Find Academic Supervisors

• AI Ethics
• Sustainability in AI
• Data Ethics
• +7 more

Dr. Simon David Hirsbrunner serves as a team leader at the International Center for Ethics in Science and Technology (IZEW) at the University of Tübingen. As a media and social scientist, his research focuses on AI ethics, particularly examining the relationship between AI, ethics, and sustainability ("Sustainability in AI"), alongside high-risk applications of AI in education, police investigations, and personnel selection. His research interests span multiple critical domains: Application-oriented ethics and AI Ethics and Governance Data ethics and AI in educational contexts Open Science practices and Science & Technology Studies Technology Assessment and Digital media research Social science sustainability research Currently leading a Frontiers Research Topic on "AI contestability," Dr. Hirsbrunner investigates how AI systems can incorporate meaningful contestation mechanisms, especially in high-stakes decision contexts. His interdisciplinary approach bridges media studies, social science, and technical systems analysis. His publication record demonstrates consistent contributions to understanding algorithmic fairness across security applications, personnel systems, and educational technologies. He has made significant methodological contributions to climate change frame analysis using computational approaches and has explored openness challenges in digital media research. Professional recognition includes: Founding and board member of 'stsing - Science & Technology Studies in and through Germany' Co-spokesperson of the Open Science working group of the Society for Media Science Goethe Institute scholarship holder Expert consultant for multiple German government institutions including the Federal Foreign Office, DAAD, and environmental ministries With prior research positions at Freie Universität Berlin's Human-Centered Computing group, PIK, Wikimedia Deutschland, and adelphi think tank, Dr. Hirsbrunner brings extensive interdisciplinary experience to his work. His educational background includes MA degrees in International Relations (Geneva) and European Media Studies (Potsdam), plus a PhD in Media Ethnography from the University of Siegen. He actively engages in science communication through television discussions on AI in education and interviews exploring the cultural dimensions of climate change and digital media research methodologies.

Huaming ChenView profile

Senior Lecturer

• Software Engineering
• Artificial Intelligence
• Software Security
• +3 more

Dr. Huaming Chen is a Senior Lecturer in the School of Electrical and Computer Engineering at The University of Sydney, Australia. His work focuses on trustworthy machine learning systems, software engineering, and software security. With numerous publications in top-tier conferences and journals, Dr. Chen has established himself as a significant contributor to the fields of AI security and software engineering. Dr. Chen's primary research interests lie at the intersection of software engineering and artificial intelligence, with a strong emphasis on trustworthy AI systems. His work spans several key areas including: Software Security for AI-enabled systems Trustworthy and Responsible AI development Computational biology applications Industrial 4.0 implementations Federated learning and privacy-preserving techniques Large language model verification and uncertainty analysis His research addresses critical challenges in ensuring AI systems are secure, reliable, and ethically sound. Dr. Chen's recent publications demonstrate a strong trend toward addressing security and trustworthiness challenges in AI systems. His work spans multiple domains including software security (particularly for AI systems), trustworthy AI development, and applications in computational biology. A significant portion of his recent work focuses on large language models, examining their vulnerabilities, verification methods, and uncertainty analysis. He also maintains active research in federated learning, adversarial machine learning, and software security techniques. Dr. Chen has received several notable awards and recognitions: 2020 IEEE CIS Student Grant for IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE (WCCI) 2017 Student and Early Career Travel Fellowship for The 16th International Conference on Bioinformatics (InCoB 2017) 2017 Student Travel Award for 2017 IEEE World Congress on Services Dr. Chen actively supervises multiple research students working on cutting-edge projects related to trustworthy AI and software security. His current students are exploring topics ranging from blockchain-based governance frameworks to open-source AI security and digital twin platforms. He also serves in numerous committee roles at top conferences including area chair for ACM MM, and PC member for ACM CCS, IJCAI, KDD, and many others. His service as a Guest Editor for journals like Computers & Security and as a Grant Reviewer for UKRI demonstrates his standing in the research community. Dr. Chen organizes workshops focused on Trustworthy and Responsible AI, reflecting his commitment to advancing the field. His research group appears to focus on practical applications of AI security techniques, with projects spanning multiple domains including healthcare, finance, and industrial systems. He maintains active collaborations with researchers across multiple institutions, as evidenced by his co-authorship on diverse publications.

Marcos KalinowskiView profile

Professor

• Software Engineering
• Machine Learning
• Empirical Software Engineering
• +5 more

Professor Marcos Kalinowski is a faculty member in the Department of Informatics at Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Brazil. He serves as Professor of Software Engineering with an active research program focused on the intersection of software engineering and artificial intelligence. His research interests span: Software Engineering Machine Learning in Software Engineering Empirical Software Engineering Requirements Engineering for AI/ML Systems Trustworthy AI Systems Software Engineering Education Professor Kalinowski's recent work has concentrated on Large Language Models (LLMs) applications in software engineering processes, emphasizing empirical validation and practical relevance. His publications reveal a strong commitment to understanding how AI technologies can be effectively integrated into software development while maintaining quality standards and addressing human factors. He leads the international "Naming the Pain in Requirements Engineering" (NaPiRE) initiative, which investigates requirements engineering challenges across global organizations. His scientific contributions include: Framework development for trustworthy AI systems Empirical studies on LLMs in software engineering research Investigations of human factors in software development Analysis of machine learning code quality and technical debt Requirements engineering methodologies for AI-enabled systems Professor Kalinowski holds leadership positions in major software engineering conferences including General Co-Chair for ICSE 2026 and Program Co-Chair for ESEM 2021. His work appears consistently in top-tier venues such as ICSE, ESEC/FSE, EASE, and SANER, demonstrating significant recognition within the software engineering research community.

