Dr. Moran Lazar is a Senior Lecturer at the Coller School of Management, Tel Aviv University, specializing in the early foundations of entrepreneurship and innovation with emphasis on new venture team formation, ideation processes, and organizational innovation leadership. Her educational background includes: PhD in behavioral science and management from the Technion - Israel Institute of Technology Research fellow at the Robert H. Smith School of Business, University of Maryland Research fellow at INSEAD Dr. Lazar integrates organizational behavior and strategy perspectives to investigate entrepreneurship micro-foundations, utilizing diverse methodologies including entrepreneurship competitions, hackathons, accelerators, educational programs, and crowdfunding platforms. Her work examines how individuals and teams generate, evaluate, and develop entrepreneurial ideas through behavioral lenses. Her publication trends reveal consistent contributions to top management journals focusing on team dynamics in nascent ventures, with recent works analyzing attachment theory in idea evaluation, relationship-business balance in team composition, and comprehensive frameworks for entrepreneurial team formation across multiple contexts including accelerators and international delegations. Dr. Lazar actively consults for global companies and facilitates innovation processes for international delegations from Europe, the United States, East Asia, and the United Arab Emirates, while sharing insights through her TEDx talk on entrepreneurial team formation.
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.
Prof. Dr.-Ing. Rüdiger Daub serves as Professor and Chair of Production Engineering and Energy Storage Systems at the Technical University of Munich (TUM), operating within the Department of Mechanical Engineering. His leadership encompasses research direction, academic supervision, and strategic development of battery production technologies at TUM's Garching campus (Boltzmannstr. 15), with active industry collaborations driving innovation in sustainable manufacturing. Daub's research program pioneers advanced production methodologies for lithium-ion and solid-state batteries, focusing on electrode manufacturing, electrolyte filling, and cell assembly processes. His work investigates critical parameter interdependencies affecting battery safety and performance, developing inline monitoring systems and digital twin technologies for real-time process optimization. Key contributions include moisture control in electrode production, electrochemo-mechanical characterization of solid-state systems, and robotics solutions for deformable object assembly, all integrated with machine learning for quality assurance in industrial settings. Analysis of his 2023-2025 publications reveals a dominant research trajectory toward solving production bottlenecks in next-generation energy storage. The work demonstrates increasing integration of computational modeling with empirical validation, particularly in solid-state battery manufacturing and high-voltage electrolyte systems. A notable trend is the cross-pollination of robotics, computer vision, and uncertainty quantification techniques to address complex assembly challenges and distribution shifts in quality monitoring, reflecting industry's urgent need for adaptable, data-driven production systems. Leading TUM's specialized laboratories for battery cell production, Daub's team maintains comprehensive facilities for electrode calendering, electrolyte filling, and cell assembly with integrated tracking and tracing capabilities. The research infrastructure supports collaborative projects with automotive OEMs and battery manufacturers to develop scalable production processes, emphasizing environmental sustainability through water-based electrode production and footprint optimization. Current initiatives focus on digital factory modeling and prelithiation technologies for next-generation battery systems.
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.
