جست‌وجوی استاد و پژوهشگر

Judith Glaesserمشاهده پروفایل

پژوهشگر ارشد

• Sociology of Education
• Research Methods
• Qualitative Comparative Analysis (QCA)
• +۷ مورد دیگر

Judith Glaesser is a Research Fellow at the Methods Center, Department of Social Sciences, Faculty of Economics and Social Sciences, University of Tübingen. She has held academic positions at Durham University and the University of Konstanz, with a sustained focus on research methods, sociology of education, and educational inequality. Research Interests: Her work centers on qualitative comparative analysis (QCA), mixed-methods integration, educational decision-making, and competence modeling. She investigates how social background, ability, and institutional structures interact to shape educational outcomes in Germany and England. Her methodological contributions emphasize causal asymmetry, limited diversity in QCA, and the integration of survey and interview data. The most recent articles reflect a strong trend in methodological innovation, particularly in refining QCA techniques, exploring causal complexity, and analyzing longitudinal data on student affect and dropout. Her work spans sociology, education, and psychometrics, often in interdisciplinary collaboration. She also contributes critical book reviews on topics ranging from social theory to mental health in youth. Book Review: JH Goldthorpe, The Making of a Sociologist (2025) Book Review: The Anxious Generation (2025) Case-to-Condition Ratios in QCA (2025) Analysing causal asymmetry (2024) Chance and the limits of social science (2024) Advising and Grants: While specific students are not listed, her roles as Senior Lecturer and Research Fellow imply mentoring of graduate students. She has led and contributed to significant research projects, including the 'Kompetenzmodellierung' initiative at Tübingen School of Education. Her collaborative work with Kelava, Kilian, and Cooper suggests involvement in funded interdisciplinary teams focused on educational measurement and dropout prevention. Labs and Teams: She is affiliated with the Methods Center at the University of Tübingen, which supports advanced research methodology across social sciences. She has also been associated with the Tübingen School of Education (TüSE) and the Graduate College 'Early Concepts of Man and Nature' at Mainz, indicating participation in interdisciplinary research networks focused on education and epistemology.

• Database Systems
• Data Stream Processing
• Uncertain Data Management
• +۴ مورد دیگر

Tingjian Ge is an academic researcher with a focus on database systems, graph stream processing, and uncertain data management. His work spans theoretical foundations and practical implementations in data science, with a career trajectory showing increasing specialization in real-time network analytics and secure data processing. PhD from Brown University (2009) Active in top-tier venues: ICDE, KDD, VLDB, WWW Research Interests include: Approximate query processing under resource constraints Graph stream modeling and edge shedding techniques Security and privacy in data systems Temporal network analysis and predictive modeling Optimization of multi-core and cloud-based query execution Scientific Contributions demonstrate expertise in: Developing sketch data structures for graph streams Creating fairness-aware prediction frameworks Advancing differential privacy mechanisms Designing efficient temporal subgraph algorithms

Wenjie Ruanمشاهده پروفایل

مدرس ارشد

• Robustness of Deep Learning
• Safety of Deep Neural Networks
• Interpretability of Machine Learning
• +۷ مورد دیگر

Dr. Wenjie Ruan is a Senior Lecturer in Data Science at the Department of Computer Science, College of Engineering, Mathematics and Physical Sciences, University of Exeter, a Russell Group university. He is also the Co-Lead of the Trustworthy AI Theme at IDSAI. Previously, he was a Lecturer at Lancaster University and a Postdoctoral Researcher at the University of Oxford, funded by EPSRC. He holds a PhD from the University of Adelaide and conducted research at Tsinghua University. University: University of Exeter School: College of Engineering, Mathematics and Physical Sciences Department: Department of Computer Science Position: Senior Lecturer (~Associate Professor) Research Theme: Co-Lead, Trustworthy AI at IDSAI His primary research interests lie in robustness, safety, and interpretability of deep learning models, with applications in health data analytics and human-centred computing. He focuses on adversarial robustness, verification, testing, and explainable AI, particularly in safety-critical domains such as healthcare and autonomous systems. The recent publications reflect a strong trend in trustworthy machine learning, with emphasis on adversarial robustness (e.g., Vision Transformers, 3D models), verification techniques, and healthcare applications (e.g., COVID-19 severity prediction, EMR data analysis). His work often includes open-sourced tools like GUAP, DeepConcolic, and DeepGO, highlighting a commitment to reproducibility and practical impact. Dean's Commendation for Doctoral Thesis Excellence, University of Adelaide (2017) Scholarship for Outstanding PhD Students Abroad, Chinese Government (2017) Best Student Paper, ADMA 2016 Best Poster Award, ACM IOT & Cloud Computing Workshop (2016) PRF Project Grant (£180K) from ORCA Hub Subcontract from DSTL via Liverpool University (£15K) Dr. Ruan has actively advised numerous PhD and Master’s students, many of whom have achieved distinctions or secured prestigious positions. He has been involved in significant research grants, including projects on accountable AI in robotics and AI test coverage metrics for defense applications. His leadership in the ORCA-funded AELARS project demonstrates his role in guiding emerging researchers and shaping future work in trustworthy AI. He leads a dynamic research group and has hosted postdoctoral researchers like Dr. Syed Yuns. His team focuses on developing robust, verifiable, and interpretable AI systems, particularly in digital health and autonomous robotics. Collaborations with institutions such as Oxford, Liverpool, and Imperial College London further enrich the lab’s research ecosystem.

