Carl Vondrick is a Professor in the Department of Computer Science at Columbia University. His research focuses on creating robust and versatile perception systems that leverage video and interaction with the natural world, with applications in 3D reconstruction, visual question answering, and robot manipulation. Former research scientist at Google Visiting researcher at Cruise Education: PhD (2017) from MIT, advised by Antonio Torralba BS (2011) from UC Irvine, advised by Deva Ramanan His research explores multimodal approaches for cross-task and cross-modal transfer, scene dynamics, audiovisual perception, interpretable models, and spatial awareness systems. The lab emphasizes zero-shot generalization and neuro-symbolic methods while addressing safety and robustness in AI systems. Key publication trends include: 2025: Video generation for robotics 2024: Differentiable rendering and cross-modal reasoning 2023: Robust perception and 3D modeling Scientific Awards: 2024 PAMI Young Researcher Award 2021 NSF CAREER Award Teaching Roles: Teaching Computer Vision II (2021-2025), Computer Vision I (2018-2019), and Representation Learning (2020-2022). Advising: Advises 8 current PhD students and has mentored 5 graduated students now at institutions like MBZUAI and UMD. The lab recruits 1-2 PhD students annually through Columbia’s PhD program. Grants and Collaborations: Funded by NSF, DARPA, Toyota Research Institute, Amazon Research, and Google.
Gül Şen is a Senior Lecturer and Privatdozentin at the Institute of Oriental and Asian Studies, University of Bonn, and also serves as a Lecturer at the University of Heidelberg. Her academic work focuses on premodern Ottoman history, historiography, and the dynamics of dependency, particularly in maritime contexts such as galley slavery and war captivity. She is actively involved in major research programs including the DFG-Priority Program 'Transottomanica' and the Bonn Center for Dependency and Slavery Studies. Her research areas include: Premodern Ottoman historiography and narrative strategies Legitimacy of rule and political transitions Maritime unfree labor and galley slavery War captivity and captivity narratives in the 18th century Dependency and asymmetrical power relations in the early modern Mediterranean Her recent publications reveal a strong thematic trend centered on the interplay between narrative construction and social power, particularly in contexts of slavery and captivity. She investigates how historical actors used storytelling to assert legitimacy, cope with crises, and negotiate identity. Her work bridges literary analysis with social history, offering nuanced understandings of agency within systems of dependency. She frequently collaborates with leading scholars like Stephan Conermann and contributes to major edited volumes and series in Ottoman studies. Her scientific awards include: DAAD Award for outstanding academic achievements (2012) Postdoctoral Scholarship from the Fritz Thyssen Foundation (2012–2013) Postdoctoral Fellowships at the Annemarie Schimmel Kolleg (2015–2016, 2018–2019) Postdoctoral Scholarship from the University of Bonn (2019–2020) She has supervised numerous B.A. and M.A. theses at the University of Bonn and Heidelberg and has secured third-party funding, including a DFG project (€192,000) from 2016–2018 and Fritz Thyssen Foundation grants. She is co-editor of the 'Ottoman Studies' and 'Otto Spies Memorial Series' book series, and holds leadership roles in the Society for Turkic, Ottoman and Turkish Studies (GTOT) and the International Association for Ottoman Social and Economic History (IAOSEH). Her academic activities are deeply embedded in collaborative and interdisciplinary research environments. She is affiliated with the Bonn Center for Dependency and Slavery Studies and contributes to the DFG-Priority Program 'Transottomanica,' where she examines mobility dynamics and captivity narratives. Her work is supported by a strong network of international collaborations and editorial engagements.
