جست‌وجوی استاد و پژوهشگر

• Human-Machine Interaction
• Model-based Development
• Intelligent Production Systems
• +۲ مورد دیگر

Claudia Fellner is a researcher at the Chair of Automation and Information Systems under Prof. Birgit Vogel-Heuser at the Technical University of Munich (TUM). She contributes to the chair's academic and research activities with office hours held Tuesday through Friday from 8:00 a.m. to 12:30 p.m. Her research aligns with the chair's core focus areas including Human-Machine Interaction for intuitive system interfaces, Model-based Development for engineering complex systems, Intelligent Production Systems integrating AI in manufacturing, Big Data applications in automated production environments, and Control Software Engineering for robust industrial systems. These fields address critical challenges in modern industrial automation through both theoretical and applied research. The chair maintains active research in numerous projects such as IEV4PI, advacode, AIValve, and CausAIITI, supported by facilities including the Visual Computing Laboratory and demonstrators like the Self-X Material Flow system. Claudia Fellner participates in these initiatives while supporting the chair's educational mission through teaching activities in mechatronics and automation disciplines.

• Industrial Cyber-Physical Systems
• Digital Twins
• Human-Machine Interaction
• +۶ مورد دیگر

Dominik Hujo is a researcher at the Chair of Automation and Information Systems at the Technical University of Munich (TUM). He holds a Master of Science degree and contributes to advanced research in industrial automation and AI integration. His research focuses on industrial cyber-physical systems , digital twins , human-machine interaction , and AI deployment in manufacturing environments . His work emphasizes real-time requirements, embedded systems, and data management for production processes. Dominik's publications from 2023-2025 demonstrate expertise in multi-agent coordination , predictive maintenance , edge-cloud architectures , and SysML modeling for mechatronic constraints . Key application areas include construction machinery, gear assembly, and logistics systems. He actively collaborates with researchers like Prof. Birgit Vogel-Heuser and Marius Krüger on projects such as KI.Fabrik (AI Factory) and OpAI4DNCS (Operator-AI Interaction for Distributed Control Systems).

Jeni Tennisonمشاهده پروفایل

پژوهشگر

• Data governance
• Open data
• Data policy
• +۶ مورد دیگر

Jeni Tennison is an expert in data governance, policy, and open data who serves as an Associated Researcher at the Bennett Institute for Public Policy at the University of Cambridge. She is also the founder and Executive Director of Connected by Data, a Shuttleworth Foundation Fellow, and co-chair of the Data Governance Working Group at the Global Partnership on AI. Her research focuses on challenging traditional notions of data ownership and consent, advocating for collective governance of data when processed in aggregate. She has a long-standing interest in open and web standards, having served on the W3C's Technical Architecture Group and co-chaired the W3C's CSV on the Web Working Group. Her work bridges academic research with practical implementation, having previously served as CEO of the Open Data Institute for nine years. Tennison's publications reveal a consistent focus on agent-based modeling of information economies, data governance frameworks, and the societal implications of data monopolies. Her work spans disciplines including computer science, economics, public policy, and information science, with particular emphasis on creating practical tools and frameworks for better data governance. OBE for services to technology and open data Shuttleworth Foundation Fellow As Executive Director of Connected by Data, she leads initiatives that put community at the heart of data narratives, practices, and policies. She serves on the Boards of Creative Commons, the Global Partnership for Sustainable Development Data, and the Information Law and Policy Centre. Her work involves substantial collaboration with governments, international organizations, and private sector entities to build trustworthy data ecosystems. She is also known for co-creating Datopolis, an open data board game that helps people understand data infrastructure concepts through gameplay.

