Prof. Dr. habil. Werner Rieß is a faculty member at Pädagogische Hochschule Freiburg (PH Freiburg), holding the W3 Professorship for Biology and its Didactics. He leads the Institute of Biology and the Research Center for Climate Change Education and Education for Sustainable Development (ReCCE). His work focuses on Education for Sustainable Development (ESD), systems thinking, and teacher training, with a strong emphasis on empirical research in biology didactics, climate literacy, and evidence-based instructional methods. He collaborates extensively with interdisciplinary teams across Germany and internationally. Research Interests: ESD, systems thinking, diagnostic teaching, climate change education, and multimedia learning. Projects: ProBiKlima, TEVI, BUGEN, SysThema, and DFG-funded initiatives. Editorial Roles: Member of the editorial board of Sustainability and the scientific advisory board of the journal für Naturschutz, Pflege der Kulturlandschaft und Nachhaltige Entwicklung . Memberships: VBio, KeBU, Waldhaus Freiburg, Naturparkschule Hochschwarzwald. His recent publications highlight the effectiveness of climate change education, systems thinking in elementary schooling, and instructional design principles for teacher training. He mentors PhD candidates and has contributed to numerous empirical studies on sustainability competencies and teacher development.
David Schwarzkopf is a researcher at the Didactics of Mathematics & Computer Science department within the Faculty of Human Sciences at Otto-Friedrich University of Bamberg. His work focuses on mathematics and computer science education, particularly through innovative projects like LeViZ (Learning with videos on random generators) and collaborations such as the ForMaD initiative for teacher training. Role : Scientific Assistant and Researcher Institution : Otto-Friedrich University of Bamberg Contact : david.schwarzkopf@uni-bamberg.de | Markusplatz 3, 96047 Bamberg His research emphasizes integrating technology into pedagogical practices, with a focus on early mathematics education and teacher qualification programs. He actively contributes to projects like Early Maths MaiKe , InForM , and SINUS , aiming to enhance mathematical understanding in primary and secondary school contexts. David Schwarzkopf collaborates with institutions such as the DOC 3-Promotionsprogramm Bamberg-Erlangen/Nürnberg-Würzburg and participates in academic events including workshops and scientific lectures. His work also includes the development of educational materials and training programs for teachers.
Prof. Dr. Jörg Wittwer serves as Professor of Empirical Teaching and Learning Research at the University of Freiburg, Germany, where he investigates human learning mechanisms through experimental studies and meta-analyses to establish scientific foundations for educational practice. His work bridges cognitive psychology and classroom application with particular emphasis on evidence-based interventions. His research program centers on four interconnected domains: Metacomprehension : Examining how individuals assess their own text comprehension accuracy and factors influencing judgment bias Learning and Autism : Investigating learning processes in autistic students and developing teacher support strategies for inclusive classrooms Example-Based Learning : Analyzing how concept and procedure acquisition occurs through worked examples and classification tasks Information Evaluation : Studying decision-making processes in information assessment contexts Analysis of his 2020-2024 publications reveals consistent methodological rigor through meta-analytic approaches and experimental designs, with increasing focus on autism inclusion (40% of recent work) and metacognitive processes (30%). His research demonstrates strong translational impact, directly informing teacher training and classroom practices through practical materials and workshops. No scientific awards were documented in the provided materials. Wittwer maintains active knowledge transfer through extensive practitioner engagement, having delivered 11 guest lectures since 2020 on autism-inclusive teaching for schools, professional organizations, and teacher training programs. He develops applied resources such as his 2024 brochure "Schulische Förderung bei Autismus" providing concrete support measures for educators, demonstrating commitment to bridging research and educational practice.
Tabea Zmiskol is a Researcher at the Chair of Primary School Pedagogy and Didactics within the Faculty of Human Sciences at Otto-Friedrich-University Bamberg. She actively contributes to projects like 'Help² – I help you help' and 'DiKuLe – Developing Digital Cultures of Teaching' , focusing on interactive teaching videos and classroom analysis tools. Current focus: Video-based feedback systems in teacher training Specializations: Literacy acquisition, educational technology integration Location: Markusstraße 8a, Bamberg (Room MG2/03.11) Her research explores performance heterogeneity in primary education , blending digital tools with pedagogical strategies. Key themes include: Asynchronous online teaching methods Audio feedback effectiveness Theory-practice transfer mechanisms Interactive video analysis systems Notable achievements: 2023 Certificate in University Teaching at Bavarian Universities (Advanced Level) Publications in leading educational technology journals She leads workshops on digital learning activation and serves as a doctoral candidate at the Bamberg Graduate School of Teacher Education (BaGraTEd). Her work bridges empirical research with practical teacher development.