• Human-Computer Interaction
• Robotics
• Assistive Technologies
• +۵ مورد دیگر

Jens Gerken is a Professor at TU Dortmund University, Germany, specializing in Human-Computer Interaction with a particular focus on assistive robotics, tangible interfaces, and human-robot collaboration. His work bridges theoretical HCI research with practical applications for people with disabilities, resulting in numerous publications in top-tier venues including CHI, HRI, and INTERACT. Dr. Gerken's research interests center around making technology more accessible and intuitive, particularly through innovative interaction techniques. His current work explores how shared control systems, AI-enhanced interfaces, and extended reality can empower users with motor impairments. He has developed frameworks like AdaptiX for evaluating assistive robotic applications and investigates how to effectively communicate robot motion intent to users. His recent publications also address ethical concerns in interface design, particularly deceptive patterns in digital interfaces, using serious games as educational tools. The trajectory of his recent publications shows a consistent focus on human-centered robotics, with increasing integration of AI techniques. His work demonstrates a strong commitment to participatory design methods, frequently involving end-users with disabilities in the development process. The research spans from fundamental interaction techniques to complete system implementations, always maintaining a strong connection to real-world usability and accessibility needs. Dr. Gerken has mentored several doctoral students who have become active researchers in the field, including Max Pascher, Kirill Kronhardt, and Younes Lakhnati. His collaborative network extends across multiple institutions, with frequent partnerships with researchers at the University of Konstanz and other German universities. His projects often involve interdisciplinary teams combining expertise in computer science, engineering, and human factors. His laboratory work focuses on developing and testing assistive technologies in realistic settings, moving beyond traditional lab evaluations to more authentic contexts. Recent projects include developing robotic arms with adaptive control for users with limited mobility, creating transparency tools for AI-generated personas, and designing serious games to raise awareness about deceptive interface patterns.

Mansi Sharmaمشاهده پروفایل

پژوهشگر

• Human Computer Interaction
• Human-Robot Interaction
• Multi-modal Interaction
• +۲ مورد دیگر

Mansi Sharma is a doctoral researcher affiliated with the Ubiquitous Media Technology Lab (UMTL) at Saarland University and part of the Cognitive Assistants (COS) department at the German Research Center for Artificial Intelligence (DFKI). Her work bridges Human-Computer Interaction , Brain-Computer Interfaces , and Machine Learning , focusing on multimodal interaction and cognitive workload analysis. Research Interests: Human-Robot Interaction, Multi-modal Interaction, Brain-Computer Interfaces, Machine Learning. Teaching: Led seminars on Brain-computer Interaction in 2020 and 2022. Her publications explore EEG and eye-tracking applications in intent recognition, medical diagnostics, and cognitive workload assessment, often in collaboration with Antonio Krüger and Maurice Rekrut. She contributes to projects like EXPECT and KITTATA , with a focus on adaptive systems and neuroergonomics. Her recent work spans AI-driven medical evaluation, autonomous driving interface design, and VR-based psychophysical experiments, reflecting interdisciplinary applications of her core research areas.