Celestine Mendler-Dünner is a Principal Investigator at the ELLIS Institute in Tübingen, co-affiliated with the Max Planck Institute for Intelligent Systems and the Tübingen AI Center. She leads the Algorithms and Society research group, focusing on machine learning in social contexts and the role of prediction in digital economies. Her work bridges theoretical machine learning with practical societal impact, developing tools for safe, reliable, and equitable AI ecosystems. Her educational background includes a PhD from ETH Zurich in collaboration with IBM Research, followed by an SNSF postdoctoral fellowship at UC Berkeley hosted by Moritz Hardt. She was previously a group leader at the Max Planck Institute for Intelligent Systems before joining the ELLIS Institute. Mendler-Dünner's research spans several interconnected themes including performative prediction (where predictions change the behavior they aim to predict), algorithmic collective action (how participants can steer AI systems toward common goals), and the role of LLMs in social science research. Her work combines theoretical foundations with practical implementations, addressing challenges in interactive machine learning, optimization in dynamic environments, and context-specific evaluation of AI systems. She particularly examines how algorithmic predictions mediate services and platforms at societal scale, exploring concepts of economic power in digital markets. Her publication record shows a clear evolution from system-aware machine learning algorithms (including foundational work on IBM Snap ML) toward increasingly sociotechnical questions at the intersection of machine learning, economics, and policy. Recent work focuses on measuring performative power in digital economies, evaluating LLMs as risk scores, and developing frameworks for algorithmic collective action in recommender systems and labor markets. Among her notable recognitions are the ETH Medal for her dissertation, the IBM Research Division Award, the Fritz Kutter Award, and the IBM Eminence and Excellence Award. She is an ELLIS Scholar, a fellow of the Elisabeth-Schiemann-Kolleg, and affiliated with several prestigious research programs including the International Max Planck Research School for Intelligent Systems and the Max Planck ETH Center for Learning Systems. ETH Medal (dissertation award) IBM Research Division Award Fritz Kutter Award IBM Eminence and Excellence Award SNSF Early Postdoc Mobility Fellowship Mendler-Dünner actively mentors the next generation of researchers, advising PhD student Patrik Wolf and supervising research interns including Joachim Baumann, Haiqing Zhu, and Anna Badalyan, as well as Master's student Dorothee Sigg. She serves as core faculty for the International Max Planck Research School and associated faculty for the Max Planck ETH Center for Learning Systems. Her group has secured significant research funding through fellowships and institutional support, enabling work on projects like Powermeter (measuring search engine influence) and Snap ML (resource-efficient machine learning library with over 1 million PyPI downloads). She leads the Algorithms and Society research group, which examines machine learning as part of broader sociotechnical ecosystems. The group explores human-population interactions with algorithmic systems and incorporates these insights into learning system fundamentals. Current projects include investigating economic incentives in digital platforms, developing tools for systematic LLM evaluation in social science contexts, and creating frameworks for collective action in algorithmic systems. Mendler-Dünner also co-organizes the Algorithmic Collective Action workshop at NeurIPS 2025, demonstrating her leadership in emerging research directions at the AI-society interface.
Prof. Laura Leal-Taixé is a Professor at the Technical University of Munich (TUM) in the Department of Informatics, leading the Dynamic Vision and Learning group. She holds the Rudolf Mößbauer Tenure Track Assistant Professorship, promoted to W3 Associate Professorship in 2022. Her research focuses on computer vision and machine learning, particularly video analysis, multi-object tracking, and autonomous driving applications. Education: B.Sc./M.Sc. in Telecommunications Engineering (Technical University of Catalonia, UPC) Ph.D. in Information Processing (Leibniz University of Hannover, Germany) Postdoctoral Research at ETH Zürich (Switzerland) and TUM Research Interests: Laura’s work addresses challenges in video analysis, including motion analysis, semantic segmentation, and integrating social dynamics into urban traffic modeling. Her project socialMaps , funded by the Sofja Kovalevskaja Award, explores decoupling vehicle and pedestrian traffic using dynamic maps. Her research combines optimization techniques, deep learning, and sensor data for real-world applications like autonomous systems. Recent Trends: Her publications highlight advancements in multi-object tracking, 3D LiDAR segmentation, and trajectory forecasting, emphasizing neural networks and geometric approaches. Collaborations with industry and academia underscore her work’s practical impact. Awards: 2017 Sofja Kovalevskaja Award (€1.65M, Humboldt Foundation) 2017 DAAD Australia-German Joint Research Grant Travel grants from Women in CV, CVPR Doctoral Consortium, and Vodafone Foundation Labs & Projects: Leads the Dynamic Vision and Learning group at TUM, focusing on vision-based AI for autonomous systems and environmental monitoring. Active in developing datasets like DynamicEarthNet for semantic change analysis.
