Find Academic Supervisors

• Science Communication
• Rhetoric
• Knowledge Communication
• +7 more

Olaf Kramer is a Professor of Rhetoric and Knowledge Communication at the Department of General Rhetoric, Faculty of Humanities, University of Tübingen. He leads the Presentation Skills Research Center and serves as Managing Director of the Research Center for Science Communication (RCS). Since 2021, he has been the spokesperson for the RHET AI Center, focusing on artificial intelligence in science communication. Kramer is also a key editor of Science Notes magazine and the neue rhetorik / new rhetoric book series. Professor, Department of General Rhetoric, University of Tübingen Head, Presentation Skills Research Center Managing Director, Research Center for Science Communication (RCS) Spokesperson, RHET AI Center Editor, Science Notes and neue rhetorik series Education: Studied General Rhetoric, German Literature, Philosophy, and Psychology in Tübingen, Frankfurt (with Jürgen Habermas), and Chapel Hill, USA (with Lawrence Grossberg) Ph.D. (2008): Rhetoric in Goethe Habilitation (2015): Virtual Reality, with teaching authorization in General Rhetoric and German Literary Studies Olaf Kramer's research centers on science communication , communicative competence , political communication , digital rhetoric , and virtuality . His work bridges classical rhetorical theory with contemporary media and public discourse, particularly in scientific and political contexts. He investigates how knowledge is recontextualized in public communication and how digital platforms reshape rhetorical practices. The recent publications reflect a strong trend in interdisciplinary rhetoric , combining insights from law, theology, education, and digital media. His work explores the rhetorical dimensions of judicial decisions, science slams, social media, and AI, emphasizing the role of narrative, visual design, and audience engagement in shaping public understanding. The integration of virtuality and digital navigation into rhetorical theory highlights his innovative approach to modern communication challenges. Scientific Awards: No specific awards are mentioned in the provided text. Kramer actively supervises a large cohort of students and researchers, many of whom have collaborated on publications and projects. He has secured third-party funding for major initiatives like the Presentation Skills Research Center. His advisory and leadership roles extend to university governance, public engagement, and professional consulting for organizations such as the Max Planck Society and the German Foreign Office. He is deeply involved in public science communication through the Science-Notes lecture series, which he founded and moderates, and through media appearances on ZDF/3sat and RTL. His work also includes designing and leading rhetorical training programs for academic, corporate, and governmental clients, demonstrating a strong commitment to translating academic knowledge into practical applications.

Jinqiu YangView profile

Associate Professor

• software reliability
• quality assurance of machine learning systems
• autonomous vehicles
• +5 more

Jinqiu Yang is an Associate Professor in the Department of Computer Science and Software Engineering at Concordia University in Montreal, Canada. Her research focuses on improving software reliability and quality assurance, particularly in the context of machine learning systems and autonomous vehicles. She leads active research projects in software testing, automated program repair, and mining software repositories, with strong connections to both academic and industrial applications. Her research interests span software reliability, quality assurance of machine learning systems including autonomous vehicles, software testing, automated program repair, text analytics of software artifacts, and mining software repositories. She has developed novel approaches for testing deep learning libraries, evaluating robustness in autonomous driving systems, and tracking the evolution of static code warnings. Her work bridges traditional software engineering with emerging challenges in AI systems, addressing critical issues of reliability and safety in complex software environments. Yang's recent publications (2021-2025) demonstrate a clear trajectory toward AI/ML system reliability, with increasing focus on autonomous vehicles, concept drift detection, and security aspects of large language models. Her work spans both theoretical foundations and practical applications, often involving empirical studies of real-world systems and development of practical tools to address identified challenges. ACM SIGSOFT Distinguished Paper Award Dr. Yang actively mentors graduate students and is currently recruiting Master's and PhD candidates. She has secured significant research funding including NSERC Discovery Grants (2019-2025), Gina Cody Research and Innovation Fellowship (2024-2026), and participation in the NSERC CREATE Program SE4AI (2021-2026). Her research is supported by multiple grants including NOVA – FRQNT-NSERC PROGRAM (2024-2027) and Volt-Age Seed Grant (2024-2026). She leads research in the O-RISA Lab at Concordia University, focusing on reliability and security aspects of intelligent software systems. Her team collaborates with industry partners including IBM, where she previously worked at IBM Watson Research Lab and IBM CAS, bringing practical experience to her academic research.