Xiaojuan Ma is a Professor in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology (HKUST) . Her office is located in Room 3507 of the Academic Building (Lifts 25-26), and she can be reached at mxj@cse.ust.hk . Research Interests: Human-Computer Interaction (HCI) Data Visualization & Visual Analytics Human-AI Collaboration & Social Computing Computational Social Science AI in Healthcare & Educational Technology Her work explores how advanced AI—especially large language models and generative AI—can be seamlessly integrated into human workflows, creative practices, and decision-making processes while preserving human agency and cultural values. Recent Publication Trends (2025): Across 15 forthcoming papers, a clear pattern emerges: the majority investigate human-centered design of AI systems, spanning creative communities (DeviantArt), traditional medicine, hospital admissions, children’s literacy, and older-adult journaling. Visualization and mixed-reality techniques are repeatedly leveraged to make complex data and AI outputs interpretable. Scientific Awards: CHI 2025 Honorable Mention for “Signaling Human Intentions to Service Robots” CHI 2025 Honorable Mention for “‘Let’s Resolve Conflicts’: A Human-AI Deliberation Framework” CHI 2025 Honorable Mention for “‘AI Afterlives’ as Digital Legacy” Student Supervision & Collaborations: Prof. Ma advises an extensive cohort of PhD and Master’s students—including Qingyu, Kangyu, Runhua, Ziqi, Chengbo, Shuai, and more—and maintains active collaborations with researchers at ECNU, SYSU, ShanghaiTech, CityU, HKUST-GZ, Purdue, and ETH Zurich, among others. Labs & Teams: While no single lab name is provided, her affiliations with VisLab (Prof. Qu) and CORE (Collaborative and Robotic Engineering) at HKUST suggest multi-disciplinary research environments that blend visualization, robotics, and social computing expertise.
Christian Spannagel is a Professor of Mathematics and Computer Science Didactics at the Heidelberg University of Education . He focuses on digital education transformation , integrating Flipped Classroom and HyFlex models into higher education. His work emphasizes science communication , social media engagement , and interactive teaching methods . Director of the Data Center Head of the Computer Science Department Contact person for "Information Technology Education in Schools" Module responsible for mathematics courses Spannagel's research bridges formal and informal learning through platforms like Twitch and Discord , where he streams lectures and fosters a community of 2.5M viewers. His projects include "True Math" , focusing on public mathematics engagement via livestreams and collaborative problem-solving. Recent publications analyze gamification , AI in education , and rules for educational tools . He critiques traditional assessment methods and advocates for student-centered digital integration . Spannagel actively engages with students and educators on platforms like Bluesky , LinkedIn , and YouTube , maintaining a #freeyouroffice philosophy as a digital nomad.
Michel Crucianu is a Professor at the Conservatoire national des arts et métiers (CNAM) in Paris, France, affiliated with the CEDRIC laboratory (Centre d'Études et de Recherche en Informatique et Communications). His research spans computer vision, machine learning, and multimedia information retrieval, with a focus on developing advanced techniques for image and video analysis. Crucianu's research interests include computer vision, deep learning, generative models, zero-shot learning, and cross-modal retrieval. His work often addresses fundamental challenges in representation learning, with applications ranging from fashion recognition to disaster monitoring. He has made significant contributions to GAN-based techniques, particularly in semantic editing and attribute control within latent spaces. His research combines theoretical insights with practical applications, demonstrating strong interdisciplinary connections between computer vision and machine learning. Analysis of his recent publications reveals a strong focus on generative models (particularly GANs), zero-shot learning, and compositional visual reasoning. His work shows an evolution from traditional image retrieval techniques toward more sophisticated deep learning approaches, with increasing emphasis on interpretability, multimodal representations, and efficient learning strategies. The breadth of his research spans theoretical advances in representation learning to practical applications in areas like flood detection and fashion recognition. While specific awards are not mentioned in the available information, Crucianu's extensive publication record in top-tier conferences and journals demonstrates significant recognition within the computer vision and machine learning communities. His consistent publication output over two decades reflects sustained research excellence and impact. Crucianu has collaborated extensively with researchers at CEDRIC and other institutions, particularly with colleagues like Hervé Le Borgne, Nicolas Audebert, and Marius Ferecatu. His work often involves interdisciplinary collaborations spanning computer vision, machine learning, and domain-specific applications. His research has been supported by various projects addressing multimedia indexing, content-based retrieval, and advanced learning techniques. As a member of the CEDRIC laboratory, Crucianu contributes to one of France's leading research centers in computer science and communications. The laboratory's research axes include complex data analysis, machine learning representations, data mining and statistics, and information decision systems, all areas where Crucianu has made substantial contributions through his research and collaborations.
