جست‌وجوی استاد و پژوهشگر

• Digital Archiving
• Conventional Archiving
• Digital Preservation
• +۳ مورد دیگر

Christian Keitel is an Honorary Professor for Archival Science and Digital Archiving at the University of Applied Sciences Potsdam. He works at the Landesarchiv Baden-Württemberg, where he has served since 2000, currently as Deputy Head of Department 2 (Specialized Programs and Educational Work). His research focuses on conceptual principles of conventional and digital archiving, DIMAG systems, certification of digital archives, authenticity of digital records, and cooperative learning processes in digital archiving. University of Applied Sciences Potsdam – Honorary Professor (2015–) Landesarchiv Baden-Württemberg – Deputy Head of Department (2011–), Senior Archivist (2000–) Keitel’s scholarly work emphasizes digital preservation, metadata standards, and long-term archive certification. His publications address challenges in trustworthiness of digital repositories, significant properties of electronic records, and collaborative digital archiving frameworks. He co-authored DIN standards 31644 and 31645 for trustworthy digital archives. Recent articles highlight his contributions to digital ingest workflows, metadata extraction, and municipal archive solutions. His work explores intersections between traditional archival principles and modern digital challenges, including authenticity verification, system development, and cross-institutional cooperation.

Ajda Pretnar Žagarمشاهده پروفایل

پژوهشگر

• Computational Anthropology
• Machine Learning Applications in Social Sciences
• Data Mining
• +۳ مورد دیگر

Dr. Ajda Pretnar Žagar is a researcher at the University of Ljubljana's Faculty of Computer and Information Science and the Institute for Contemporary History. With a PhD in Anthropology from the University of Ljubljana (2021), she bridges computational methods with social sciences through interdisciplinary research. University of Ljubljana Institute for Contemporary History Her research focuses on: Quantitative Anthropology Computational Social Sciences Machine Learning Applications Algorithmic Futures Bioinformatics Recent projects include: REIMAGINE ADM (2022-2025): Reimagining public values in algorithmic futures DALI4US (2024-2026): Data Literacy for upper primary schools xAIM (2021-2024): Explainable AI in healthcare

• Business Process Management
• Process Mining
• Object-Centric Process Mining
• +۶ مورد دیگر

Amin Jalali is an Associate Professor of Computer and Systems Sciences at Stockholm University, specializing in business process modeling, analysis, and management. He is affiliated with the Department of Computer and Systems Sciences within the Faculty of Social Sciences, where he serves as a board member and manages three graduate courses: Business Process Design and Intelligence, Business Process and Case Management, and Data Warehousing. Institution: Stockholm University Department: Department of Computer and Systems Sciences (DSV) Research Groups: Natural Language Processing Research Group and PRECIS (Process, Requirements, Enterprise, Capability, Information Systems modelling) His research focuses on business process analysis through model-based and data-driven techniques, with particular emphasis on process simulation, process mining, event knowledge graphs, and object-centric process mining. He has led numerous research projects across healthcare, education, and finance domains. His work includes significant contributions to the development of NLP methods involving large language models, with focus on privacy, explainability, and domain adaptation. Jalali's research output shows a strong trend toward practical applications of process mining techniques, particularly in healthcare contexts like drug-drug interaction analysis and elderly care. More recently, his work has expanded into blockchain applications for fraud detection, motor imagery signal classification, and advanced object-centric process mining approaches. His publications span both theoretical contributions to business process management frameworks and practical implementations in real-world settings. He has extensive industry experience in designing and implementing Business Intelligence and Big Data Analytics solutions, which informs his academic work and teaching approach. His research has been published consistently from 2012 through 2024, demonstrating sustained scholarly productivity in his field. Dr. Jalali has contributed significantly to the development of tools and libraries for process mining, including the dfgcompare library for process variant analysis and implementations for object-centric process mining. His work bridges academic research with practical applications, particularly evident in healthcare projects like the DDIs-Graph system for identifying drug-drug interactions.

