جست‌وجوی استاد و پژوهشگر

• Media Aesthetics
• Media Culture
• Game Studies
• +۵ مورد دیگر

Dr. Rolf F. Nohr serves as Professor of Media Aesthetics/Media Culture at Braunschweig University of Art (HBK Braunschweig) and holds an External Affiliate position at the University of Arizona's College of Humanities. His research centers on media evidence methodologies, game studies, and instant images, with particular emphasis on simulation games as cultural techniques that shape rationality and decision-making processes. Nohr's scholarly work investigates the interplay between media theory, cultural techniques, and ludic systems. He examines how games function as evidentiary media through historical analysis of business simulations (1955-1975), military war games, and contemporary digital environments. His research reveals how strategic play constructs rational subject positions while interrogating the materiality of game interfaces and the epistemological status of media images. Recent publications demonstrate a cohesive trajectory analyzing games as media artifacts that produce knowledge through procedural logic. His work bridges historical media archaeology with contemporary game design, focusing on genre theory, player agency, and the pedagogical dimensions of serious games. Key themes include the transformation of work logic into play systems, feedback mechanisms in teaching machines, and the cultural techniques embedded in simulation interfaces. Scientific recognition includes: LehrLeo TU Braunschweig Award for Best Lecture in BA Studies (2013) German Study Prize, 3rd Place by Körber Foundation (1998) Nohr has secured major research funding from the German Research Foundation (DFG), Federal Ministry of Education and Research (BMBF), and NORD/LB Foundation for projects including 'Strategie Spielen' (2006-2011), 'Kulturtechnik Unternehmensplanspiel' (2012-2019), and 'PlanA – Planspiel Arbeitswelten' (2018). As Regional Director of the Learning Games Initiative Research Archive since 2015, he leads game preservation efforts while collaborating across engineering, humanities, and social science disciplines. He co-founded the Games Research Group within the German Society for Media Studies (GfM) and serves as editor for the 'Medien'Welten' and 'Braunschweiger Schriften zur Medienkultur' book series. His interdisciplinary collaborations span the TU Braunschweig's engineering departments, University of Arizona humanities scholars, and international game researchers through the Learning Games Initiative network.

Patrick Dinklageمشاهده پروفایل

پژوهشگر

• Algorithm Engineering
• Data Structures
• Text Compression
• +۳ مورد دیگر

Patrick Dinklage is a researcher at the Department of Computer Science, Faculty of Computer Science, Technical University of Dortmund. His work focuses on algorithm engineering, data structures, and text compression, particularly in external memory and distributed settings. Research Interests: Algorithm engineering, wavelet tree construction, lossless compression, and external memory data structures. Publications: He has contributed to competitive conferences like ESA, SEA, and ALENEX, with a focus on space-efficient algorithms and compression frameworks. Software: Developed tudocomp , a lossless compression framework. Teaching: Involved in lectures and seminars like Fachprojekt Digital Entertainment Technologies and PG 628: PlaDs. Workshops: Organized BwInf-Workshops at Dortmund (2018-2020).

• Neuroscience
• Computational Neuroscience
• Cognitive Science
• +۳ مورد دیگر

Andreea Lazar is a Researcher at the Singer Lab, located at ESI-Frankfurt in Germany. Her work focuses on understanding how cortical networks process external stimuli and internally generated activity patterns, particularly exploring spontaneous activity's role in prediction, memory, and statistical learning. She employs both computational modeling and electrophysiological data from in vivo studies. Her research interests span computational neuroscience, systems neuroscience, and learning mechanisms. Key topics include neural network dynamics, visual cortex processing, and the interplay between spontaneous activity and sensory-driven responses. Publications highlight contributions to understanding neural variability, predictive coding, and Bayesian learning in recurrent networks. While no formal awards are listed, her work bridges theoretical models and experimental findings in neural systems. Lazar collaborates within the Singer Lab, led by Prof. Wolf Singer, alongside researchers such as Igor Dubinin and Katharine Shapcott. The lab investigates fundamental principles of brain function, with a focus on cortical integration and sensory processing.