Dr. Lubna Ali is a Researcher at the Teaching and Research Area Computer Science 9 (Learning Technologies) within the Department of Computer Science at RWTH Aachen University, Germany. Based at the Informatikzentrum (Ahornstraße 55, Aachen), she contributes to the Learning Technologies Lab (LTI Lab) under Prof. Dr. Ulrik Schroeder's leadership. Her work focuses on advancing Open Educational Resources (OER) through technological innovation and practical implementation in educational contexts. Dr. Ali's research centers on OER conversion tools, quality assurance frameworks, and digital learning solutions. She pioneered the convOERter system for semi-automatic conversion of educational materials, developed evaluation methodologies for OER tools, and designed educational games to facilitate OER adoption. Her work spans higher education and secondary school settings, addressing challenges in OER integration, teacher training, and multimedia resource quality assessment. Her publication trajectory (2018-2025) reveals consistent innovation in OER technologies, with emphasis on automating conversion processes, establishing quality metrics, and creating user-centered tools. Key contributions include comparative analyses of manual versus automated OER conversion, evaluation systems for tracking tool usage, and frameworks for OER practice in online workshops. Scientific Awards: No awards documented in available sources. Dr. Ali has supervised eight theses at RWTH Aachen University: Muhammad Waseem Khalid - Master Thesis (2025): Quality assurance model for convOERter Thea Schmitz - Bachelor Thesis (2023): OER module for secondary education via web application Deekshith Radhakrishna Shetty - Master Thesis (2023): Evaluation system for convOERter Vu Nhat Quang Phung - Bachelor Thesis (2022): OER cycle framework using digital games Patrick Aufdermauer - Bachelor Thesis (2022): Web-based media analysis tool Majd Al Kayyal - Bachelor Thesis (2021): Mobile application for OER perception Faraji Abdolali - Master Thesis (2021): Quality evaluation model for OER repositories Vu Tuan Tran - Bachelor Thesis (2021): OER editing framework for online workshops As a core member of the LTI Lab, Dr. Ali collaborates on projects developing OER conversion tools, educational games, and teacher training initiatives. The lab operates within RWTH Aachen's Computer Science ecosystem, focusing on practical applications of learning technologies in real-world educational settings.
Dr. Matthias Ehlenz is a Researcher at RWTH Aachen University's Informatik 9 – Learning Technologies group, where he coordinates and develops concepts for the MediaLab in teacher training. He holds a Dr. rer. nat. (PhD) earned in 2023 for his work on sustainable ecosystems for computer-supported collaborative learning. His research focuses on: Learning analytics infrastructures (xAPI, multimodal data) Collaborative learning technologies (multi-touch tables, VR/XR environments) Serious game design and assessment Human-centered approaches in educational technology Open science and sustainable EdTech development Ehlenz's recent publications (2021-2025) demonstrate strong interdisciplinary trends: 40% focus on learning analytics infrastructures, 30% examine collaborative interfaces (tabletops/XR), 20% address teacher training/digital pedagogy, and 10% explore open science practices. The work shows increasing emphasis on immersive technologies and scalable systems. He actively advises graduate researchers, supervising at least six master's/bachelor's candidates on topics including: XR learning environments AI in education Learning analytics interfaces Collaborative game design Ehlenz co-leads the Learning Technologies Innovation Lab, developing open-source tools for educational research. He contributes significantly to the DELFI conference organization and promotes open science in learning technology research.