Mahnoor Shahidمشاهده پروفایل

پژوهشگر

• Neuro Symbolic AI
• Symbol Grounding
• Natural Language Processing
• +۶ مورد دیگر

Mahnoor Shahid is a Researcher at the University of Duisburg-Essen , affiliated with the Faculty of Computer Science and the Chair of Information Systems and Sustainable Supply Chain Management . Specializes in Neuro Symbolic AI , aiming to create explainable and adaptable AI systems PhD candidate with prior experience as a Research Assistant at DFKI Education : B.Sc. Computer Science (NED University, Pakistan, 2014-2017) M.Sc. Data Science and Artificial Intelligence (Saarland University, Germany, 2020-2023) Research Interests : Symbol Grounding and Common Sense Reasoning in AI Natural Language Processing and Language Models Domain Adaptation and Transfer Learning Machine Learning Privacy for responsible AI Recent Research Trends : Developing neuro-symbolic architectures for generalization and compositional reasoning Advancing NILM (Non-Intrusive Load Monitoring) with domain adaptation techniques Exploring prompt analysis in LLM platforms for inverse generativity Building python packages for BERT probing and joint learning Applying creative AI to text-to-image generation Investigating web security through ML-based threat detection Labs & Projects : Active in the Rhine-Ruhr Institute of Information Systems Maintains open-source python packages for NILM analysis Key contributor to tools like nilm_analyzer and nilm_analyzer_tutorials

Martin Eberleinمشاهده پروفایل

پژوهشگر

• Software Engineering
• Automated Software Testing
• Vulnerability Detection
• +۴ مورد دیگر

Martin Eberlein is a Doctoral Researcher and Ph.D. candidate in the Software Engineering group at Humboldt University of Berlin, Germany, working under Prof. Lars Grunske. Previously, he collaborated with Prof. Andreas Zeller's research group at CISPA Helmholtz Center for Information Security. His research focuses on automated software engineering, particularly software testing, vulnerability detection, and fuzzing. He is currently part of the EMPEROR project, which aims to automatically generate explanations for program behaviors, especially failures. Dr. Eberlein has developed notable tools including Avicenna (for explaining why programs fail) and EvoGFuzz (an evolutionary, grammar-based fuzzer). Education: 2022-Present: Dr. rer. nat. (PhD), Computer Science, Humboldt-Universität zu Berlin 2020-2022: Master of Science (M.Sc.), Computer Science, Humboldt-Universität zu Berlin (Final Grade: 1.0) 2015-2020: Bachelor of Science (B.Sc.), Computer Science, Humboldt-Universität zu Berlin (Final Grade: 1.3) His publications demonstrate innovative approaches to software testing and debugging, with emphasis on explaining program failures through machine learning. Recent work includes 'Which Inputs Trigger My Patch?' (APR'2025) and 'jAST' (FSE'2025), showing trends toward automated explanation of software behavior and program analysis tools. Scientific Awards: Black Shirt from HU-Berlin research group (2025) €900k initial funding for InputLab startup Dr. Eberlein serves on program committees for FSE 2025 (Artifact Evaluation Track) and ISSTA 2025 (Tools Demonstrations Track). He organizes and assists with teaching courses at HU Berlin, particularly in Software Engineering II and Compiler Construction. As co-founder of InputLab, he bridges academic research with practical applications in software testing for government and business formats. He maintains active research collaborations through GitHub, his blog, and participation in major software engineering conferences worldwide.