Jingling XueView profile

Professor

• Programming Languages
• Compilers
• Program Analysis
• +5 more

Jingling Xue is a Scientia Professor at the School of Computer Science and Engineering at the University of New South Wales (UNSW) in Sydney, Australia. As an IEEE Fellow of the Computer Society, he leads the Programming Languages and Compilers research group, focusing on practical applications of compiler optimization and program analysis techniques. His work bridges theoretical foundations with real-world software systems, particularly in developing open-source tools for large-scale program analysis. Professor Xue received his B.Eng and M.Eng degrees from Tsinghua University in 1984 and 1987, respectively, followed by a PhD from the University of Edinburgh in 1992. His academic journey has established him as a leading figure in programming languages and compiler technology. Xue's research spans programming languages, compiler technology, and program analysis with emphasis on practical relevance. His current projects include compiler techniques for improving parallelism and locality, pointer/alias analysis for million-line-scale programs, and static/dynamic analysis for detecting bugs and security vulnerabilities in real-world applications like web browsers and Android apps. His group actively develops open-source tools to support scientific replicability and reproducibility in these areas. His recent publications demonstrate a strong focus on applying program analysis techniques to modern challenges including AI compilers, homomorphic encryption, security vulnerability detection, and graph processing systems. The work shows evolution from traditional compiler optimization to addressing emerging domains like privacy-preserving computation and deep learning systems while maintaining rigorous theoretical foundations. Scientific Awards: Best Paper Award at CGO'13 Best Paper Award at CGO'16 Distinguished Paper Award at ECOOP'16 Distinguished Paper Award at ICSE'18 Distinguished Paper Award at ISSTA'19 Distinguished Paper Award at ASE'19 Distinguished Artifact Award at ISSTA'23 Best Artifact Award at FSE'23 Distinguished Paper Award at ASE'23 Test-of-Time Award at CGO'21 Professor Xue has successfully supervised 30 PhD students to completion, many of whom now work as professors or researchers in academia and industry. He has served as Program Chair for major conferences including LCTES'13, CC'18, CGO'20, and General Chair for LCTES'20. His group currently focuses on memory safety in Rust, smart contract analysis, AI compilers, compilation for privacy-preserving computation, and adversarial attacks in deep learning. The Programming Languages and Compilers group maintains strong connections with industry partners, translating theoretical advances into practical tools for real-world software development challenges. Their work on pointer analysis, memory safety, and compiler optimizations continues to influence both academic research and industrial practice.

• Computer Architecture
• Hardware Design
• Signal Processing
• +7 more

Prof. Dr.-Ing. Holger Blume serves as Vice President for Research and Transfer at Leibniz University Hannover while maintaining his academic position as Professor in the Architectures and Systems Section within the Faculty of Electrical Engineering and Computer Science. He holds multiple leadership positions including Chairperson of the Research Commission and Central Ethics Committee, Executive Board member of eNIFE (Leibniz Research Initiative for Neurosciences), and membership in both the Laboratory of Nano and Quantum Engineering and L3S Research Centre. His research interests span computer architecture, hardware design, signal processing, AI accelerators, hearing aid technology, and biomedical engineering. His work bridges theoretical computer science with practical applications in automotive systems, medical devices, and quantum engineering. Professor Blume's research demonstrates strong interdisciplinary connections between electrical engineering, computer science, and biomedical applications, with particular emphasis on hardware-oriented solutions for real-world problems. Analysis of his recent publications (2023-2025) reveals a strong focus on hardware acceleration for AI and signal processing applications, particularly in automotive radar/LiDAR systems and hearing aid technology. His work shows consistent innovation in RISC-V processor design, specialized hardware for mathematical functions, and biomedical applications of engineering principles. The research demonstrates a clear trajectory toward energy-efficient, specialized computing architectures for specific application domains. As Vice President for Research and Transfer, Professor Blume oversees significant research initiatives at Leibniz University Hannover, which hosts multiple Clusters of Excellence including PhoenixD (Photonics, Optics, and Engineering), QuantumFrontiers, and Hearing4all. The university participates in numerous collaborative research centers and junior research groups funded by DFG, BMBF, and EU programs. Professor Blume is actively involved in multiple research facilities including the Laboratory of Nano and Quantum Engineering and the L3S Research Centre. His work connects with Leibniz University's research focuses on optical technologies, quantum optics and gravitational physics, and biomedical research and technology. His leadership positions indicate strong involvement in shaping the research strategy and ethical framework of the university's scientific endeavors.

