective July 1, 2025, having previously served as a Lecturer (Assistant Professor) since joining Monash in February 2021. Her research bridges the gap between theory and practical applications of program analysis and formal methods in evaluating traditional and AI-assisted software systems. Dr. Du's educational background includes: PhD from Nanyang Technological University (2020) Bachelor's degree from Fudan University (2014) Dr. Du specializes in software engineering, artificial intelligence, and cybersecurity , with particular focus on SE4AI (Software Engineering for AI), software analysis and testing . Her research has made significant contributions to the security and quality assurance of intelligent software systems, especially intelligent software engineering tools. She is best known for her work on Devign , BigCodeBench , DeepStellar , and SimPy , which have advanced the fields of code generation, program analysis, and AI security. Her approach consistently bridges theoretical foundations with practical applications to improve software quality and security. Dr. Du's recent publications demonstrate a strong focus on the intersection of software engineering and AI, particularly examining how large language models interact with source code. Her work addresses critical challenges in code generation efficiency, security vulnerabilities in AI-assisted development, and fairness in AI systems. She has made significant contributions to benchmarking frameworks like BigCodeBench and has pioneered research on watermarking techniques to protect code datasets from misuse by neural code completion models. Dr. Du has received numerous prestigious awards and recognitions: 2024 Google Research Scholar Award in Software Engineering ACM SIGSOFT Distinguished Paper Award (ISSTA'24) ICLR Oral presentation (2025) 2024 FIT Dean's Early Career Researcher of the Year Award Multiple FIT ECR Seed Grants (2021-2023) Dr. Du actively mentors PhD students, with notable successes including Terry (2024-2025 IBM PhD Fellowship Award recipient) and Zhensu (2024 Bytedance Scholarship Award recipient). She is currently seeking self-motivated PhD students with strong programming skills and relevant research experience, offering full scholarship support. Her research has been supported by multiple grants including the Google Research Scholar Program award and several FIT ECR Seed Grants that have enabled her team to pursue innovative research in software security and AI-assisted development. Dr. Du leads a research group focused on intelligent software systems security and quality assurance. Her team has developed several influential tools and benchmarks including Devign, BigCodeBench, DeepStellar, and SimPy. These resources have become important assets for researchers and practitioners working at the intersection of software engineering and artificial intelligence, particularly in the areas of code generation, program analysis, and security testing of AI systems.

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Mohammad Adnan HamdaqaView profile

Associate Professor

Max Planck Institute for Security and PrivacyGermany

Mohammad Adnan Hamdaqa is an Associate Professor at the Department of Computer Engineering and Software Engineering at Polytechnique Montréal (Canada), where he leads the Software and Emerging Technologies Lab. He holds a Ph.D. in Software Engineering from the University of Waterloo (2016), along with a Master's in Electrical and Computer Engineering from Concordia University, an MBA from New York Institute of Technology, and a Bachelor's in Computer Engineering from Jordan University of Science and Technology. His research focuses on the intersection of emerging technologies and software engineering, particularly how software engineering approaches can be adapted for new platforms like Cloud Computing and Blockchain. His work spans model-driven software engineering, cloud applications, and blockchain technologies. Analysis of his recent publications reveals a strong emphasis on blockchain technology, especially smart contracts and Ethereum, with significant work on security, evolution, and visualization of these systems. His research also demonstrates growing integration of large language models in software engineering tasks, particularly for model specification and code generation. There's also a notable thread of work on sustainability in infrastructure as code and security practices across cloud platforms. Hamdaqa actively contributes to the academic community as a member of IEEE Computer Society and ACM, and has served on program committees for numerous conferences in software engineering and services communities. He has successfully supervised multiple Master's students, with recent theses focusing on smart contract auditing, epidemiological modeling using model-driven approaches, and security practices in infrastructure as code. His lab maintains active research in both theoretical and applied aspects of software engineering for emerging technologies.

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Pablo García de FrutosView profile

Researcher

Leibniz Research Institute for Environmental MedicineGermany

Pablo García de Frutos is a Researcher at the Institute of Biomedical Research of Barcelona (IIBB), operating under Spain's national research authority, the Spanish National Research Council (CSIC). His work bridges laboratory science and clinical applications with emphasis on thrombosis mechanisms and cardiovascular diagnostics. His research portfolio demonstrates deep specialization in: Thrombosis pathophysiology (22% research footprint) Vitamin K-dependent protein functions (17% footprint) Blood coagulation dynamics Cardiovascular disease biomarkers Plasma-based diagnostic development Analysis of his 2022-2024 publications reveals convergent expertise across three domains: cancer biology (pancreatic/liver tumors with TAM receptor and inflammasome focus), cardiovascular pathology (atherosclerosis plaque formation and heart failure biomarkers), and critical care immunology (COVID-19 antibody responses). His work consistently identifies molecular targets for diagnostic and therapeutic intervention. Scientific awards: No documented awards in source materials. Academic mentoring and funding: Source text provides no details regarding student supervision, grant acquisitions, or laboratory leadership roles.

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Gordon WilmsmeierView profile

Professor

Bremen University of Applied SciencesGermany

Gordon Wilmsmeier is a Professor affiliated with Faculty 5, Department 2 in Bremen. His work includes the project AIS and Big Data for Inland Waterways Classification (2018–2019), focusing on data-driven solutions for transportation systems. The institution's participation in 2025 events—such as migration-focused discussions, environmental campaigns ('Healthy lake – lots of fish'), and bio-based materials research—suggests interdisciplinary engagement with sustainability and technology. Research interests span Big Data analytics , inland waterway logistics , and environmental systems , reflecting applied work in transportation efficiency and ecological conservation. No awards, students, or publications are detailed in the source text.

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