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +۵ مورد دیگر

Thomas Kosch serves as Professor at the Institute of Computer Science within the Faculty of Mathematics and Natural Sciences at Humboldt University of Berlin. His research group Human-Computer Interaction for Scientific Software develops innovative interfaces for scientific applications, with laboratory facilities at Rudower Chaussee 25, 12489 Berlin-Adlershof and administrative correspondence via Unter den Linden 6, 10099 Berlin. His research spans Human-Computer Interaction, Virtual/Augmented Reality, Artificial Intelligence, and Neurophysiological Computing. Key interests include cognitive augmentation through EEG/EMG systems, motor learning with electrical muscle stimulation, large language model integration in UX workflows, and privacy implications of tracking technologies. His work bridges theoretical HCI frameworks with empirical validation through controlled experiments involving physiological measurements and immersive environments. Analysis of his 15 most recent publications (all 2025) reveals three dominant trends: (1) Critical examination of LLM limitations through prompt-hacking and deceptive design studies, (2) Neurophysiological validation of cognitive phenomena using multimodal sensing (EEG/eye-tracking), and (3) Application-driven XR solutions for veterinary care, navigation, and motor assessment. These works consistently employ rigorous user studies with quantitative behavioral metrics. No scientific awards are documented in the provided materials, though his publication volume in top-tier venues (e.g., CHI, UIST) indicates significant field contributions. Professor Kosch actively supervises doctoral candidates, with at least one PhD defense (Michael Piechotta, Dipl.-Bio-Inf.) scheduled for September 2025. His research group likely secures competitive grants supporting equipment-intensive projects involving EEG systems, VR setups, and physiological sensors, though specific funding sources aren't detailed. The Human-Computer Interaction for Scientific Software group operates as an interdisciplinary hub combining computer science, cognitive psychology, and domain-specific applications. Current projects involve developing open-source tools like MorphoHaptics for medical imaging, MIRAGE for fall hazard detection, and Senscon for physiological sensing integration in VR controllers.

• Human-Computer Interaction
• Software Engineering
• Virtual Reality
• +۵ مورد دیگر

Christopher Lazik is a Researcher at Humboldt University of Berlin's Institute of Computer Science within the Faculty of Mathematics and Natural Sciences, specializing in the Software Engineering group. His work bridges technical innovation with human-centered design across emerging technology domains. His research focuses on Human-Computer Interaction, Software Engineering, and immersive technologies, with particular emphasis on Large Language Models for user experience design, value-aware software development, and empathic interfaces. Key themes include human factors in AI systems, psychological impacts of virtual environments, and safety applications of mixed reality, reflecting interdisciplinary engagement between computer science and social sciences. Recent publications (2022-2025) reveal a concentrated research trajectory on generative AI applications, with 6 of 8 papers published in 2024-2025. His work demonstrates strong alignment between technical implementation (e.g., mixed reality safety systems, workflow specification languages) and human behavior considerations, indicating a consistent focus on usability and societal impact of emerging technologies. No scientific awards were mentioned in the available documentation. There is no available information regarding student advising or research grants in the provided materials. Lazik operates within the Software Engineering research group at Humboldt's Institute of Computer Science, located at the Adlershof science park campus, contributing to the university's interdisciplinary research initiatives in human-centered computing.

• Computational Linguistics
• Empirical Educational Science
• Intelligent Computer-Assisted Language Learning (ICALL)
• +۱۰ مورد دیگر

Prof. Dr. Walt Detmar Meurers is a Research Professor at the Leibniz Institute for Knowledge Media (IWM) since April 2024, leading the Language and AI in Education research group. Previously, he served as a Full Professor of Computational Linguistics and head of the Theoretical Computational Linguistics group at the University of Tübingen (2008–2024). His career spans roles at The Ohio State University (Assistant to Associate Professor, 2001–2008), Universitet i Tromsø (Professor II, 2013–2016), and University of Tübingen (Lecturer, 1997–2000). His research bridges Computational Linguistics and Empirical Educational Science, focusing on Second Language Acquisition, Intelligent Computer-Assisted Language Learning (ICALL), learner corpora analysis, and linguistic complexity modeling for adaptive educational systems. Key projects include FeedBook (adaptive English learning), MERLIN (learner corpus analysis), and CoMiC (semantic comparison in education). He has contributed to formal syntax-information structure interfaces within the HPSG framework and advocated for integrating linguistic theory with educational technology. Scientific Leadership: Steering Board, LEAD Graduate School and Research Network Steering Committee, Heritage Language Consortium Scientific Advisory Board, CATALPA and SZHB Consultant, EFCAMDAT project Education: PhD in Computational Linguistics, University of Tübingen (2000) MA in Linguistics, Computer Science, Psychology, University of Tübingen (1994) ERASMUS exchange at IRIT, Université Paul Sabatier Impact: Co-authored Language and Computers (freely available as an open-access textbook) Organized workshops: AALL'09, IICALL Advisory roles for start-ups: cabuu, Prosodiya