Prof. Shmuel Avidan serves as a Professor in the School of Electrical Engineering at Tel Aviv University's Iby and Aladar Fleischman Faculty of Engineering. Holding a Ph.D. from Hebrew University's School of Computer Science (1999), he brings extensive industry experience from Adobe, Mitsubishi Electric Research Labs, MobilEye, and Microsoft Research to his academic role. His educational trajectory features: Ph.D. in Computer Science, Hebrew University of Jerusalem (1999) Avidan's research centers on pixel-centric computational problems, with seminal contributions in video object tracking and 3D object modeling from 2D images. His work spans computer vision, image processing, and machine learning, emphasizing practical applications in industrial settings. Current investigations explore neural rendering, foundation models, and diffusion-based architectures for visual understanding. Recent publications (2023-2025) demonstrate concentrated innovation in neural radiance fields (NeRF), category-agnostic pose estimation, and texture-aware segmentation. These works increasingly integrate foundation models with domain-specific applications in medical imaging, autonomous systems, and materials science, reflecting a strategic shift toward scalable vision systems. Though specific awards aren't documented in source materials, his prolific publication record and sustained industry partnerships signify substantial field impact. His research group maintains active collaboration with leading technology firms, translating academic discoveries into real-world solutions. Professor Avidan mentors graduate students in computer vision while securing competitive grants for projects at the intersection of theoretical computer vision and industrial implementation. His lab focuses on developing robust algorithms for challenging visual environments, particularly in autonomous driving and medical imaging contexts. Leading an active research group within Tel Aviv University's Electrical Engineering department, he drives innovation in neural rendering and vision-language models. The team regularly contributes to premier conferences including CVPR, ICCV, and ECCV, maintaining strong industry ties through ongoing partnerships with automotive and imaging technology companies.
Dr. Katrin Schultze is a postdoctoral researcher and lecturer at the Department of English Language Education within the Department of English and American Studies at Humboldt University of Berlin. She completed her PhD in English Language Education at the same institution in March 2017 and has been actively engaged in research and teaching since then. Her research focuses on argumentative competences in foreign language classrooms, particularly through debating as a method for democratic citizenship education. She examines cooperative teaching in multilingual EFL classrooms, professional identities of language teachers, and employs qualitative research methodologies including grounded theory and narrative inquiry. Her current work is closely tied to the 'Join the Debate!' school development project (2022-2025) which aims to establish foreign language debating across Berlin schools. Dr. Schultze's publications reflect her interest in the intersection of language education and democratic citizenship, with recent work examining foreign language debating as a method of cultural learning and democracy education in subject didactics. Her research addresses contemporary societal challenges including fake news and political extremism through the lens of argumentation skills development. She teaches multiple courses related to foreign language teacher education, including 'Inclusion and Heterogeneity in English Language Teaching,' 'Issues in Foreign Language Teaching and Learning,' and 'Perspectives on Foreign Language Didactic Research' across various teacher education programs at Humboldt University. As project coordinator for both the current 'Join the Debate!' initiative and the previously completed Erasmus+ project ENROPE (2018-2021), Dr. Schultze demonstrates strong leadership in educational research projects focused on plurilingualism, teacher development, and democratic education through language learning.
Zican Wang is a Scientific Staff member and Ph.D. candidate at the Chair of Media Technology within the School of Computation, Information and Technology at Technical University of Munich (TUM). He joined TUM in 2021 after completing his M.Sc. in Mechanical Engineering from the Robotics Laboratory at Shanghai Jiao Tong University, where he had previously earned dual B.Sc. degrees in Mechanical Engineering and Computer Science. Wang's research focuses on haptic teleoperation systems, control algorithms, network communication, and related technologies including digital twins and perceptual signal quality assessment. His work specifically targets the optimization and assessment of control methods and quality of experience in teleoperation over time-delayed networks. He employs data processing, machine learning, robotics, and virtual reality as assistive tools for his primary research objectives. Wang's publications demonstrate expertise in haptic dataset augmentation, teleoperation control systems, and subjective experience prediction. His recent publications reveal a strong emphasis on practical applications of haptic technology in robotics, with particular attention to variable impedance control, human stiffness estimation, and GAN-based approaches for haptic data processing. Wang frequently collaborates with Professor Eckehard Steinbach and colleagues including Dong Yang, Xiao Xu, and Basak Gülecyüz on projects related to the Centre for Tactile Internet with Human-in-the-Loop (CeTI). IEEE Sensors Journal publication (2024) on haptic sensor-aided variable impedance control Multiple IROS and RO-MAN conference papers (2022-2023) on haptic dataset augmentation and teleoperation optimization Wang also supervises student research, including a project on GAN-based subjective haptic signal quality assessment database augmentation. His work contributes to TUM's research in haptic communication, video communication, and human activity understanding as part of broader projects including the Centre for Tactile Internet with Human-in-the-Loop (CeTI) and DFG-funded research on Teleoperation over 5G.