Dan Gutfreundمشاهده پروفایل

پژوهشگر

• Machine Learning
• Natural Language Processing
• Computer Vision
• +۳ مورد دیگر

Dan Gutfreund is a Principal Research Scientist and Senior Manager at the MIT-IBM Watson AI Lab, focusing on machine learning with applications to natural language processing and computer vision. He previously held managerial and technical roles at IBM's Haifa Research Lab and was involved in IBM Project Debater. Gutfreund earned his PhD in computer science from the Hebrew University in Jerusalem in 2005. His research spans Neuro-Symbolic AI , Computational Complexity , and Foundations of Cryptography , with notable contributions to datasets like Moments in Time and ObjectNet . His recent work includes multimodal models for the metaverse, generative AI for engineering design, and simulator-assisted training for interpretable systems. Gutfreund's publications reflect expertise in AI applications for supply chain prediction, avatar personalization, and reconciling virtual disputes. He has also explored evolutionary algorithms for software engineering and constraint-based generative models in design tasks.

Karl Ulrichمشاهده پروفایل

استاد

• Product Design
• Innovation
• Entrepreneurship
• +۳ مورد دیگر

Karl T. Ulrich is the CIBC Endowed Professor at the Wharton School of the University of Pennsylvania, with dual appointments in the Department of Operations, Information and Decisions and the Department of Mechanical Engineering. A renowned scholar and practitioner in product design, innovation, and entrepreneurship, he has co-founded key institutions like Venture Lab, the Weiss Tech House, and the Integrated Product Design Program. His work bridges academic rigor with real-world impact, evidenced by 24 patents and ventures such as Terrapass Inc. and the Xootr scooter. Education : MIT (BS, MS, ScD in Mechanical Engineering) His research focuses on product design , innovation , and entrepreneurship , with recent articles exploring animal ethics in food supply chains and evidence-based housing standards . Earlier work investigates machine learning in idea generation and innovation tournaments . Awards include the Anvil Award, Miller-Sherrerd Award, and multiple Excellence in Teaching Awards at Wharton. He has taught courses like Product Design , Product Management , and Innovation , often incorporating studio and project-based learning. His executive education programs emphasize strategic technology leadership and global business challenges.

Franc Solinaمشاهده پروفایل

استاد

• Computer Vision
• Human-Computer Interaction
• 3D Documentation
• +۶ مورد دیگر

Franc Solina is a Full Professor at the Faculty of Computer and Information Science , University of Ljubljana, Slovenia. He holds a Ph.D. from the University of Pennsylvania and has been active in academia since the 1990s. Education: Dipl.Ing. (1979) and M.S. (1982) in Electrical Engineering, University of Ljubljana Ph.D. (1987) in Computer and Information Science, University of Pennsylvania Research Interests: His work spans Computer Vision (superquadric modeling, underwater archaeology documentation), Human-Computer Interaction (interactive art installations, sign language technology), and Air Transport Applications (machine learning for aircraft trajectory prediction). He also explores Color-Based Applications and Visual Expression in art-technology intersections. Publication Trends: Franc's 15 most recent articles focus on superquadric modeling (1990-2004), underwater archaeology (2013-2015), and machine learning applications (2020). His work bridges theoretical computer vision with practical implementations in art and aviation. Students: He has supervised notable students like Marko Hrastovec (2018 thesis on aircraft trajectory prediction) and Tim Oblak (2020 work on superquadric deep learning). Labs & Teams: A key member of the University of Ljubljana's Computer Vision Laboratory , he collaborates with international researchers in projects like the Slovenian sign language web dictionary and air traffic safety initiatives .