• Visual Foraging
• Visual Attention
• Temporal-Order Perception
• +۴ مورد دیگر

Dr. Jan Tünnermann is a Research Fellow at the Philipps-Universität Marburg , affiliated with the Department of Cognitive Psychophysiology within the Faculty of Psychology. His research focuses on Visual Foraging, Temporal-Order Perception, and Artificial Visual Attention Systems , with particular emphasis on cognitive modeling and Bayesian estimation techniques. He investigates how attentional mechanisms guide human behavior in naturalistic and experimental settings, including foraging tasks, game-like experiments, and human-computer interaction scenarios. Research Interests : Visual Attention Dynamics and Template Switching Temporal-Order Judgment and Psychophysics Cognitive Models of Attentional Resource Allocation Artificial Visual Systems Inspired by Human Perception Recent work highlights attention's role in optimizing search strategies across oculomotor and manual tasks, revealing trade-offs between speed and accuracy. He collaborates on interdisciplinary projects, such as developing sensory substitution devices for visually impaired individuals and virtual cycling environments for human-in-the-loop experiments. His publications span journals like Journal of Experimental Psychology and Cognitive Computation , with a focus on advancing computational theories of visual attention. Key Contributions : Pioneering use of the Theory of Visual Attention (TVA) in real-world experiments Model-based analysis of temporal-order judgments Development of saliency detection algorithms for artificial systems No scientific awards explicitly listed, though his work has received attention for methodological innovations in attention research.

Agnieszka Wykowskaمشاهده پروفایل

استاد

• Social Cognition
• Human-Robot Interaction
• Neuroengineering
• +۳ مورد دیگر

Agnieszka Wykowska is a Professor and Principal Investigator leading the Social Cognition in Human-Robot Interaction unit at the Italian Institute of Technology (IIT), where she also coordinates the Center for Human Technologies (CHT). She holds adjunct professorships in Engineering Psychology at Luleå University of Technology and is a Hans Fischer Senior Fellow at TUM-IAS. Her research bridges cognitive neuroscience, robotics, and healthcare, focusing on understanding human brain mechanisms during interactions with technology. Education: Habilitation in Psychology (LMU Munich, 2013), PhD in Psychology (LMU Munich, 2008), M.Sc. in Neuro-Cognitive Psychology (LMU Munich, 2006). Research interests include social cognition, human-robot interaction, neuroengineering, and EEG-based studies. Key achievements include ERC grants (Starting Grant 2016, Proof-of-Concept 2024), presidency of ESCAN (2022–2024), and the André Mischke Award (2025). She edits the International Journal of Social Robotics and contributes to EU science policy via the ERA Forum. Current projects: RONIN (Robot Training Independence) and InStance (Intentional Stance for Social Attunement). Supervises PhD students in robotics, cognitive science, and human-robot collaboration.

Andreas Lachnerمشاهده پروفایل

استاد

• Educational Technology
• Teaching and Learning with Digital Media
• Adaptive Teaching
• +۱۲ مورد دیگر

Andreas Lachner is a Professor of Education with a focus on teaching and learning with educational technology at the University of Tübingen, Germany. He is affiliated with the Faculty of Economics and Social Sciences and the Department of Social Sciences. He also serves as co-director of the Tübingen Center for Digital Education (TüCeDe), a leading hub for digital education research and development. His work bridges theory and practice in educational innovation. Research Interests: His research centers on enhancing learning through educational technologies, particularly focusing on adaptive teaching, generative AI, computer-based feedback, and video explanations. He investigates how these tools support cognitive and motivational learning processes. A major strand of his work involves teacher professional development, especially in the context of technology integration and the development of Technological Pedagogical Content Knowledge (TPACK). Publication Trends: His recent publications (2023–2025) reveal a strong emphasis on TPACK, adaptive teaching with technology, feedback systems, and teacher knowledge. He frequently publishes in high-impact journals such as Computers & Education , Learning and Instruction , and Educational Psychology Review . His work combines experimental designs, systematic reviews, and theoretical modeling to advance evidence-based practices in digital education. Co-Director, Tübingen Center for Digital Education (since 2022) Coordinator, EARLI Special Interest Group 7: Technology-Enhanced Learning and Instruction (2019–2023) Advising and Grants: While specific students and grants are not listed, his leadership in multiple research projects—including DiA:GO, TüDiTeach, and TPACK 4.0—indicates active supervision of graduate students and successful grant acquisition. His collaborative network includes prominent researchers in educational psychology and teacher education. Labs and Teams: He is closely associated with the Tübingen Center for Digital Education and has collaborated extensively with the educational psychology group at the University of Tübingen, particularly with researchers like Katharina Scheiter and Kerstin Richter. His work often involves interdisciplinary teams focused on digital learning, teacher training, and cognitive science.