Bashir KazimiView profile

Researcher

• Deep Learning
• Computer Vision
• Materials Science
• +3 more

Dr.-Ing. Bashir Kazimi is a group leader at the Materials Data Science and Informatics (IAS-9) department within the Institute for Advanced Simulation at Forschungszentrum Jülich. His work focuses on advancing deep learning and computer vision techniques for electron microscopy data analysis, enabling efficient material characterization. Expertise: Deep Learning, Computer Vision, Image Analysis Collaboration: Works closely with the Ernst-Ruska-Center (ER-C) for electron microscopy expertise Research Interests: Bashir develops and applies deep learning methods for tasks such as denoising, super-resolution, semantic segmentation, and tracking in electron microscopy. His applications span nanomaterial characterization, crystallographic defect identification, and orientation mapping. Scientific Trends: His recent publications highlight advancements in self-supervised learning, semantic segmentation of TEM images, and applications of deep learning to both materials science and archaeological monument detection in geospatial data. Scientific Achievement: Admitted to the Young Excellent Scientist Program (YESP) in 2024, supporting leadership development and scientific visibility Advising: Supervises Shrindhi Bhat , a PhD student in his group. He is involved in projects like FAST-EMI (Deep-learning assisted fast in situ 4D electron microscope imaging), with a focus on enhancing materials analysis through AI.

Peter Friedrich StephanView profile

Professor

• Digital Transformation
• Social Transformation
• Design Theory
• +3 more

Prof. Peter Friedrich Stephan is a full Professor of Transformation Design at the Academy of Media Arts Cologne (KHM). His work focuses on digital and social transformation, leveraging design methodologies to address stakeholder concerns and artifacts. He co-founded the Computational Design program in 1994 and has held roles at institutions like the University of the Arts Berlin and St. Gallen. His research explores cognitive and emotional aspects of transformation, with projects funded by agencies such as BMBF and acatech. Education: Design, Business Communication, and Music (Berlin & New York) Key Roles: Professor at KHM since 1997 Guest Lecturer at University of the Arts Berlin (2002–2013) Consultant for Fraunhofer Gesellschaft, FWF, and DEGinvest Research Interests: Stephan’s work bridges design theory and practice, emphasizing tools like the Concern Canvas and Hypercycle of Transformation . He explores how design can mediate between societal concerns and technological systems, informed by Actor-Network Theory (ANT) and Bruno Latour’s philosophy. His 2024 monograph Designing Concerns synthesizes these ideas, while earlier works like Knowledge Media Design (2005) and Events and E-Commerce (2000) address digital and commercial ecosystems. Publications & Awards: Over 50 articles, two edited books, and notable awards include the Cologne Design Award (2013) and CD-ROM of the Year (1999). Key projects include Intelligent Objects (2008–2009) and Medienquadrat (2002–2004). His work spans academic, artistic, and industrial collaborations. Labs & Teams: Active in KHM’s exMedia Lab, focusing on experimental design and digital transformation.

• Object-Oriented Programming
• Software Engineering
• Formal Methods
• +5 more

Bertrand Meyer is a renowned academic and software engineering expert affiliated with Constructor University in Switzerland. He previously held positions at ETH Zurich (2001-2016), the University of Toulouse (2015-2016), and Monash University. His research focuses on object-oriented programming, software engineering, formal methods, and programming languages. He is best known for developing the Eiffel programming language and pioneering the 'Design by Contract' paradigm. Meyer earned his PhD from the University of Nancy, France. His contributions include seminal textbooks like *Object-Oriented Software Construction* (1988, 1997), *Touch of Class* (2009), and *Agile!* (2014). He has received the ACM Software System Award (2006) for his work on Eiffel. His research emphasizes rigorous software design principles, formal verification, and practical software engineering practices. Key innovations include: Design by Contract methodology Advancements in object-oriented design patterns Contributions to component-based development Work on software testing and validation techniques Meyer has authored over 374 publications spanning journals, conferences, and books. His work bridges theoretical foundations and practical software development methodologies.