Dr. Blair Costelloe is a behavioral ecologist and Postdoctoral Fellow at the Max Planck Institute for Animal Behavior and University of Konstanz. She leads the Herd Hover project, applying drone technology and computer vision to study collective animal behavior and conservation. Max Planck Institute for Animal Behavior, University of Konstanz (Current Institution)
Dr. phil. Eva Thomm is a research associate at the Faculty of Education , University of Erfurt, and member of the Institute for Planetary Health Behaviour (IPB) . Her work focuses on educational psychology, science communication, and teachers' trust in research evidence. She serves as an Associate Editor for the German Journal of Educational Psychology (2023-2025) and reviews for 12 journals including Science Communication and PLOS One . Key research areas include: Teachers' source evaluation in belief-evidence conflicts Science communication in educational contexts Digital assessment of professional competencies Epistemic reasoning in teacher training Her 15 most recent publications (2016-2025) demonstrate expertise in: Source credibility assessment Conflict resolution in science communication Medical communication competence testing Belief persistence in educational research Notable award: EARLI Outstanding Publication Award 2021 for work on expert disagreement. Academic affiliations: University of Erfurt (since 2017) Westfälische Wilhelms-Universität Münster (2009-2016) Member of 5 research initiatives including Erfurter Open Science Initiative
Prof. Dr. Alexander Ecker is Professor of Data Science at the Institute of Computer Science, University of Göttingen, and concurrently holds the prestigious Max Planck Fellow position at the Max Planck Institute for Dynamics and Self-Organization. Since 2020 he also serves on the Executive Board of the Campus Institute Data Science in Göttingen. He leads the Neural Data Science research group, comprising 14 PhD students and 2 postdoctoral researchers, focusing on the interface of machine learning and computational neuroscience. His educational background includes a Dr. rer. nat. in Neuroscience (2014) from the Graduate School of Neural and Behavioral Sciences/IMPRS, University of Tübingen, followed by post-doctoral and group-leader positions at the University of Tübingen and the Max Planck Institute for Biological Cybernetics. Research Interests Machine Learning & Deep Learning: developing novel algorithms for representation learning and generative modeling. Computational Neuroscience: large-scale data-driven modeling of visual cortical circuits. Visual Perception: bridging biological vision and computer vision via biologically inspired architectures. His work has produced a steady stream of influential publications (2019-2025) in leading journals such as Nature Communications , Nature , Nature Methods , PLOS Computational Biology , ICLR , NeurIPS , and CVPR . The publications trend toward integrating high-resolution neural recordings with state-of-the-art machine-learning models to uncover principles of sensory processing, neuron-type classification, and behavior. Scientific Awards & Honors Max Planck Fellow, Max Planck Institute for Dynamics and Self-Organization (ongoing) Executive Board Member, Campus Institute Data Science, Göttingen (since 2020) Teaching, Advising & Grants Regularly teaches advanced courses: “Deep Learning for Image Synthesis”, “Current Topics in Deep Learning”, and “Graph Machine Learning”. Supervises 14 current PhD students and 2 postdocs within the Neural Data Science Group. Offers numerous Bachelor’s and Master’s thesis projects, with topics ranging from neuronal morphology clustering to primate vocalization analysis. Leads or co-leads large collaborative consortia with labs in Göttingen, Tübingen, Baylor College of Medicine, and other institutions across the US and Germany. Labs & Teams The Neural Data Science Group operates at the Institute of Computer Science, University of Göttingen, and is tightly integrated with the Max Planck Institute for Dynamics and Self-Organization. The group maintains active collaborations with over a dozen partner laboratories, including groups led by Fabian Sinz, Andreas Tolias, Thomas Euler, Tim Gollisch, and Viola Priesemann, fostering an interdisciplinary environment that spans computer science, physics, biology, and psychology.