Prof. Dr. Claudia Peus is a full Professor of Research and Science Management at the Technical University of Munich (TUM) School of Management , serving since May 2011. She holds executive roles as Founding Director of the TUM Institute for LifeLong Learning (TUM IL3) since December 2019 and Executive Vice President for Talent Management and Diversity since October 2017. Her career spans visiting positions at MIT's Sloan School of Management and Harvard University, alongside her habilitation (2011) and PhD (2005) from LMU Munich. Current affiliations: TUM School of Management, TUM IL3, RWI – Leibniz Institute for Economic Research Research focuses: Leadership development in the digital age, diversity in organizations, ethical leadership, and research organization management Recent research trends analyze digital leadership dynamics, gender-decoded recruitment practices, robotic leadership interfaces, and neurophysiological mechanisms in leadership behavior. Her 2025 work on moral careers and 2024 resource-based absorption theory highlight evolving themes in organizational psychology. Scientific honors include: Highly Cited Research Award, Leadership Quarterly (2016) Emerald Citations of Excellence (2016) Best Teaching Award, TUM School of Management (2014) Academy of Management Symposium Award (2010) Bayerische Landesbank Wissenschaftspreis (2006) Prof. Peus advises organizations on diversity and talent management. She was recognized as one of Germany's Most Inspiring Women (2020) and leads projects like FührMINT, ForGenderCare, and the TUM Neurophysiological Leadership Lab (NeLeLab).
Prof. Alois Christian Knoll is a full professor at the Technical University of Munich (TUM) in the School of Computation, Information and Technology. His academic career includes roles at Bielefeld University and leadership in major EU initiatives like the Human Brain Project and ECHORD++. He specializes in robotics, AI, and autonomous systems, with a focus on medical robotics, sensor-based systems, and neuromorphic engineering. Knoll has supervised over 100 doctoral theses and authored/co-authored over 1,000 publications. Education: Diploma in Electrical Engineering (University of Stuttgart, 1985); PhD in Computer Science (Technical University of Berlin, 1988); Habilitation (TU Berlin, 1993). He has been at TUM since 2001, leading the Robotics, AI, and Real-Time Systems department. Research interests span autonomous systems, neuro-IT integration, and traffic simulation. Key projects include fortiss (Bavarian State Institute for Computer Science) and TUM-CREATE (Singapore collaboration). Awards include IEEE Fellow, University of Tokyo Fellow, and the Carl-Ramsauer-Prize (1990). Current roles include editorships in robotics journals, leadership in EU flagship projects, and teaching across multiple programs. His work bridges computer science, neuroscience, and engineering, with applications in healthcare, automotive systems, and urban mobility.
Sebastian Thies is Professor and Chair for Ibero-American Literary and Cultural Studies at the University of Tübingen, where he has been employed since October 2012. He serves as Vice Director of the Interdisciplinary Centre for Global South Studies (ICGSS) and coordinates the BMBF/DAAD thematic network 'Futures under construction in the Global South'. His academic journey began with a PhD in Hispanic Studies from the University of Osnabrück in 2000, followed by positions at the University of Bielefeld where he progressed from Junior Professor for Hispanic Literary and Media Studies to Full Professor for Inter-American Studies. Thies' research focuses on Global South Studies, with particular emphasis on Latin American literature, film, and media. His work explores subjectivity formations, entangled temporalities, and political communication across borders. He has directed significant research initiatives including the doctoral studies program 'Entangled Temporalities in the Global South' and has co-edited major reference works such as The Routledge Handbook for Global South Studies on Subjectivities (2024). His extensive publication record demonstrates a consistent engagement with transnational cultural phenomena, particularly examining how Latin American cultural production intersects with global political and social dynamics. Thies frequently collaborates with international scholars, reflecting his commitment to transdisciplinary and transregional approaches to cultural analysis. Project Leader: Research Training Network 'Entangled Temporalities in the Global South' Vice Project Leader: Thematic network 'Literary Cultures of the Global South' Associated Investigator: BMBF-Area Studies Project 'The Americas as a Space of Entanglement' Project Leader: Research Group 'E Pluribus Unum? Ethnic Identies in Processes of Transnational Integration' Thies actively supervises doctoral students through the Interdisciplinary Centre for Global South Studies and has established collaborative networks across Latin America, particularly with institutions in Mexico and Colombia. His current research agenda focuses on 'Futures under construction in the Global South' and continues to explore the intersections of cultural production, political communication, and subjectivity formation in transnational contexts.
Prof. Stefan Rohdewald is a Professor of East and South-Eastern European History at the University of Leipzig since 2020. Previously, he held positions at Justus Liebig University Giessen (2013-2020), University of Passau (2003-2012), and University of Zurich (1998-2001). His research focuses on transregional histories, religious memory, and intercultural communication in Eastern Europe and the Ottoman sphere. Key roles include coordinating DFG’s Transottomanica program and leading the GiZo partnership with University of Zagreb. Education: PhD (2004, University of Zurich), Habilitation (2012, University of Passau). Research interests span memorial discourses, Ottoman-Europe relations, and sport history. Major projects include studies on Serbo-Bulgarian religious figures and transottoman mobility dynamics. He chairs conferences on minority politics and Ottoman Europe, contributing to over 70 peer-reviewed publications. Award-winning publications include Götter der Nationen (2014) and Vlad der Pfähler (2017). His work bridges Eastern European, Ottoman, and transnational histories through innovative methodological frameworks.