Lutz PrecheltView profile

Professor

• Software Engineering
• Empirical Software Engineering
• Agile Processes
• +5 more

Lutz Prechelt is Professor of Informatics at Freie Universität Berlin where he heads the Software Engineering research group (AG SE). His academic journey spans theoretical foundations, industry experience, and extensive empirical research in software engineering. He has held significant administrative positions including Executive Director of the Institute of Informatics and member of various academic senates. Prechelt's research interests have evolved from artificial intelligence and neural networks to empirical software engineering, with a recent focus on qualitative approaches to Agile processes and Pair Programming. His work has consistently emphasized methodological rigor, having conducted pioneering controlled experiments on topics like type-checking, inheritance depth, design patterns, and the Personal Software Process. His research has also ventured into plagiarism detection (JPlag), melody recognition, and qualitative studies of pair programming dynamics. His publication record shows a clear transition from quantitative to qualitative approaches in empirical software engineering. Early work featured controlled experiments on specific technical aspects of software development, while more recent publications focus on qualitative analysis of team dynamics, agile methodologies, and research methodology itself. A notable thread throughout his career has been platform comparison studies (Plat_Forms) examining how different technologies affect development outcomes. Ernst Denert Software Engineering Award 2020 Prechelt has served extensively as reviewer for major funding agencies including DFG, EU, ERC, and BMBF, and as editor for journals like Journal of Universal Computer Science and Transactions on Pattern Languages of Programming. He founded the Forum for Negative Results (FNR) to address publication bias in scientific research. His research group has developed several notable software tools including Saros for distributed pair programming, JPlag for plagiarism detection, and tools for maintainable lecture videos.

• Inclusive Education
• Special Education
• Pedagogy for Intellectual Disabilities
• +5 more

Dr. Judith Riegert is a Research Associate at the Humboldt University of Berlin, Faculty of Humanities, Social Sciences, and Education, working at the Institute of Rehabilitation Sciences in the Department of Education for People with Intellectual Disabilities. She has been in this position since October 2016, with previous experience as Research Associate and Program Coordinator at the same institution. Her academic journey includes serving as Deputy Professor at Leibniz University Hannover (2016-2018) and as a Visiting Professor at Humboldt University (2019). 1997-2002: Studies at Justus Liebig University of Giessen and Heidelberg University of Education 2003-2004: Traineeship at Seminar for Didactics and Teacher Training Heidelberg 2004-2006: Special education teacher at Carl Orff Special School 2012: Completed doctorate (Dr. phil.) at Humboldt University Dr. Riegert's research focuses on educational theory questions in intellectual disability contexts, trans- and intermediality in inclusive literature teaching, pedagogical professionalization for inclusive subject teaching, and participation of adults with severe disabilities. Her work bridges theoretical frameworks with practical classroom applications, examining how to create meaningful learning experiences across subject areas while maintaining academic rigor. She investigates the tension between educational standards and individualized instruction, particularly in German, history, and mathematics education. Her recent publications demonstrate a strong focus on participation frameworks for people with severe disabilities, inclusive teaching methodologies across subject areas, and the development of pedagogical approaches that bridge educational theory and classroom practice. Her work consistently addresses the challenge of maintaining subject integrity while adapting instruction to diverse learning needs. November 5, 2014: Prize for Good Teaching 2014 from Humboldt University's Faculty of Humanities, Social Sciences and Education February 16, 2016: Honorary certificate from Polytechnische Gesellschaft Foundation for the 'Animals in Numbers' project Dr. Riegert provides academic advising for special education and primary school teaching students (surnames He to Z), supervises bachelor's and master's theses, and offers consultation hours both in person and via Zoom. Her advising focuses on supporting students in the M.Ed. program, particularly addressing application concerns and transcript issues. As a member of the German Society for Educational Science (DGfE), she contributes to research teams examining inclusive education methodologies and implementation of inclusive practices across educational settings.

