Prof. Dr. Angela Kaindl is an active faculty member specializing in pediatric neurology and neurodevelopmental research, with a focus on epilepsy mechanisms, genetic disorders, and cognitive development. Her work bridges clinical neurology and basic neuroscience, particularly in understanding memory consolidation across developmental stages. Her research examines critical areas including: Epilepsy pathophysiology and precision medicine approaches (e.g., TRPM3-linked encephalopathy) Neurodevelopmental outcomes in congenital conditions (corpus callosum agenesis, microcephaly) Memory formation dynamics in typical/atypical development (preterm/term infants vs. adults) Genetic basis of brain malformations (MN1 truncation, DYNC1H1 disorders) Analysis of her recent publications reveals strong thematic focus on: pediatric epilepsy interventions, neuroanatomical correlates of memory, genetic determinants of brain development, and neurocognitive outcomes in congenital disorders. Her work employs diverse methodologies including neuroimaging, molecular genetics, and systematic clinical evaluations. No awards, students, or explicit affiliation details were documented in the source materials. Collaborative networks include multidisciplinary teams across neurology, genetics, and psychology research groups.
Dr. Rüdiger Berger serves as Group Leader of the central Scanning Probe Microscopy (SPM) facility at the Max Planck Institute for Polymer Research in Mainz, Germany, operating ten microscopes for 30+ researchers since October 2002. Educational background: Physics degree from Friedrich-Alexander University Erlangen-Nuremberg (1994), specializing in high-Tc superconductors via SPM Doctorate and postdoc at IBM Research Laboratory Zurich (micromechanical sensors with Ch. Gerber/J. Gimzewski) Research engineer at IBM Deutschland Speichersysteme GmbH Mainz (1998-2002), focusing on test system automation and magnetic materials His research investigates nanoscale electrical surface properties with direct applications in solar cells and batteries. Collaborating with the Butt group, he pioneers droplet friction analysis methods and studies interfacial droplet behavior at defects. This work bridges surface science, nanoelectronics, and energy materials through advanced microscopy techniques. Recent publications (2023-2024) demonstrate convergence of operando microscopy, machine learning, and interfacial physics—particularly in droplet dynamics and solid-state battery systems. Key trends include computational analysis of sliding drops, lithium dendrite evolution at grain boundaries, and nanoscale friction quantification, spanning electrochemistry, fluid dynamics, and materials characterization. No scientific awards were documented in the source material. No student advising relationships or research grants were specified in the provided information. Berger manages the SPM facility as a collaborative hub where 30+ scientists utilize ten manufacturer-diverse microscopes for surface/interface characterization. The laboratory enables nanoscale electrical and mechanical property analysis across polymer research domains, emphasizing real-time observation of energy materials and fluid-solid interactions.
Max Planck Institute for Security and PrivacyGermany
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.
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.
Nadia Zaboura is a communication scientist and linguist serving as a Guest Researcher at Freie Universität Berlin's Institute for Media and Communication Studies, Department of International Communication. With over 14 years of professional experience as a consultant, she bridges academic research with practical media consultancy for organizations across media, government, and civil society sectors. Her educational background includes an M.A. summa cum laude in Communication Science and Linguistics/German Studies from the University of Essen (2007), with a thesis examining mirror neurons and communicative intersubjectivity. Her academic journey reflects a consistent interdisciplinary approach connecting neuroscience, communication theory, and media practice. Zaboura's research interests center on critical media analysis, particularly German media coverage of the Middle East, right-wing extremism, and authoritarianism, and their implications for social cohesion and democracy. She investigates how digital communication can serve as an academic third mission to reach diverse audiences, with special attention to diversity in media representation and the challenges facing public service broadcasting in turbulent times. Her scholarly output reveals a clear evolution from foundational neuroscience-communication research (2006-2009) toward increasingly applied media criticism and journalism studies. Recent work demonstrates growing concern with media trust, democratic integrity, and the specific challenges of Middle East coverage in German media, alongside exploration of emerging technologies like AI in journalism. Bert-Donnepp-Preis 2024 - German Award for Media Critique for her podcast 'quoted' Grimme Online Award Audience Prize German Radio Award recognition for jury leadership (2019-2022) As a consultant, Zaboura provides scientifically informed analysis to media organizations, foundations, and government bodies. Her advisory work spans media criticism, Middle East coverage expertise, and communication strategy for sensitive topics. She serves on influential committees including the European Commission as an evaluator for Horizon Europe, the Board of Trustees of the Grimme Research College, and as a long-standing juror for the German Radio Award. Her professional activities consistently connect academic rigor with real-world media challenges, particularly regarding democratic discourse and representation.