Siegfried Zürnمشاهده پروفایل

استاد

• Digital Transformation Management
• Quality Management
• Systems Thinking Modelling
• +۳ مورد دیگر

Prof. Siegfried Zürn holds a professorship in Operations Management at the University of Applied Sciences Esslingen. He currently serves as Director of the International Centre and Graduate School, and previously as Dean of the Faculty Graduate School. His academic roles include membership in the Building Committee and International Committee. He leads act.if Consulting Group, focusing on operational and digital transformation consulting. His research interests center around Digital Transformation Management, Quality Management, and Systems Thinking Modelling. He has pioneered business simulation tools like 'Sustain2030®' and 'StarsEngines' for teaching complex management concepts. His work integrates Industry 4.0 strategies with quality systems, emphasizing SME digitalization challenges and sustainable business frameworks. Key contributions include over 30 peer-reviewed publications since 2019, addressing topics like AI integration in quality processes, digital transformation frameworks, and SDG implementation strategies. He has presented at international conferences including the NUST Public Lecture (Namibia) and the BRITAE Conference (Sri Lanka), focusing on systemic approaches to modern management challenges. Consultation Hours: Thursdays 9:00-9:30 via Webex or F02.122 Professional Certifications: Professional Scrum Master (PSM I), ECQA Certified Innovation Manager Memberships: German Association for Project Management (GPM), DGQ (Quality Management), SAGSAGA (Simulation & Gamification) His professional experience spans 14 years in industry roles, including Director positions at BASF Construction Systems and Xella Group, where he managed international operations and technology development.

• Software Testing
• Machine Learning
• Big Data Analytics
• +۷ مورد دیگر

Jerry Zeyu Gao is a Professor at San Jose State University's College of Engineering, Department of Computer Engineering. He has affiliations with institutions like University of Auckland, University of Melbourne, and Xi'an Jiaotong University, reflecting a global research network. PhD in Computer Science and Engineering from University of Texas at Arlington (1995) Research focus: Software testing, AI, machine learning, and smart systems His research spans AI testing , mobile application quality assurance , and big data analytics for smart cities. Recent work includes autonomous vehicle testing , drone-based security systems , and encryption technologies . Publications highlight GUI testing , environmental data modeling , and reinforcement learning applications. Key trends include machine learning in test automation , smart city infrastructure , and data-driven environmental solutions . He has served as General Chair for IEEE CISOSE conferences and contributed to AI quality standards. His work involves collaborations with researchers across institutions, focusing on security , data quality , and urban sustainability . Notable projects: smart OCR testing , EV charging infrastructure analysis , and automated graffiti detection .

• Machine Learning
• Neural Networks
• FPGA Optimization
• +۳ مورد دیگر

Vladimir Loncar is a researcher specializing in machine learning, FPGA optimization, and high-energy physics computing. His work focuses on accelerating neural networks and scientific algorithms using hardware-aware techniques. Notably, he contributes to the hls4ml framework for FPGA deployment of machine learning models, and has applied these methods to particle physics experiments like LHCb and the HL-LHC. His research spans symbolic regression, recurrent neural networks, and real-time data processing for large-scale physics detectors. Key projects include developing resource-efficient inference systems (e.g., Tailor for CNN optimization), benchmarking frameworks for GNN-based surrogate models, and latency-critical implementations for collider experiments. Loncar's work bridges theoretical physics and computational engineering, emphasizing practical applications in experimental particle physics, quantum simulations, and autonomous detector control. He collaborates extensively with institutions like CERN and the sPHENIX collaboration.