Xiongcai Caiمشاهده پروفایل

دانشیار مدعو

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۳ مورد دیگر

Dr. Xiongcai Cai is an Adjunct Associate Professor at the School of Computer Science and Engineering, University of New South Wales (UNSW). With expertise in Artificial Intelligence , Machine Learning , and Computer Vision , he contributes to advancing Recommender Systems , Natural Language Processing , and Health Informatics . His work bridges theoretical and applied research in technology for human-centric applications. Current roles: Adjunct Associate Professor, UNSW School of Computer Science and Engineering Key research areas: Machine Learning, Recommender Systems, Computer Vision, Generative AI Dr. Cai's research portfolio demonstrates a consistent focus on recommender systems and machine learning over the past decade. His technical contributions span graph convolutional networks , temporal bilinear models , and embedding techniques for collaborative filtering. Recent work in 2025 addresses knowledge distillation for GCNs-based recommenders, while earlier studies tackled cold-start transitions and matrix factorisation boosting. His publication history (2 book chapters, 7 journal articles, and 36 conference papers) reveals a strong emphasis on real-time applications in domains like gait recognition (2020), health data analytics (2016), and social network recommendation (2010-2015). The research applies mathematical rigor to practical challenges in online dating platforms , medical decision support , and object tracking systems . Contact details: Email: x.cai@unsw.edu.au Phone: +61 2 9385 8858

• Military Strategy
• Artificial Intelligence
• Data Science
• +۵ مورد دیگر

Benjamin Jensen is Professor of Strategic Studies at Marine Corps University School of Advanced Warfighting and holds dual roles as Director of the Futures Lab and Senior Fellow in the Defense and Security Department at the Center for Strategic and International Studies (CSIS). At CSIS, he leads AI/machine learning research on warfare evolution and designs scenario-based wargames. At MCU, he researches future conflict and teaches operational art. His research explores military innovation, AI integration in battle networks, cybersecurity, geopolitical competition, and gray-zone tactics. Recent work analyzes landpower evolution, China-Taiwan tensions, and Russia-Ukraine dynamics through data-driven frameworks. Jensen holds a PhD from American University and MA/BA from University of Wisconsin-Madison. He serves as a U.S. Army Reserve officer with command experience and authored five books including Information at War: Military Innovation, Battle Networks, and the Future of Artificial Intelligence (2022). Scientific Awards: Frank E. Petersen Chair for Emerging Technology (current) He directs CSIS Futures Lab pioneering AI-wargaming integration and leads MCU's future war research program. Previously served as Senior Research Director for the U.S. Cyberspace Solarium Commission.

• Decision Support Systems
• Energy Management
• Sustainable Energy Planning
• +۸ مورد دیگر

Dr. Vangelis Marinakis is an Assistant Professor at the School of Electrical and Computer Engineering (ECE) of the National Technical University of Athens (NTUA). His academic background includes an Electrical and Computer Engineering degree and a PhD in Decision Support Systems for Sustainable Energy Planning from NTUA. PhD in Decision Support Systems for Sustainable Energy Planning (NTUA) Electrical and Computer Engineer (NTUA) His research focuses on designing methodologies for intelligent energy management across Smart Homes, Buildings, Cities, and Districts, leveraging technologies like IoT, AI, and Big Data. He has contributed to over 25 European (Horizon Europe, H2020) and national projects, with more than 50 journal publications and book chapters. Key research areas include Decision Support Systems , Energy Efficiency , and Renewable Energy Integration . He has led research in AI-driven energy forecasting, federated learning for privacy-preserving data models, and blockchain applications in energy markets. His work explores the intersection of Smart Grids , Building Informatics , and Climate Resilience . Dr. Marinakis has developed frameworks for: Decarbonization-as-a-Service in building renovations Scalable Big Data architectures for smart buildings Multi-criteria optimization of EV charging stations Explainable AI in energy decision-making Climate resilience assessment for urban housing

Nikolaos Papaspyrouمشاهده پروفایل

استاد

• Programming Languages
• Software Engineering
• Formal Verification
• +۴ مورد دیگر