Penelope Tilsley serves as a Postdoctoral Fellow at the Center for Environmental Neuroscience, Max Planck Institute for Human Development in Berlin. Her research integrates neural science with environmental contexts to investigate human cognitive and behavioral responses to ecological stimuli. Her primary focus lies in Environmental Neuroscience , examining how natural and built environments shape brain function through methodologies spanning neuroimaging , cognitive testing , and ecological monitoring . This interdisciplinary work bridges environmental psychology and systems neuroscience to address urgent questions about urbanization, climate change, and neural adaptation. As a core member of the Environmental Neuroscience Research Team, Dr. Tilsley contributes to collaborative projects analyzing neural responses across diverse environmental settings. Her current work emphasizes translational applications for public health and urban planning, leveraging the Institute's advanced neuroscientific infrastructure to generate policy-relevant insights.
Max Planck Institute for Security and PrivacyGermany
Andrew Begel is an Associate Professor in the Software and Societal Systems Department at Carnegie Mellon University's School of Computer Science. Previously, he was a Principal Researcher at Microsoft Research from 2006 to 2022. He received his Ph.D. in Computer Science from the University of California at Berkeley and holds a Master of Engineering from MIT. Dr. Begel is internationally recognized for his pioneering research on cooperative and human aspects of software engineering, combining empirical studies of professional software engineers with organizational behavior. His work focuses on accessibility, neurodiversity, and human-computer interaction, with particular emphasis on creating more inclusive technology workplaces. He was the first to study emotions in software engineering and conducted groundbreaking research on autistic software developers, identifying their unique strengths and challenges. His research portfolio shows a clear trajectory toward understanding human factors in software development, with increasing focus on neurodiversity and accessibility. Early work examined code comprehension through eye tracking and fMRI studies, while recent publications focus on creating inclusive environments for autistic software engineers and developing tools that support mixed-ability collaboration. His work spans empirical software engineering, human-computer interaction, and accessibility research, often bridging these domains to address real-world challenges in software development environments. Best Paper Award — SIGCSE (2021) ACM Distinguished Member (2019) Best Paper Honorable Mention Award — CSCW (2019) Best Paper Award — ICSE, Software Engineering In Practice (2019) Most Influential Paper Award (10 Years) — ICER (2019) Best Paper Honorable Mention Award — CHI (2017) Dr. Begel has been deeply involved in academic service, organizing and serving on program committees for top software engineering conferences. He has run FSE and ICSE's ACM Student Research Competitions and ICSME's Doctoral Symposium. He created the Autism at Work Research Workshop series, bringing together researchers, practitioners, and autism self-advocates to help autistic engineers find and keep jobs. As a member of Microsoft's AI Ethics Board, he contributed to disseminating best practices for responsible AI engineering. His teaching includes courses at the University of Washington's iSchool and coding camps for autistic youth. Dr. Begel leads the Autism at Work Research Workshop series and has established himself as a prominent figure in creating more inclusive environments for neurodiverse software engineers. His work bridges academic research with practical applications in industry settings, particularly through his collaborations with Microsoft and other technology companies.