• Computer Science Education
• Educational Technology
• Mastery Learning
• +۳ مورد دیگر

Daniel D. Garcia is a Professor in the Department of Computer Science at the University of California, Berkeley. He specializes in computer science education, focusing on innovative teaching methods, mastery learning, and the development of educational technology tools. His work includes contributions to platforms like Snap!, Prairielearn, and GradeSync, which aim to enhance student engagement and learning outcomes through adaptive and automated systems. Research Interests Computer Science Education: Developing curricula and tools for K-12 and university-level instruction. Educational Technology: Designing interactive tools like Snap! and automated assessment systems. Mastery Learning: Implementing policies and systems to improve student success in computing courses. Cybersecurity Education: Integrating security concepts into introductory computing courses. Articles Trends Recent work emphasizes tools for automated assessment (e.g., Checkpoint, GradeSync), mastery learning systems, and interactive programming environments. He also explores the impact of course policies on student performance and sentiment. Awards No specific awards listed in the provided texts. Advising & Grants Collaborates with teams on grants related to educational technology and curriculum development, though specific grants are not detailed here. Advises students on projects related to the Beauty and Joy of Computing (BJC) curriculum and Snap! development. Labs/Teams Part of the BJC curriculum development team and leads initiatives at UC Berkeley for improving computing education through technology and pedagogy innovation.

• Educational Technology
• Cognitive Science
• Human-Computer Interaction
• +۳ مورد دیگر

Richard Catrambone is a Professor at Georgia Institute of Technology, Atlanta, USA, specializing in cognitive science and educational technology. His work focuses on instructional design, multimedia learning, and cognitive processes in problem-solving contexts. With over 60 publications spanning decades, his research emphasizes strategies like subgoal labeling and self-explanation to enhance learning outcomes in STEM education and programming instruction. Key contributions include studies on deepfake detection's cognitive aspects, the role of virtual agents in learning environments, and optimizing procedural instruction formats. He collaborates frequently with institutions like Georgia Tech's School of Psychology and School of Interactive Computing, and co-authors include notable researchers such as Lauren Margulieux and John Stasko. His work appears in journals like Human Factors, Computers & Education, and ACM Transactions on Computer-Human Interaction, highlighting intersections between cognitive science and technology-mediated learning. Despite prolific output, no specific awards or grants are explicitly mentioned in the provided texts.

• Cryptography
• Privacy-Preserving Technologies
• Secure Computation
• +۳ مورد دیگر

Ágnes Kiss is a Researcher at the Department of Computer Science, Technical University of Darmstadt, Germany. She earned her PhD in 2021 with a thesis titled Efficient Private Function Evaluation . Her research focuses on cryptographic protocols, privacy-preserving technologies, and secure computation, with applications in distributed systems and real-world security challenges. Her work spans topics such as private function evaluation (PFE), universal circuit design, and privacy-preserving location proximity schemes. She has contributed to advancing secure computation efficiency and resistance against side-channel attacks. Her publications appear in top venues like Journal of Cryptology , EUROCRYPT , and USENIX Security Symposium . Key areas of interest include cryptography, algorithmic countermeasures, and the practical implementation of secure protocols. Her recent work addresses security risks in scripting languages and explores trustworthy AI inference systems, reflecting her commitment to both theoretical and applied cryptography.

Gábor Kismihókمشاهده پروفایل

پژوهشگر

• Learning Analytics
• Artificial Intelligence in Education
• Ontology Engineering
• +۳ مورد دیگر

Dr. Gábor Kismihók is a senior researcher at the Corvinus University of Budapest specializing in learning analytics , ontology engineering , and AI-driven educational systems . His work bridges academic research with practical applications in career development , educational technology , and researcher mental health . Leading Learning and Skill Analytics research group Developing ontology-based educational systems since 2005 Pioneering AI-driven career recommendation ontologies His research focuses on: Personalized learning through knowledge graphs and semantic technologies Academic mental health advocacy and survey design Labor market intelligence integration with educational systems Mobile learning frameworks for vocational education Text mining applications in organizational research Competency validation between education and workplace Recent publications demonstrate expertise in: Large language model integration for adaptive learning Geriatric care technology redefining nursing competencies Skills gap analysis in AI and big data Digital educational federation systems like DALIA FAIR Academic well-being measurement frameworks He has contributed to: Multiple IEEE/ACM conference proceedings (2016-2023) European training networks like INSPIRE and ReMO COST Action Policy development through researcher well-being manifestos