Meysam Goodarziمشاهده پروفایل

مدرس

• Artificial Intelligence
• Data Science
• Economics
• +۷ مورد دیگر

Meysam Goodarzi is a Lecturer at the Hertie School in Berlin, Germany, specializing in Data Structures & Algorithms within the Master of Data Science for Public Policy program. His research bridges computer science, economics, and probabilistic modeling, focusing on Bayesian inference, probabilistic graphical models, and optimization techniques. PhD in Computer Science (Humboldt University of Berlin) M.Sc. in Economics (Panthéon-Sorbonne University) His work emphasizes applications in data science and economics, particularly within AI-driven network optimization and 5G technology. He has contributed to EU Horizon 2020 projects, advancing synchronization, localization, and machine learning algorithms in telecommunications. Recent publications highlight his expertise in 5G networks , autonomous systems , and probabilistic modeling , with a focus on synchronization, localization, and communication-sensing integration. Articles span from 2024 to 2019, reflecting sustained contributions to 5G/6G research and AI applications. At Hertie School, he contributes to the Data Science Lab , integrating advanced computational techniques into public policy education. His interdisciplinary approach connects technical advancements in telecommunications with economic analysis and public sector applications.

Martin Kesternichمشاهده پروفایل

استاد

• Environmental Economics
• Behavioral Economics
• Sustainable Resource Management
• +۳ مورد دیگر

Prof. Dr. Martin Kesternich is a Professor of Economics, especially Sustainability, at the Department 4: Economics within the Faculty of Economics at the University of Paderborn. His research focuses on environmental and behavioral economics, addressing cooperation challenges in sustainable resource use and developing evidence-based solutions for climate policy and collective action problems. Faculty of Economics, University of Paderborn Department 4: Economics, Chair in Sustainability His work examines incentive structures for climate protection, behavioral decision-making in sustainability contexts, and policy instrument design for energy efficiency, equity in climate transitions, and consumer cooperation. He integrates microeconomic theory with interdisciplinary links to psychology and business studies. Recent publications analyze field experiments on energy efficiency, climate policy compliance, and behavioral interventions for low-income households. Key projects include DFG-funded research on "Asset Allocation and Asset Pricing" and policy evaluations for programs like "Energy Efficiency for All." He teaches modules including Field Experiments in Environmental and Behavioral Economics and Behavioral Environmental Economics , emphasizing critical analysis of causal relationships and preparing students for research through seminars connected to his work. Thesis supervision prioritizes microeconometric and experimental methods, requiring completion of statistical software courses. The research team includes collaborators such as Vicky Leoni Tinnefeld, Stephanie Langenströer, and Felix Sebastian Mörchel. The chair’s work bridges academic research with practical policy advice, evident in contributions to the Paris Climate Agreement analysis and the Three Minute Thesis Competition for student research dissemination.

• Blockchain Technology
• Distributed Systems
• Consensus Algorithms
• +۳ مورد دیگر

Wolf Posdorfer is a researcher at the University of Hamburg 's Department of Informatics, focusing on Blockchain Technology, Distributed Systems, Consensus Algorithms, Smart Contracts, IoT Optimization, and Energy Informatics . He contributes to projects like Baqend , SmartOpenHamburg , and HADeS . His research explores decentralized coordination mechanisms, including works on EU-GDPR compliant blockchains , transaction dependency models , and context-aware mobile systems . He has advised over 20 student theses on topics ranging from blockchain-based access control to peer-to-peer energy trading . Recent publications highlight his contributions to blockchain scalability , smart grid optimization , and citizen-centric sensor data marketplaces , with keywords spanning Computer Science, Distributed Ledger Technology, and IoT . He also co-supervises the Masterprojekt Entwicklung verteilter kontextbasierter Anwendungen and teaches courses on Mobile Computing and Decentralized Applications .

• Cognitive Psychology
• Educational Technology
• Human-Computer Interaction
• +۵ مورد دیگر

Maria Wirzberger is an Assistant Professor at the University of Stuttgart, specializing in Teaching and Learning with Intelligent Systems (LLiS). She serves as Spokesperson of the Stuttgart Research Focus IRIS and Co-Director of the AI Software Academy, focusing on adaptive teaching systems, cognitive modeling, and human-AI interaction. Her work bridges cognitive psychology, educational technology, and human-computer interaction, with a strong emphasis on self-regulation and attention control. Research Interests: Modeling human cognition, statistical analysis of behavioral data, distraction/interruption handling in digital environments, development of AI-driven educational tools, multimodal cognitive load assessment, and trust in AI systems. Scientific Contributions: 15 recent articles explore topics like AI feedback mechanisms for focus, emotion-performance dynamics in tutoring systems, sustainable behavior cognition, and neuroergonomic approaches to workload analysis. Grants & Collaborations: Involved in projects like the AI Software Academy and interdisciplinary studies on sustainability personas and cognitive pathways. Labs & Teams: Affiliated with the Stuttgart Research Focus IRIS and University of Stuttgart's LLiS department.