Dr. Chris John Potter is a Professor of Neuroscience at Johns Hopkins University School of Medicine, where he has been faculty since 2010. His research program investigates neural mechanisms of olfaction in disease-transmitting insects, particularly malaria mosquitoes. Dr. Potter leads the Christopher Potter Lab, developing genetic tools like the Q-system to study sensory processing and behavior. Education: Ph.D. in Genetics, Yale University (2002) B.A. in Molecular and Cell Biology, University of California, Berkeley (1996) Postdoctoral Fellowship in Neuroscience, Stanford University (2010) Research focuses on: Neural circuit basis of olfactory behaviors in Drosophila and mosquitoes Development of genetic tools for neural manipulation Chemosensory mechanisms guiding mosquito host-seeking and oviposition Translational applications for vector-borne disease control Recent publications emphasize mosquito neurobiology, genetic tool development, and olfactory coding mechanisms. His work consistently integrates molecular genetics with systems neuroscience approaches. Honors and Awards: NIH R21 Grants (NIAID 2018, NINDS 2015) Johns Hopkins Discovery Award (2017) Malaria Research Institute Pilot Award (2015) Whitehall Foundation Grant (2011) Damon Runyon Fellowship (2003) The Potter Lab ( potterlab.johnshopkins.edu ) develops transgenic approaches to study sensory processing. Current projects investigate mosquito olfactory circuits using calcium imaging, single-cell sequencing, and behavioral assays. Dr. Potter collaborates with public health researchers to translate basic discoveries into vector control strategies.
Professor Dirk J. Lehmann is a Professor of Data Science in IoT at Ostfalia University of Applied Sciences, Faculty of Computer Science, where he has been employed since May 2022. He holds significant leadership roles including Deputy Head of the Institute for Information Engineering (since 2024), Research Officer of the Faculty of Computer Science (since 2023), and membership in multiple committees including the Admissions Committee for Digital Technologies and the Digital Technologies Examination Board. Professor Lehmann's extensive academic journey includes: Part-time professorship in Data Science in IoT at Ostfalia University (2020-2022) Senior Specialist for Digitalization, AI, and Visual Analysis at IAV GmbH (2018-2023) Assistant Professor of Visual Data Analysis at Nazarbayev University, Kazakhstan (2017) Visiting professorships at TU Graz, Austria and Universidad Rey Juan Carlos, Spain (2016-2017) Researcher at Otto-von-Guericke University Magdeburg (2009-2017) His research expertise centers on Visual Analytics and Data Science, with particular emphasis on high-dimensional data visualization, categorical data analysis, and IoT applications. Professor Lehmann leads the Data Science in IoT working group, conducting research across three main areas: visual data analysis, distributed data analysis using AI methods, and applied data analysis in geology, climate data, medicine, and industrial processes. His methodological contributions include innovative visualization techniques for complex datasets across multiple domains. Analysis of Professor Lehmann's 15 most recent publications (2017-2025) reveals a consistent focus on advancing visualization techniques for complex data analysis. His work spans categorical data visualization (CatNetVis), biological data analysis (D. Melanogaster research), optimization of star coordinate systems, and interactive exploration methods for large datasets. These publications appear in top venues including IEEE Transactions on Visualization and Computer Graphics and EuroVis, demonstrating both theoretical rigor and practical application across diverse domains from healthcare to environmental science. As an educator, Professor Lehmann teaches a comprehensive range of courses from foundational mathematics to advanced machine learning and visualization techniques. He actively supervises student projects and theses, emphasizing clear project definitions with measurable acceptance criteria. His international collaborations span institutions in Israel, Saudi Arabia, China, Austria, and Spain, reflecting a global research perspective that bridges academic theory with industry applications, particularly through his previous role at IAV GmbH, a Volkswagen subsidiary.
Helmholtz Association of German Research CentersGermany
Prof. Dr. Ozgun Gokce is a Group Leader at the German Center for Neurodegenerative Diseases (DZNE) in Bonn. His research program integrates advanced genomic technologies to investigate neuroinflammatory processes and degeneration mechanisms. Primary focus areas include: Single-cell and spatial genomics of neural-immune interactions White matter aging and remyelination strategies Neurodegenerative disease mechanisms (Alzheimer's, ALS) Brain injury responses and repair pathways Recent work demonstrates strong emphasis on omics approaches, with 2022-2025 publications predominantly featuring transcriptomics, neuroimmunology, and computational integration of multi-modal datasets. Studies frequently examine microglia-T cell crosstalk, lipid metabolism in neurodegeneration, and innate immune training paradigms. Laboratory resources include access to DZNE's core facilities for genomics, imaging, and bioinformatics. Current work involves several collaborative projects investigating neuroimmune axis dysfunction across neurological conditions.