• Multimodal Interaction
• Artificial Intelligence
• Human-Computer Interaction
• +۳ مورد دیگر

Hung-Hsuan Huang is an academic researcher focused on multimodal interaction, embodied conversational agents, and educational technology. His work spans topics such as virtual agent behavior, gamified learning systems, and nonverbal communication analysis. Collaborating frequently with institutions like Osaka University, he has published extensively in venues including HCI, ICMI, and IVA conferences. His research often integrates machine learning techniques with human-computer interaction challenges, particularly in educational and collaborative environments. Key research areas include: (1) Designing virtual agents for tutoring and teacher training, (2) Multimodal assessment systems using speech and body language analysis, (3) Gamification mechanisms for knowledge refinement and skill evaluation, and (4) Cross-cultural interaction frameworks for virtual guides. Recent work emphasizes applications in language proficiency assessment and teacher training simulations. Notable contributions include developing frameworks for integrating embodied conversational agents, simulating group discussion dynamics, and creating virtual classroom environments for skill evaluation. His methodologies often combine deep learning with behavioral analysis to address challenges in human-agent collaboration.

Frank Hopfgartnerمشاهده پروفایل

استاد

• Information Retrieval
• Gamification in Education
• Machine Learning
• +۵ مورد دیگر

Prof. Frank Hopfgartner is a Professor at the University of Koblenz's Institute of Computer Science, Department 4. His research focuses on information retrieval, gamification in education, machine learning ethics, digital preservation, and user modeling. He leads projects involving AI-driven healthcare triage systems, bias-aware search engines, and participatory web archiving initiatives. His academic work bridges technical innovation with societal impact, addressing challenges in pandemic response systems, generational engagement in education, and ethical AI development. Key areas of contribution include lifelog data retrieval, knowledge graph alignment, and misinformation analysis during crises. Notable ongoing projects include: FAIR clustering algorithms for ethical machine learning Privacy-preserving email archive exploration Design of gamified IR systems for Gen Z learners He advises external doctoral student Dr. Matthias Lohr and collaborates extensively on international evaluation frameworks for information systems (e.g., NTCIR, CLEF). His research group maintains strong ties with institutions like National Museums Liverpool and NHS data networks.

Michael Smolkaمشاهده پروفایل

استاد

• Neuro-cognitive mechanisms of addiction
• Decision making
• Instrumental and Pavlovian learning
• +۴ مورد دیگر

Prof. Michael Smolka holds dual appointments as Full Professor (W2) of Systems Neuroscience at TU Dresden Medical Faculty and Co-opted Professor at TU Dresden Faculty of Psychology. He leads the Section of Systems Neuroscience within the Department of Psychiatry and Psychotherapy. His research focuses on neuro-cognitive mechanisms underlying addiction, decision-making processes, and brain imaging methodologies. Key contributions include studying nicotine dependence, alcohol-induced neural impairments, and adolescent neurodevelopment. Education: Dr. med. from Freie Universität Berlin (1996), Habilitation in Psychiatry from Universität Heidelberg (2006). Professional milestones include leadership roles in Collaborative Research Centers SFB 940 and TRR 265 investigating volition control and addiction mechanisms. Awards include the W.E.-Heraeus Foundation thesis award and Human Brain Mapping Editor's Choice Award. Research interests span computational models of addiction, reward processing networks, and longitudinal cohort studies. His 320+ publications (h-index 54) explore topics like alcohol use disorder neurobiology and adolescent brain maturation. Current projects include developing machine learning tools for psychiatric nosology and real-time addiction interventions. Editorial roles: Addiction Biology (since 2008), Sucht (since 2008) Key grants: Spokesperson roles in 2 major CRCs (SFB 940/265) Labs: Active in Dresden's Systems Neuroscience lab and transdisciplinary addiction research consortia

• Neural Networks
• Information Processing
• Statistical Physics
• +۱۳ مورد دیگر

Viola Priesemann is a Professor of Physics at the University of Göttingen and heads the Max Planck Research Group on the Theory of Neural Systems at the Max Planck Institute for Dynamics and Self-Organization in Göttingen. She also holds affiliations with the Cluster of Excellence 'Multiscale Bioimaging', the Campus Institute for Data Science, and the Max Planck-University of Toronto Centre for Neural Science and Technology. Her research focuses on understanding the fundamental principles of collective information processing in both neural and social networks. She employs approaches from statistical physics and information theory to investigate self-organization and learning processes in living networks. Her work spans several interconnected areas: neural criticality and subsampling effects in network analysis, information processing in neural circuits, and the spread of information (and misinformation) in social networks. During the COVID-19 pandemic, she applied her expertise in spreading dynamics to study viral transmission and the effectiveness of interventions, becoming a member of the German government's expert panel on the pandemic. Her recent publications reveal a strong focus on understanding how neural networks maintain optimal information processing through controlled criticality, how subsampling affects our ability to infer network properties, and the parallels between information spread in neural and social networks. Her work bridges theoretical physics, computational neuroscience, and epidemiology, demonstrating how principles from statistical physics can illuminate collective phenomena across vastly different scales. Medal for Scientific Journalism of the German Physical Society (DPG) Communitas Award of the Max Planck Society Member of the Junge Akademie Dannie-Heineman Award of the Academy of Science and Humanities, Göttingen Science award of Lower-Saxony - Wissenschaftspreis Niedersachsen Young Scientist Award for Socio- and Econophysics from the German Physical Society Professor Priesemann actively mentors numerous PhD students and postdocs in her research group, fostering interdisciplinary collaboration between physics, neuroscience, and data science. Her lab investigates topics ranging from neural plasticity and learning to epidemic modeling and information spread in social networks. She has secured significant research funding, including a German-Israel Foundation Young Investigator Grant and projects within the Cluster of Excellence 'Multiscale Bioimaging' and the Max Planck-University of Toronto Centre. Her research group maintains strong connections with experimentalists and theorists across multiple institutions, creating a vibrant environment for studying the principles of living adaptive networks. She has initiated several interdisciplinary research projects, including a major initiative on curiosity and hierarchical information processing across species.