Rainer Watermann is a Full Professor for Empirical Research in Education at the Free University of Berlin since 2011, previously serving as Full Professor for Education and Empirical Research in Schools at Georg-August University of Göttingen (2005-2011). His academic career includes significant research positions at the Max Planck Institute for Human Development in Berlin (1997-2005). Watermann earned his Diploma in Educational Science from the University of Münster (1996), followed by a Dr. phil (2002) and Habilitation (2005), both from Freie Universität Berlin. His educational background established the foundation for his extensive research in educational transitions and disparities. His research focuses on educational transitions, particularly from primary to secondary school and into higher education, examining motivational factors, social background influences, and achievement goal development. Watermann's work consistently addresses how social disparities affect educational opportunities and outcomes, with particular attention to gender differences and longitudinal developmental patterns. His methodological expertise includes latent class analysis, structural equation modeling, and large-scale assessment design. Watermann's publication portfolio reveals consistent research trajectories examining motivational frameworks (particularly expectancy-value theory), educational transitions, social disparities in education, and political socialization. His work spans both theoretical development and practical applications for educational policy and practice, with increasing focus on intervention effectiveness in recent years. As an active member of the academic community, Watermann serves on multiple editorial boards including the Swiss Journal for Educational Sciences and Empirical Educational Science , and regularly reviews for major educational and psychological journals. He has also contributed to significant research centers, including serving as spokesman for the Center for Empirical Research on Teaching and Learning in Schools (ZeUS) at the University of Göttingen (2008-2010). Watermann maintains an active research program with numerous collaborations across Germany and internationally, evidenced by his consistent publication record through 2025. His work bridges educational psychology, sociology of education, and policy-relevant research, maintaining strong connections between theoretical frameworks and practical educational contexts.
Torsten Grust is a Professor of Computer Science at the University of Tübingen, leading the Database Systems research group since 2008. Previously, he held professorships at TU München and TU Clausthal. He earned his M.Sc. (Diploma) and Ph.D. in Computer Science from Universität Konstanz in 1994 and 1999, respectively. His research focuses on database languages, query and programming language technology, and scalable processing of non-relational queries. He bridges database and programming language research, emphasizing mutual benefits between the fields. **Education:** Ph.D. in Computer Science, University of Konstanz (1999) M.Sc. (Diploma), Computer Science, University of Konstanz (1994) Visiting Scientist, IBM Silicon Valley Laboratories (2000) **Research Interests:** Design and optimization of database languages Query compilation and execution engines Integration of functional programming with SQL Query provenance and debugging **Awards and Honors:** ACM SIGMOD Reproducibility Award (2021) University of Tübingen Teaching Award (2021/22) Winner of Dyalog 2019 APL Program Solving Competition Member of the VLDB Endowment Board of Trustees (2022–2027) **Advising & Grants:** Guided numerous students, including alumni such as Alexander Ulrich, Benjamin Dietrich, and Christian Duta Recipient of grants supporting research in query compilation, provenance analysis, and database language design **Labs & Teams:** Leads the Database Systems research group at University of Tübingen Collaborates with the National Institute of Informatics (Tokyo) on query and programming languages
Cornelia Betsch serves as Director of the Institute for Planetary Health Behaviour (IPB) at the University of Erfurt, where she holds a professorship in Health Communication within the Faculty of Philosophy. She is responsible for the Master's program in Health Communication through the Department of Media and Communication Studies and leads the Health Communication Working Group at the Bernhard Nocht Institute for Tropical Medicine in Hamburg as an external position. Her interdisciplinary work bridges behavioral science, psychology, and public health to address critical global challenges. Habilitation (2006), University of Erfurt: 'The role of risk perception and risk communication in prevention decisions – the example of vaccination decisions' PhD (Dr. phil., summa cum laude, 2006), University of Heidelberg: 'Preference for intuition and deliberation– measurement and consequences of affect- and cognition based decision making' Diplom in Psychology (2002), University of Heidelberg Betsch's research focuses on understanding health and planetary health behaviors, particularly examining vaccination behavior, prudent antibiotic use, and climate-friendly actions. Her work extends globally, with investigations in various African countries on vaccination and antibiotic practices. She pioneered the influential COVID-19 Snapshot Monitoring (COSMO) and subsequently developed the Planetary Health Action Survey (PACE), large-scale studies that regularly track public knowledge, risk perception, protective behaviors, and trust during crises. Her research emphasizes applying behavioral and cultural insights to design effective policy frameworks and explanatory communication that promotes positive health behaviors. The 15 most recent articles showcase Betsch's research evolution toward integrating behavioral science with planetary health, climate