Julian McAuley is a Professor in the Department of Computer Science and Engineering at the University of California, San Diego's Jacobs School of Engineering. His research spans recommender systems, machine learning, natural language processing, music information retrieval, and multimodal learning. He maintains an active research group with numerous PhD students and postdocs working on cutting-edge AI problems. His research interests focus on developing advanced algorithms for personalized recommendation systems, with particular emphasis on sequential recommendation, multimodal learning, and integrating large language models with traditional recommendation approaches. His work bridges the gap between theoretical machine learning and practical applications across multiple domains including e-commerce, music, and healthcare. McAuley has published extensively in top-tier conferences including NeurIPS, ICML, KDD, SIGIR, and ACL, with his most recent work exploring the intersection of large language models and recommendation systems. His publications reveal a strong trend toward multimodal approaches that combine text, vision, and audio for more comprehensive understanding and recommendation. He has received significant research funding from major technology companies including Google, Amazon, Facebook, Adobe, and Samsung, as well as government agencies like the National Science Foundation and Department of Defense. His work has practical applications across multiple industries, with a focus on improving user experience through better personalization. McAuley advises numerous PhD students who have gone on to successful careers at leading technology companies and academic institutions. His former students include Wang-Cheng Kang and Jianmo Ni at Google DeepMind, Chris Donahue and Zachary Lipton as assistant professors at CMU, and Ruining He at Google Deepmind.
Benjamin Mako Hill is an Associate Professor in the University of Washington Department of Communication and an Adjunct Associate Professor in Human-Centered Design & Engineering , the Paul G. Allen School of Computer Science & Engineering , and the Information School at UW. He is a Faculty Associate at the Berkman Klein Center for Internet and Society at Harvard University and a Fellow at the Center for Information Technology Policy at Princeton University during the 2023–2024 academic year. Educational Background : PhD in an interdepartmental program at Massachusetts Institute of Technology (MIT) , involving the MIT Sloan School of Management and the MIT Media Lab , advised by Eric von Hippel, Yochai Benkler, Tom Malone, and Mitch Resnick. MS in Media Arts and Sciences from MIT. B.A. in Technological and Legal History from Hampshire College . Research Interests span peer production, online communities, collective action, cooperation, learning, and computer-mediated communication. His work explores how communication and information technologies shape social outcomes in collaborative environments like Wikipedia and Linux, focusing on governance, moderation, anonymity, and educational platforms such as Scratch. Article Trends : His publications analyze peer production dynamics, privacy in open collaboration, and computational thinking in youth. Topics include underproduction in open source software, algorithmic fairness, taboo knowledge production, and legitimate peripheral participation in online communities. Methodologies combine big data, quasi-experimental, and comparative analyses. Scientific Awards : Dordick Award for Best Dissertation (2013). CHI '22 Best Paper Honorable Mention (2022). CSCW '18 Best Paper Honorable Mention (2018). CHI '17 Best Paper Honorable Mention (2017). CSCW '13 Best Paper Award (2013). CHI '11 Best Paper Honorable Mention (2011). Advising and Grants : He co-founded the Community Data Science Collective and collaborates with researchers like Aaron Shaw. Grants include multiple National Science Foundation awards for studies on digital knowledge commons, anonymous participation, and collaborative success, as well as a Sloan Foundation grant for modeling underproduction in peer production. Labs and Teams : He leads the Community Data Science Collective , an interdisciplinary research group studying online communities, and contributes to open-source projects like Debian and Ubuntu . He actively edits Wikimedia projects and participates in the Cascadia Wikimedians User Group .