• Static Analysis
• Abstract Interpretation
• Fixpoint Algorithms
• +۱ مورد دیگر

Sarah Tilscher, M.Sc., is a researcher at the Chair for Languages and Structures in Computer Science at the Technical University of Munich (TUM). She contributes to teaching tutorials for courses including Advanced Concepts of Programming Languages and Compiler Construction , and has supervised seminars on static analysis and programming paradigms. Her research focuses on: Incremental and interactive static analysis using abstract interpretation Verification of fixpoint algorithms in Isabelle theorem prover Development of the Goblint static analyzer for concurrent C programs Formal methods for program correctness and verification Her publications (11 recent works) predominantly explore static analysis techniques, abstract interpretation frameworks, and verification tools. Key themes include top-down solvers, weak relational domains, parser generators, correctness witnesses, and concurrency modeling, primarily applied to programming languages and compiler design. She actively supervises student theses on topics including incremental static analysis, visualization of analysis results, and verification of fixpoint algorithms. Current opportunities include master's projects on verified top-down solvers and bachelor's projects on solver code generation. As a core member of the Goblint project team, she develops static analysis tools for memory safety and termination verification, collaborating with TUM researchers and external partners.

• Database Systems
• Embedded Analytics
• Query Processing
• +۵ مورد دیگر

Hannes Mühleisen is a prominent database systems researcher affiliated with Centrum Wiskunde & Informatica (CWI) in Amsterdam, with a PhD from Free University of Berlin (2012) in distributed query processing. His research spans database architecture, embedded analytics, and query optimization, with significant contributions to the DuckDB open-source analytical database project. His primary research interests focus on embedded analytical database systems , query processing optimization , columnar storage , and database reliability . Mühleisen's work bridges theoretical database concepts with practical implementations, particularly in the context of analytical workloads. His research demonstrates how database systems can be optimized for modern hardware architectures including WebAssembly and tensor processing units. Mühleisen has published extensively in top database venues including VLDB, SIGMOD, ICDE, and SSDBM, with a consistent publication record from 2009 through 2025. His recent work shows increasing focus on robustness, reliability, and practical deployment of database technology in diverse environments from the web browser to scientific computing contexts. His collaborations reveal strong ties to the CWI database research group, with frequent co-authorship with Peter Boncz, Martin Kersten, and Mark Raasveldt. Mühleisen's work on DuckDB has made significant impact in the data science community as an embedded analytical database solution.

• Cybernetics
• Computational Architecture
• Digital Twins
• +۷ مورد دیگر

Liss C. Werner is a computational design researcher at Dessau International Graduate School of Architecture , focusing on the intersection of cybernetics, architecture, and digital systems. Her work explores bio-computational reactors, digital twins for buildings, and slime mold-based architectural models. She contributes to urban planning through GIS-based tools and investigates historical cybernetic principles in design. Key Research Areas: Cybernetics, computational architecture, bio-digital integration, digital twins, and urban systems. Collaborations: Projects with scholars in Germany, Austria, and Sweden, including studies on microbial fuel cells and particle physics applications. Theoretical Contributions: Extended Gordon Pask's Conversation Theory into architectural design, proposed 'sixth ecology' frameworks, and critiqued bio-digital fantasies in design. Tools & Methods: Uses Python OpenCV, Grasshopper/Rhinoceros, Arduino-Uno, and parametric CAD environments for bio-reactor monitoring and urban optimization. Publications: 15 recent works cover topics from digital infrastructure in the Anthropocene to cybernetic feedback mechanisms in architecture, with a focus on adaptive geometries and human-machine co-evolution.