action, and vaccine communication. Her work increasingly examines the psychological foundations of climate behavior while maintaining her established expertise in vaccine hesitancy and antimicrobial resistance. Recent publications demonstrate methodological diversity, including systematic reviews, meta-analyses, survey experiments, and large-scale monitoring datasets that bridge academic research with practical policy applications. German Psychology Prize (2021) Thuringian Research Prize (2022) Betsch has secured research funding from independent research organizations, ministries, and foundations to support her work on health communication and planetary health behavior. She serves as a scientific advisor to multiple organizations including the WHO Technical Advisory Group on Behavioral and Cultural Insights, Science Media Center Germany, and Museum für Naturkunde Berlin. At the Bernhard Nocht Institute for Tropical Medicine, she established the WHO Collaborating Center for Behavioral Research in Global Health, demonstrating her commitment to translating research into global health practice. Her engagement extends to policy advising, having served on the Corona Expert Council of the Federal Chancellery during the pandemic. As Director of the Institute for Planetary Health Behaviour, Betsch leads an interdisciplinary team applying social and behavioral science perspectives to planetary health and the climate crisis. The institute serves as a hub for research, education, and science communication at the intersection of human health and environmental sustainability. Her work through the IPB emphasizes Open Science principles and aims to understand the comprehensive factors influencing climate-friendly behavior to identify effective intervention points for policy development.
Christopher Deninger is a distinguished Professor in the Mathematical Institute at the University of Münster, Germany, where he leads research in Arithmetic Geometry and Representation Theory. His office is located in Room 413 of the Einsteinstr. 62 building, and he maintains active teaching responsibilities including courses in Representation Theory of Finite Groups, Linear Algebra, and specialized topics like Adic Spaces. Deninger's research spans multiple interconnected domains of modern mathematics, with a consistent focus on the deep connections between number theory and geometry. His work has evolved from classical arithmetic geometry to incorporate increasingly sophisticated connections with p-adic analysis, dynamical systems, and more recently proalgebraic fundamental groups. A unifying theme throughout his career has been exploring analogies between different mathematical structures, particularly those connecting analytic number theory with dynamical systems on foliated spaces. His recent publications reveal a continued expansion of his research program into new territories while maintaining connections to his foundational work. The most recent papers show increasing integration of algebraic topology concepts with arithmetic geometry, particularly through proalgebraic fundamental groups and their applications. The consistent thread throughout his decades of publications is the search for deeper structural connections between seemingly disparate areas of mathematics, particularly those bridging analysis, geometry and number theory. Professor Deninger has mentored an extensive number of doctoral students and postdoctoral researchers, as evidenced by the comprehensive list of former members in his working group. His collaborations span the international mathematical community, with numerous joint publications with leading mathematicians across Europe and beyond. While specific grant information isn't detailed in the available materials, his sustained publication record across decades suggests consistent research support for his mathematical investigations. The Mathematical Institute at Münster provides the institutional home for Deninger's research activities, where he maintains an active working group focused on arithmetic geometry and related fields. His office environment includes support staff and colleagues working in closely related mathematical domains, creating a vibrant research community centered around advanced topics in pure mathematics.
Fatma Deniz is a Full Professor (W3) of Computer Science at Technische Universität Berlin, supported by the Berlin Equal Opportunities Program. She leads the Chair of Language and Communication in Biological and Artificial Systems, and is a member of the Berlin Bernstein Center for Computational Neuroscience. Her roles include membership in TU Berlin's Executive Board and the Berlin University Alliance Steering Committee. She holds a Ph.D. (Dr. rer. nat.) from TU Berlin and a Diploma in Computer Science from Technische Universität München, with research training at Caltech and postdoctoral work at UC Berkeley. Her research focuses on understanding neural mechanisms of language processing, integrating computational neuroscience, cognitive science, and artificial intelligence. Key areas include semantic representation dynamics, cross-modal neural alignment, and language learning in bilingual contexts. She has pioneered studies showing the brain's invariant semantic processing across reading and listening modalities. Her grants include an ERC Starting Grant (2023-2028) for studying language learning shifts and a NSF-BMBF CRCNS grant on bilingual representations. She co-edited The Practice of Reproducible Research: Case Studies in Data Science (UC Press, 2017) and contributed to foundational work on reproducible data science methodologies. She has advised projects in neuroimaging, AI ethics, and computational linguistics, and collaborates with institutions like UCSF and the German Academic Exchange Service. Her lab explores neural correlates of language through fMRI, MEG, and machine learning techniques.