• Artificial Intelligence
• Machine Learning
• Data Science
• +5 more

Professor Kristina Schädler is a faculty member at the West Coast University of Applied Sciences (FH Westküste), where she serves as Professor of Data Processing within the School of Technology. She has been with the university since 2005 and also served as Dean of the Department of Technology. Her academic background includes a PhD in machine learning from TU Berlin, where she was awarded the Chorafas Research Prize for young scientists. West Coast University of Applied Sciences (since 2005) TU Berlin, Institute of Computer Science (1994-1999) Martin Luther University Halle/Wittenberg (1990-1994) Professor Schädler's research focuses on artificial intelligence and machine learning applications, particularly in image processing and data analysis. Her work spans multiple domains including industrial automation, agricultural technology, renewable energy, and animal husbandry. She has led numerous research projects that bridge academic theory with practical industrial applications, with particular emphasis on developing robust image processing systems that can be deployed in real-world settings. Her research portfolio demonstrates a consistent pattern of applying advanced machine learning techniques to solve practical problems across diverse industries. The ANIMET project, which developed facial recognition for horses, and the MaviSeg system for multichannel image segmentation represent her innovative approach to adapting computer vision technologies for specialized applications. Her work often involves close collaboration with industry partners to ensure practical relevance and implementation. Chorafas Research Prize for young scientists Innovationspreis at Equitana (2013) for the ANIMET project Professor Schädler has supervised numerous student theses that have resulted in practical applications across various domains. Her research group has secured funding from multiple sources including the European Commission, BMBF, and regional development agencies. She has established the CICAD project as a sustainable competence center for industrial image processing, which has trained multiple doctoral students through cooperative programs with the University of Lübeck. Her work demonstrates strong industry connections with companies like HIT Hinrichs Innovation + Technik, MBJ Solutions, and Fischer und Tausche Kondensatoren. Her research laboratory focuses on industrial image processing applications, with specialized equipment for 2D/3D imaging, spectral analysis, and machine learning implementation. The CICAD project established a dedicated competence center that continues to develop new applications of image processing technology across multiple industries.

Klaus WertenbrochView profile

Professor

• Behavioural Economics
• Consumer Choice
• Intertemporal Choice
• +7 more

Klaus Wertenbroch is the Novartis Chaired Professor of Management and the Environment and Professor of Marketing at INSEAD, where he directs the INSEAD Strategic Marketing Programme. He maintains academic affiliations with the Marketing Department at INSEAD's Fontainebleau campus in France and has previously been based in Singapore. His academic career spans multiple prestigious institutions including Duke University, Yale University, UC Berkeley, and The Wharton School of the University of Pennsylvania. Ph.D. and MBA from the University of Chicago M.Sc. (Diploma) in Psychology from Darmstadt University of Technology, Germany Wertenbroch's research focuses on behavioral economics and its strategic marketing and public policy implications, with particular expertise in consumer self-control problems related to overconsumption, overspending, and consumer debt. His current research examines how consumers respond to the dystopian aspects of artificial intelligence and marketing automation, including concerns about data privacy, algorithm explainability, and consumer autonomy. His work bridges academic rigor with practical applications, having collaborated with major organizations including Allianz, Citigroup, IBM, L'Oréal, and Unilever. His recent publications demonstrate a clear progression from traditional consumer behavior research toward the intersection of behavioral science and emerging technologies. The 2025 STAGS paper introduces an innovative methodology using AI to improve research generalizability, while his 2024 work on human agency in the AI age addresses critical concerns about consumer autonomy. His case studies on brand revitalization represent practical applications of his theoretical frameworks in real-world marketing contexts. 1995 American Marketing Association (AMA) Doctoral Dissertation Award 2005 AMA O'Dell Award (marketing's most prestigious annual award) Inaugural Marketing Science Institute Young Scholar (2001) Wertenbroch has served as Associate Editor for the Journal of Consumer Research and the Journal of Public Policy and Marketing, launched the Journal of Marketing Behavior as editor-in-chief, and contributed to numerous editorial boards. His research has appeared in leading journals including Journal of Consumer Research, Journal of Marketing Research, and Marketing Science, with coverage in Financial Times, Harvard Business Review, and The Economist. He has directed the INSEAD-Sorbonne Université Behavioural Lab in Paris and has advised public and private sector organizations on financial education initiatives.

Ralf BrunsView profile

Professor

• Data stream processing
• Evolutionary algorithms
• Machine learning
• +6 more

Prof. Dr. Ralf Bruns is a full-time Professor in the Department of Computer Science at the Faculty of Business and Information Technology, Hannover University of Applied Sciences and Arts. His office is located at Ricklinger Stadtweg 120, 30459 Hanover, with direct contact available via phone (+49 511 9296 1817) and email. His research focuses on cutting-edge computational methodologies including: Real-time data stream processing systems Bio-inspired algorithms ( evolutionary and swarm intelligence ) Machine learning applications in enterprise systems Semantic Web technologies for knowledge representation Software architecture patterns for event-driven systems Complex Event Processing (CEP) frameworks His publications demonstrate a consistent focus on event-driven architectures applied to logistics, healthcare, IoT, and urban mobility systems. Recent work emphasizes agent-based modeling and real-time analytics for decision support in dynamic environments. Prof. Bruns leads two key research initiatives: the Software Architecture Working Group (AG SWA) and the Smart Data Analytics Research Cluster . He also serves as faculty representative in the Fachbereichstag Informatik (FBTI) and contributes to academic selection committees.