Vijay Laxmi is a Professor in the Department of Computer Science and Engineering at Malaviya National Institute of Technology (MNIT) Jaipur, India. With over a decade of active research publication from 2014-2024, Dr. Laxmi has established themselves as a prominent researcher in network security, Android security systems, and Network-on-Chip architectures. Their work demonstrates consistent collaboration with Manoj Singh Gaur and numerous doctoral students at MNIT Jaipur. Dr. Laxmi's research interests span Network Security, Android Security, Malware Analysis, Network-on-Chip Architectures, Routing Protocols, Side-Channel Attacks, Wireless Networks, and Mobile Security. Their work bridges theoretical security frameworks with practical implementations, particularly in mobile and embedded systems. Recent publications indicate a growing focus on AI-based security approaches including GAN applications for fuzzing and deep learning for image dehazing. The research trajectory shows increasing sophistication in security analysis techniques, evolving from basic malware detection to advanced side-channel attack analysis and sophisticated network security protocols. Recent publications demonstrate expertise in both theoretical frameworks and practical implementations with applications in real-world security challenges. Dr. Laxmi has mentored numerous graduate students including Vineeta Jain, Anugrah Jain, Sonal Yadav, Mohit Singh, and Gaurav Singal, who appear as co-authors across multiple publications. Their collaborative network extends to researchers at international institutions, indicating strong academic connections beyond their home institution.
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.
Prof. Dr. Teresa Sansour is a full Professor of Pedagogy and Didactics in Cases of Intellectual Development Impairments with Special Consideration of Inclusive Educational Processes at the Institute for Special and Rehabilitation Education, Carl von Ossietzky University of Oldenburg. She joined the university in April 2020 and has held leadership roles including Vice Director for Teaching at the Center for Teacher Education (since October 2021) and Deputy Institute Director (since April 2025). Her academic affiliations reflect a deep commitment to inclusive and special education. Her research focuses on educational interactions in the context of intellectual disabilities, inclusive subject didactics, the participation of people with complex disabilities, and the professionalization of educators and prospective teachers. Key research areas include inclusive literacy, art education, teacher motivation, and social integration. She leads significant funded projects such as Literary Texts in Simple Language (LiES) and Lighthouses for Participation , both aimed at enhancing inclusion for people with disabilities. The recent publications of Prof. Sansour span topics such as school absenteeism in autism, self-concept in intellectual disabilities, inclusive art education, and participation models. Her work demonstrates a strong interdisciplinary and applied focus, combining qualitative methods with pedagogical innovation. She frequently publishes in peer-reviewed journals and edited volumes on special education, inclusive didactics, and disability studies. Member, German Society for Educational Research (DGFE), Section Special Education Member, Network for Complex Disabilities e.V. Chair, Advisory Board of the Georg-Leffers-Stiftung Chair, Association for the Promotion of Pedagogical Rehabilitation and Social Integration of People in Risk Situations Board Member, German Interdisciplinary Society for Research Promotion for People with Intellectual Disabilities (DIFGB) Prof. Sansour actively contributes to academic leadership and teacher training. She serves as program coordinator for the Bachelor’s in Special Education and accreditation officer for the Special Education/Social Studies cluster. Her work includes advising on inclusive curricula, fostering research collaborations, and securing external funding for inclusive initiatives. She has not received explicitly mentioned scientific awards in the provided text. She is involved in multiple collaborative research teams and projects focused on inclusion, literacy, and disability rights.
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.
Prof. Alexander Pretschner is a Professor of Software & Systems Engineering at the Technical University of Munich (TUM) and Founding Director of the Bavarian Research Institute for Digital Transformation (bidt). He also serves as Scientific Director of fortiss, a Bavarian research institute for software-intensive systems. His research focuses on software engineering, testing, information security, and ethical software development. Pretschner holds a PhD from TUM and has held academic positions at Karlsruhe Institute of Technology (KIT) and TU Kaiserslautern. He is a co-editor of several prestigious journals, including IEEE Transactions on Reliability and the Journal of Software Testing, Verification and Reliability. Education: PhD in Computer Science, Technical University of Munich MSc in Computer Science, University of Kansas (on Fulbright Scholarship) Diplom in Computer Science, RWTH Aachen University Research Interests: His work spans testing methodologies, secure software design, and ethical considerations in agile development. Notable contributions include frameworks for metamorphic testing, distributed data usage control, and accountability mechanisms for cyber-physical systems. Awards: IBM Faculty Award (2012, 2013) Google Focused Research Award (2011, 2012) EARTO Innovation Prize (2014) 2nd Platz Supervisory Award (2020) Advising & Grants: Pretschner has supervised numerous PhD and Master’s students, contributing to over 200 publications. He leads projects like EDAP (Ethical Deliberation in Agile Processes) and collaborates with industry partners on cybersecurity and AI ethics initiatives. Labs & Teams: His work is anchored in bidt, fortiss, and TUM’s Chair of Software & Systems Engineering, focusing on societal impacts of digitalization and trustworthy AI systems.