Prof. Dr. Lena Wessel is a Mathematics Education faculty member at the Department of Mathematics Didactics, Faculty of Electrical Engineering, Computer Science and Mathematics, University of Paderborn. She leads teacher training programs and participates in university governance as elected Faculty Council member. Research Focus: Her work centers on comprehension-oriented mathematics instruction at secondary/vocational levels, emphasizing language development, continuity in curriculum design (spiral principle), and digital mathematics tools. As DZLM network partner, she develops professional development programs for secondary educators. LiaNMU project (scalar products, plane reflections) VioLa project (digital discussion formats) LLV.HD project (cross-university learning networks) Key Contributions: She has coordinated major projects like MESUT (language-supported fraction understanding) and LaMaVoC (language in vocational mathematics). Her 2024 publications analyze language-integrated pedagogy and algebraic concept unification in teacher training.
Dr. Shushanik Margaryan is a Research Fellow at the University of Potsdam's Department of Economics, affiliated with the Berlin School of Economics and IZA. She holds a Ph.D. from the University of Hamburg and specializes in health, education, and labour economics with a focus on applied microeconometrics. Her work addresses societal challenges such as climate policy co-benefits, educational interventions, and healthcare disparities. Education: Ph.D. in Economics, Universität Hamburg (2016-2021) M.Sc. in Economics, Universität Hamburg (2014-2016) B.A. in Labour Economics, Armenian State University of Economics (2009-2013) Research Interests: Her research spans climate policy impacts, educational equity, and labour market dynamics. Notable projects include evaluating low-emission zones' health benefits and the effects of randomized educational interventions on disadvantaged children. Key Contributions: Recent work examines spillover effects of war on adolescents and replicates studies on long-term vaccination impacts. She co-leads a DFG-funded project on labour market transformations. Awards: HCHE Young Researcher Award (2021) Joachim Herz Fellowship (2024-2026) Teaching & Service: Teaches graduate and undergraduate courses on labour/education economics. Organizes seminars like the Potsdam Research Seminar in Economics and serves on hiring committees.
Ryomei Iwasa serves as Associate Professor in the Department of Mathematical Sciences at the University of Copenhagen, where his research bridges algebraic geometry and algebraic topology through advanced investigations in motivic homotopy theory and cohomology frameworks. His core research spans Algebraic Geometry, Algebraic Topology, Motivic Homotopy Theory, and K-Theory, with specialized focus on motivic spectra, algebraic cobordism, and the structural relationships between cohomology theories and moduli spaces. Recent publications demonstrate deep engagement with foundational aspects of Milnor excision, cdh descent, and modulus conditions in cycle theory. Analysis of his publication trajectory reveals a concentrated effort toward geometrization of cohomology theories, particularly evident in his 2025 Journal of the American Mathematical Society paper on Conner-Floyd isomorphisms and ongoing seminar work. Collaborations with leading mathematicians including Toni Annala, Marc Hoyois, and Wataru Kai underscore his position at the forefront of these mathematical frontiers. Scientific recognition includes: ERC MOSHOT grant He actively directs a weekly seminar on geometrization of cohomology theories, structuring comprehensive explorations from filtered modules to de Rham cohomology and prismatization. The seminar program—featuring presentations by Qingyuan Bai, Adrien Morin, and Florian Riedel—demonstrates his commitment to advancing collective understanding and mentoring emerging researchers in specialized mathematical domains.