Matthias BaitschView profile

Professor

• Construction Informatics
• Numerical Methods
• Structural Optimization
• +3 more

Matthias Baitsch serves as Professor of Construction Informatics and Numerical Methods in the Department of Civil and Environmental Engineering at Bochum University of Applied Sciences, where he concurrently heads the BIM Institute. His academic trajectory includes research assistant and senior engineer roles at Ruhr-University Bochum (2000-2009), academic coordination at the Vietnamese-German University (2009-2012), and an acting professorship at the University of Kassel (2012-2014). His educational foundation comprises: Civil Engineering studies at the University of Dortmund (1991-1997) under the interdisciplinary "Dortmund Model" Doctorate from Ruhr-University Bochum (2003) on geometric imperfection-based optimization of compressive beam structures Professor Baitsch's research integrates computational mechanics with civil engineering practice, specializing in construction informatics, numerical optimization, and high-order finite element methods. His work pioneers distributed optimization frameworks, structural health monitoring for wind energy infrastructure, and BIM-based construction informatics. Key methodological contributions include hp-FEM implementations, parallel optimization algorithms, and mobile structural analysis tools. Analysis of his recent publications reveals three dominant research trajectories: (1) Advanced numerical methods for structural optimization under uncertainty, (2) Health monitoring-driven lifetime prediction for wind turbine systems, and (3) Computational modeling of tunnel environments using viscoacoustic inversion techniques. These threads demonstrate consistent focus on robust numerical implementations and real-world civil engineering applications. As Head of the BIM Institute, he leads institutional efforts in digital construction technologies, fostering industry-academia collaboration on building information modeling standards and applications. His teaching portfolio spans foundational mathematics, numerical methods, and computer science for civil engineering students, emphasizing practical computational skills.

Max WillertView profile

Lecturer

• Computational Geometry
• Algorithm Design
• Theoretical Computer Science
• +3 more

Dr. Max Willert is affiliated with the Theoretical Computer Science Group at the Institut für Informatik, part of the Fachbereich Mathematik und Informatik at Freie Universität Berlin. His research focuses on computational geometry, algorithm design, and theoretical computer science, with a particular emphasis on problems involving polygonal domains, geometric algorithms, and combinatorial optimization. He has contributed to routing schemes, conflict-free chromatic guarding, and geometric covering problems. Education includes a Bachelor's thesis (2014) on orthogonal variants of the chromatic art gallery problem and a Master's thesis (2016) on routing schemes for disk graphs and polygons. His work bridges theoretical foundations with practical algorithmic solutions in geometric computing. Teaching spans from 2011 to 2020, covering courses like Informatik A/B, ProInformatik I, randomized algorithms, and programming. He has also led exercise sessions and seminars in topics such as logic, discrete mathematics, and object-oriented programming. His publications, including contributions to Computational Geometry: Theory and Applications and ISAAC , reflect expertise in geometric algorithms and discrete mathematics. Collaborations include work on routing in polygonal domains, chromatic guarding, and stabbing intersecting disks.

Michael CoblenzView profile

Assistant Professor

• Usability of programming languages
• User-centered programming language design
• Type systems for safety
• +6 more

Michael Coblenz is an Assistant Professor in the Computer Science Department at University of California, San Diego. His research focuses on integrating user-centered design into programming language development, creating safer languages for blockchain and scientific computing. He completed his Ph.D. at Carnegie Mellon University under Jonathan Aldrich and Brad A. Myers, followed by a Basili postdoctoral fellowship at University of Maryland. Specializes in usability of programming languages Created Obsidian language for safer smart contracts Developed PLIERS methodology for iterative language design Active in Rust usability and REST API quality research His work bridges programming languages and human-computer interaction, with recent projects including Kale (safer spreadsheets) and climate change-focused programming tools. He has served on program committees for SPLASH, VL/HCC, and HATRA conferences. 2025: Graduate Consortium Co-chair at VL/HCC 2024: HATRA Organizing Chair 2023: Doctoral Symposium Chair at SPLASH