Nikolaos Papaspyrou is a Professor at the School of Electrical and Computer Engineering of the National Technical University of Athens (NTUA) and a member of the Software Engineering Laboratory . His research focuses on the theory and implementation of programming languages, including semantics, type systems, compilers, static analysis, and formal verification. Since October 2021, he has been on leave from NTUA, working as a Software Engineer for Google in the memory management team for the V8 JavaScript and WebAssembly engine. He previously served as Director of the Division of Computer Science (2017-2019) and was on sabbatical with Google's compiler group in Munich (2015-2016). His work includes the RELEASE project (EU FP7 STREP) for reliable large-scale server software and uncertainty handling in distributed databases (European Social Fund). Ph.D. and Diploma in Electrical and Computer Engineering from NTUA M.Sc. in Computer Science from Cornell University His research interests span programming languages , software engineering , and formal verification , with recent publications on coinductive proofs in Liquid Haskell, concurrency semantics, and quantum compilation. He has supervised over 50 diploma projects and mentored numerous students now at institutions like MIT, Princeton, and UC Berkeley. Awards include conference organizing and program committee roles, though no formal scientific prizes are listed.

Guy Rosmanمشاهده پروفایل

دانشیار مدعو

• Machine Learning
• Surgical Computer Vision
• Human-Aware Robotics
• +۳ مورد دیگر

Guy Rosman is an Adjunct Associate Professor at Duke University, affiliated with both the Department of Surgery and the Department of Biostatistics & Bioinformatics. He has extensive academic and industry experience, including postdoctoral work at MIT/CSAIL and roles at IBM Research, RAFAEL Ltd., Medicvision, Invision Biometrics (Intel RealSense), and the Toyota Research Institute, where he leads the Human Aware Interaction & Learning team. Education: Ph.D., MSc, and BSc from the Technion - Israel Institute of Technology in Computer Science. Dr. Rosman’s research focuses on applying machine learning and inference techniques to surgical computer vision, human-aware robotics, autonomous driving, and sensor modeling. His work bridges robotics, AI, and medical applications, emphasizing human-centric systems and real-time learning. Recent publications highlight his contributions to generative robot simulation, surgical event prediction, driver safety interfaces, and shared autonomy. These works span robotics, machine learning, and AI applications in surgery and autonomous systems, with a recurring emphasis on human-aware algorithms and sensor-driven modeling. Scientific Awards: Technion-MIT Post-Doctoral Fellowship, Jacobs-Qualcomm Fellowship. Dr. Rosman’s industry leadership includes developing AI-driven robotics and sensor systems, while his academic roles involve collaborative research across Duke’s departments and MIT/CSAIL. He also co-edited the 2021 book Artificial Intelligence in Surgery , underscoring his interdisciplinary focus.

Michael Johannes Barzمشاهده پروفایل

پژوهشگر

• Interactive Machine Learning
• Federated Learning
• Eye Tracking
• +۴ مورد دیگر

Dr.-Ing. Michael Johannes Barz is a researcher affiliated with the German Research Center for Artificial Intelligence (DFKI), specializing in Interactive Machine Learning . His work bridges human-computer interaction with machine learning systems, focusing on applications like eye tracking, federated learning, and augmented reality. His research explores: Interactive annotation tools for mobile eye tracking data Web-based federated learning frameworks Inductive message passing networks for human-in-the-loop systems Recent publications highlight his contributions to computer science and artificial intelligence, particularly in user-centric machine learning paradigms. He actively collaborates with interdisciplinary teams on projects such as No-IDLE, MASTER, and GeAR.

Nitin Agarwalمشاهده پروفایل

استاد

• Social Computing
• Behavior-Cultural Modeling
• Collective Action
• +۶ مورد دیگر