• Information Science
• Knowledge Management
• Social Media
• +۳ مورد دیگر

Alton Yeow-Kuan Chua is a Professor at Nanyang Technological University within the Wee Kim Wee School of Communication & Information , Singapore. With over 140 publications from 2003-2025, his work focuses on Information Science , Social Media , and User-Generated Content analysis. His research explores: Social question-answering dynamics Fake review and news detection Knowledge commodification on platforms Clickbait psychology Data analytics in sharing economy Rumor correction mechanisms Recent article trends (2021-2025) reveal expertise in: AI-driven content verification Epistemic belief modeling Gender-based risk perception Sentiment analysis in reviews Fact-checking flag effectiveness Knowledge celebrity economics Chua's work frequently employs experimental methods and machine learning across journals like Internet Research , Computers in Human Behavior , and conferences including ICADL and iConference . His collaborations with Dion Goh, Xiaoyu Chen, and Snehasish Banerjee demonstrate sustained interdisciplinary research.

Alona Zharovaمشاهده پروفایل

پژوهشگر

• AI-driven forecasting
• Recommendation systems
• Multi-agent systems
• +۷ مورد دیگر

Dr. Alona Zharova is a Postdoctoral Researcher at the Chair of Information Systems, Humboldt University of Berlin , and holds an Honorary Research Associate position at the University of Oxford's Environmental Change Institute. She received her Ph.D. in Statistics and Econometrics from Berlin's School of Business and Economics. Research Highlights: AI-driven energy efficiency systems Explainable multi-agent recommendation technologies Behavioral nudging for climate change mitigation Smart home/city energy management frameworks Academic performance evaluation methodologies International research collaborations (Australia, Singapore, UK, Cuba) Scientific Recognition: Joachim Herz Stiftung Transfer Fellowship (2025) Berlin University Alliance Strategic Partnership Grants Add-on Fellow, Interdisciplinary Economics (2023-2025) DAAD International Connections Grant (2023) Erasmus Mundus Exchange Fellow (2013-2014) Leadership & Service: Coordinated DFG-funded CRC and IRTG applications Supervisor of bachelor/master theses since 2020 Scientific committee member for major conferences Advisor to German-Cuban business incubator Volunteer support for Ukrainian researchers in Berlin

Stefan Scherbaumمشاهده پروفایل

استاد

• Cognitive Control
• Decision Making Dynamics
• Dynamic Cognitive Modeling
• +۵ مورد دیگر

Stefan Scherbaum is a Professor for Research Methods and Cognitive Modeling at TU Dresden's Institute for General Psychology, Biopsychology, and Methods of Psychology within the Faculty of Mathematics and Natural Sciences. He holds a PhD (2011) and MSc (2006) in Cognitive Science, with additional expertise in Computer Science in Media. His research focuses on dynamic processes in human cognition, particularly decision-making and cognitive control, employing EEG, mouse-tracking, and computational modeling. He has pioneered methods to analyze continuous behavioral data and validate dynamic neural field models. Education: PhD in Psychology, TU Dresden (2011), supervised by Prof. Thomas Goschke MSc in Cognitive Science, Universität Osnabrück (2006), supervised by Prof. Peter König Diploma in Computer Science in Media, Hochschule Furtwangen (2002-2006) Research Interests: Continuous empirical methods (frequency-tagged EEG, mouse tracking), dynamic modeling (connectionist/neural field models), decision conflict dynamics, and translational applications in clinical psychology (e.g., addiction, eating disorders). His work bridges cognitive neuroscience, computational modeling, and behavioral analysis. Awards: 2011: Best Dissertation Award, Cognitive Psychology Group (1st place) Volkswagen Foundation's European Platform Membership (2006–present) Grants & Advising: Leads research projects on executive functions, open science practices, and decision dynamics. Has supervised multiple postdocs and mentored junior researchers in computational methods. Labs/Teams: Directs the Cognitive Dynamics Lab at TU Dresden, collaborating on interdisciplinary projects involving EEG, behavioral tracking, and agent-based simulations.