Dr. Tyll Robin Lemke is a researcher at Saarland University in the Department of Modern German Linguistics (Neuere deutsche Sprachwissenschaft). He serves as a scientific staff member in Project B3 of the Collaborative Research Center SFB 1102. His academic focus includes experimental linguistics, syntax, and psycholinguistics, with specialized expertise in ellipsis phenomena and fragment analysis. Lemke's research explores the cognitive underpinnings of language production and comprehension, particularly investigating how predictability, context, and information theory shape linguistic structures. His work employs diverse methodologies including corpus analysis, psycholinguistic experiments, computational modeling, and gamified experimental paradigms to examine ellipsis, fragments, and syntactic phenomena in German. Analysis of Lemke's recent publications reveals consistent themes: the role of predictability in language production, constraints on ellipsis resolution, information-theoretic approaches to language efficiency, and experimental validation of syntactic theories. His research bridges theoretical linguistics with cognitive science through innovative experimental designs. In the upcoming 2025/26 winter semester, Lemke is teaching courses on Experimental Linguistics and Ellipsis in Theory and Experiment. He maintains an active research program within the SFB 1102 collaborative framework and regularly presents at international linguistics conferences.
Dr. Yu Huang is an Assistant Professor in the Department of Computer Science at Vanderbilt University's School of Engineering, with a secondary appointment in the Department of Teaching and Learning at the Peabody School of Education. She is affiliated with the Institute for Software Integrated Systems, the Frist Center for Autism and Innovation, the Vanderbilt Lab for Immersive AI Translation (VALIANT), and the Vanderbilt LIVE Learning Innovation Incubator. Her academic journey began with a BS in Aerospace Engineering from Harbin Institute of Technology in China (2011), followed by an MS in Computer Engineering from the University of Virginia (2015), and culminated with a PhD in Computer Science and Engineering from the University of Michigan in 2021 under Professor Westley Weimer. Dr. Huang's research bridges human cognition and machine intelligence to enhance software development. Her work spans software, hardware, AI, medical imaging (fMRI/fNIRS), eye tracking, and mobile sensing through collaborations with Security, Education, Psychology, and Neuroscience researchers. She leads the MIND Lab (Mixed INtelligence Development for programming lab), investigating programming expertise formation, code comprehension processes, cognitive error patterns, and diversity in programming communities. Her innovative approach combines empirical human studies with AI model development to create more effective programming tools. Her recent publications reveal a growing emphasis on leveraging human attention data to improve code language models, analyzing cognitive biases in security contexts, and examining social factors in technical communication. The research shows strong interdisciplinary connections between neuroscience, psychology, and software engineering, with increasing applications of LLMs in developer tooling. Dr. Huang's work consistently demonstrates how understanding human cognition can inform better AI systems for programming tasks. Dr. Huang has received numerous prestigious recognitions including the 2025 ICPC Vaclav Rajlich Early Career Achievement Award and three ACM SIGSOFT Distinguished Paper Awards (ICSE 2019, FSE 2023, ICSE 2024). Her lab has earned the Best Presentation Award at GI2024, while her students have received the Richard Bennett/Dorothy Danforth Compton Prize scholarship and the C. F. Chen Best Paper award. She actively mentors a diverse team of graduate students (Yifan Zhang, Zach Karas, Zihan Fang, Yueke Zhang, Jiahao Zhang) and undergraduate researchers, with many former students advancing to top institutions (Stanford, Harvard, Duke, UC Berkeley) and organizations (NASA JPL). Her research is supported by a 4-year NSF grant, GitHub Tech for Social Good funding, and the Provost's Faculty Immersion Vanderbilt Grant, enabling comprehensive studies of human-AI collaboration in software engineering. The MIND Lab maintains a strong collaborative culture, frequently working with Professor Kevin Leach's research group and organizing retreats to locations like Radnor State Park and the Great Smoky Mountains. This environment fosters innovation at the intersection of human cognition and software engineering while supporting the professional development of emerging researchers in the field.