Nitin Agarwal is the Jerry L. Maulden-Entergy Chair & Donaghey Distinguished Professor of Information Science at the University of Arkansas – Little Rock (UALR), where he has been a faculty member since Fall 2009. He serves as the Founding Director of the Collaboratorium for Social Media and Online Behavioral Studies (COSMOS) and holds a Faculty Fellowship at the International Computer Science Institute, University of California, Berkeley. His work spans social computing, behavior-cultural modeling, collective action, and social cyber forensics. Education: Ph.D. in Computer Science, Arizona State University (2009) Bachelor of Technology in Information Technology, Indian Institute of Information Technology (2003) Dr. Agarwal’s research focuses on understanding digital/cyber social behaviors, particularly coordinated disinformation campaigns. He has secured over $25 million in federal grants from agencies like DoD, DARPA, and NSF. His tools (Blogtracker, VTracker) are used by NATO, DHS, and WHO. Recent work includes modeling toxicity propagation, analyzing algorithmic biases, and combating misinformation via AI-driven frameworks. His publications cover social cyber forensics, AI, and computational epidemiology, with 11 books and over 300 peer-reviewed articles. His 2025 articles emphasize YouTube’s recommendation algorithms, Instagram’s visual media impact, and TikTok’s role in political mobilization. Themes include anomaly detection, semiotic analysis, and toxicity mitigation using epidemiological models. Scientific Awards: University-wide Faculty Excellence Awards (2015, 2021) Social Media Educator of the Year (2015) NATO Innovation Hub Top 10 Solution (2021) WHO Recognition for COVID-19 Misinformation Tracker (2022) IEEE Senior Member (2022) Dr. Agarwal advises Little Rock-based FinTech firms and collaborates with global governments and defense agencies. His COSMOS lab leads projects on cognitive warfare, disinformation, and social network simulations, supported by extensive media coverage in Bloomberg, US News, and local outlets.

Riccardo Rosatiمشاهده پروفایل

استاد

• Knowledge Representation
• Description Logics
• Semantic Web
• +۷ مورد دیگر

Riccardo Rosati is a Full Professor at the Department of Computer, Control, and Management Engineering, Sapienza University of Rome, affiliated with the Faculty of Information Engineering, Computer Science and Statistics. He obtained his PhD in Computer Science from Sapienza University of Rome in 1997. His research focuses on Knowledge Representation, Description Logics, Semantic Web, Ontologies, Information Integration, Databases, and Artificial Intelligence. Specifically, he has made significant contributions to the integration of description logics and logic programming, and is one of the creators of the DL-Lite family of description logics, which became a standard in the Semantic Web (OWL 2 QL). His recent publications center around controlled query evaluation, ontology-based data access, and applying knowledge representation in healthcare informatics. The trend shows strong emphasis on both theoretical foundations and practical applications. Scientific awards and recognitions include: Distinguished Paper Award at IJCAI 2024 AAAI 2021 Classic Paper Award He has advised numerous students and been involved in research projects including OPTIQUE (Scalable End-user Access to Big Data), ACSI (Artifact-Centric Service Interoperation), TONES (Thinking Ontologies), INFOMIX (boosting information integration), QuOnto (Querying Ontologies), and HYPER (How Your Peers Exchange Resources). He leads the Artificial Intelligence and Knowledge Representation research group and collaborates with the Data Management and Service-Oriented Computing group at DIAG.

• Medical Assistive Technology
• Robotics and Intelligent Systems
• Design Engineering
• +۳ مورد دیگر

Eiichiro Tanaka is a Professor at Waseda University's Faculty of Science and Engineering , specializing in Medical Assistive Technology , Robotics , and Design Engineering . His research focuses on developing wearable robotic systems for gait training, neuro-rehabilitation, and elderly mobility assistance. Key Research Areas : 1. Human-Robot Interaction for emotion-adaptive assistive devices. 2. Biomechanical Modeling of lower-limb assistance. 3. Ontological Frameworks for academic emotion analysis. 4. Non-Powered Exosuits for muscle fatigue reduction. His work integrates deep neural networks and physiological signal processing to create emotion-aware walking aids. Recent studies (2022-2020) demonstrate 24% fatigue delay and 16% walking distance improvement using RE-Gait® devices. Earlier projects include guide-dog robots and self-contained gear diagnostics . All publications employ 3D motion analysis , Wearable Sensors , and torque control algorithms .