Elena ZuccaView profile

Associate Professor

• Programming Languages
• Type Systems
• Formal Semantics
• +6 more

Elena Zucca is an Associate Professor in the Department of Computer Science, Bioengineering, Robotics and Systems Engineering (DIBRIS) at the University of Genoa, Italy. She has a strong research focus on programming languages, particularly in the areas of type systems, formal semantics, and coinduction. Her work bridges theoretical foundations with practical implementations, as evidenced by her publications on topics like Featherweight Java, corecursion, and soundness proofs for programming language features. Her research interests span the theoretical and practical aspects of programming languages. She investigates the formal semantics of programming constructs, particularly focusing on the boundaries between finite and infinite computations. Her work on coinduction and corecursion explores how to safely handle infinite data structures and computations. She has made significant contributions to understanding soundness in programming language features, especially in relation to resource-aware semantics. Her research often combines theoretical foundations with practical implementations, as seen in her work on Featherweight Java extensions and effect systems. Analysis of her recent publications reveals a consistent focus on advanced type systems and semantics. Her work explores the theoretical boundaries of programming language features while maintaining practical relevance. A recurring theme is the relationship between finite and infinite computations, with particular attention to soundness guarantees. Her research has evolved from foundational work on lambda calculus and object-oriented programming toward more specialized topics like graded types, coeffects, and resource-aware semantics. Elena Zucca has been actively involved in the programming languages research community, serving on program committees for major conferences including SPLASH, ECOOP, and POPL. She has mentored students through doctoral courses on Declarative Programming and (Co)Induction. Her research has been supported through participation in various academic programs, including the SEPL research program mentioned in her course materials. She teaches a diverse range of courses at the University of Genoa, from undergraduate to doctoral levels. Her teaching portfolio includes Automata Theory and Computability, Algorithms Analysis and Design, Principles and Paradigms of Programming Languages, and specialized doctoral courses on Declarative Programming and (Co)Induction. Her courses often reflect her research interests, covering theoretical foundations of programming languages, formal methods, and advanced programming paradigms.

Anandita BajpaiView profile

Research Fellow

• Cold War History
• Transnational History
• Media Studies
• +6 more

Dr. Anandita Bajpai is a Research Fellow at Leibniz-Zentrum Moderner Orient (ZMO) in Berlin and Principal Investigator for the Leibniz Collaborative Excellence Project Crafting Entanglements: Afro-Asian Pasts of the Global Cold War (CRAFTE). Her work bridges historical anthropology, media studies, and transnational Cold War history. Research interests include media entanglements , affective trajectories of international radio broadcasting , and material culture of Cold War radio networks . She explores how radio objects (gifts, letters, journals) shaped Afro-Asian solidarity and everyday life in India. Articles reveal interdisciplinary engagement with Cold War geopolitics , radio archives , and 听众集体记忆 . Themes span radio diplomacy , epistolary networks , and transnational affective spaces . Leibniz Collaborative Excellence Funding 2023-26 DAAD Scholarships (2009–2014) Erasmus Mundus Scholarship (2006–2008) Geeta Chopra Memorial Scholarship (2006) She has supervised BA/MA theses at Humboldt-Universität zu Berlin and organized the Humboldt India Project (HIP) workshops. Her fieldwork spans Bihar, Rajasthan, Uttar Pradesh, Haryana, and Chhattisgarh, focusing on radio-objects in listeners’ homes .

Sven KlaaßenView profile

Research Fellow

• Machine Learning
• Causal Inference
• Deep Learning
• +1 more

Dr. Sven Klaaßen serves as a Research Fellow at the University of Hamburg's Hamburg Business School within the Professorship for Statistics with Application in Business Administration, collaborating closely with Prof. Dr. Martin Spindler since 2021. His research focuses on developing advanced statistical methodologies for complex data environments. His academic credentials include: Ph.D. in Statistics from Hamburg Business School (2020) Visiting Scholar at MIT Department of Economics (2022) M.Sc. in Business Mathematics from University of Hamburg (2016) BSc in Business Mathematics from University of Hamburg (2014) Dr. Klaaßen's research program centers on Machine Learning, Causal Inference, Deep Learning, and High-Dimensional Statistics, with particular emphasis on developing robust inference techniques for modern data challenges. His work bridges theoretical statistics with practical applications in business analytics and econometrics, often addressing the complexities of high-dimensional datasets where traditional methods fail. Analysis of his recent publications reveals a clear trajectory toward integrating machine learning with causal inference frameworks, exemplified by his leadership in the DoubleML software ecosystem. His research increasingly tackles multimodal data challenges while maintaining rigorous statistical foundations, with applications spanning economics, operations research, and business decision systems. As an active member of Prof. Spindler's research group, Dr. Klaaßen contributes to collaborative projects developing open-source statistical tools and advancing methodological frontiers in causal machine learning. The team maintains strong industry and academic partnerships focused on translating theoretical innovations into practical analytical solutions.