جست‌وجوی استاد و پژوهشگر

Nicola Capuanoمشاهده پروفایل

دانشیار

• Machine Learning
• Natural Language Processing
• Artificial Intelligence for Education
• +۳ مورد دیگر

Nicola Capuano is an Associate Professor at the Department of Information and Electrical Engineering and Applied Mathematics (DIEM) of the University of Salerno, Italy. He is a member of the SmartLearn research group at the Open University of Catalonia and has previously held academic roles at the University of Basilicata and technical positions at the University of Salerno. Current positions: Associate Professor (University of Salerno) since 2023 Former Associate Professor (University of Basilicata, 2022-2023) Former Researcher (University of Basilicata, 2019-2022) His research focuses on machine learning applications in education, including Artificial Intelligence for Education , Natural Language Processing , and Fuzzy Systems . He has pioneered zero-shot vulnerability detection using LLMs and developed novel graph-based approaches for misinformation analysis. Key projects include the ALICE adaptive learning system and SmartLearn research initiatives. Scientific contributions span 15+ peer-reviewed publications in IEEE, Springer, and Elsevier outlets. Recent work examines persuasive comment detection in social media and optimization techniques in fuzzy genetic algorithms. Best Paper Award recipient (2017) 2nd Best Paper Award (2008) Editorial roles: Associate Editor for 3 journals since 2019 Active in academic service, he chairs conference tracks (INCoS, AINA) and serves as independent evaluator for Horizon Europe projects. His teaching portfolio includes Software Engineering, Algorithms, and AI applications.

Damian Borthمشاهده پروفایل

استاد

• Digitalization & Transformation
• Machine Learning
• Remote Sensing
• +۵ مورد دیگر

Prof. Dr. Damian Borth is a faculty member and Academic Director of the Doctoral Program for Computer Science at the University St.Gallen , affiliated with the School of Computer Science and the Institute of Computer Science (ICS-HSG) . His research spans Machine Learning , Remote Sensing , and Digitalization & Transformation , with a focus on diffusion models, vision transformers, and environmental data analysis. Recent publications highlight advancements in anomaly detection , cross-modal translation , and climate monitoring using AI. Key themes include weight space learning , federated learning , and data-efficient AI for Earth observation. His work bridges theoretical deep learning and practical applications in financial auditing, pollution estimation, and satellite imagery.

• Adult Education
• Digital Education
• Educational Technology
• +۵ مورد دیگر

Susanne Witt is a Research Associate at the German Institute for Adult Education (DIE), a member of the Leibniz Association. She serves as a Specialist Assistant for the Portals Team in knowledge transfer and works within Research Infrastructures. Her professional contact information includes telephone (+49 228 3294-170), fax (+49 228 3294-399), and email (witt@die-bonn.de), with an ORCID identifier (0009-0000-4155-6927). Her career path includes diverse experiences as a graduate sports teacher (Ruhr University Bochum), French Business Correspondent (ILS Hamburg), Human Resources Specialist (IHK Bonn), and journalist (FJS Berlin). Witt's research interests focus on digital transformation in adult education, with particular expertise in wb-web (a portal for continuing education professionals), EPALE (Electronic Platform for Adult Learning in Europe), Qualidat (research map), library architecture, and online program scheduling. Her work increasingly addresses artificial intelligence applications in education, digital accessibility, and sustainable educational practices. She explores how emerging technologies like ChatGPT and AI tools can be effectively integrated into educational settings while maintaining critical perspectives on their implementation. Her publication portfolio reveals a clear trend toward digital education innovations, with recent work examining AI implementation requirements, prompting techniques, digital accessibility, and the implications of the EU AI Act for educational institutions. These publications demonstrate her evolving focus from foundational digital education topics to cutting-edge AI applications, while maintaining consistent attention to practical implementation challenges and accessibility considerations. Witt actively contributes to editorial work as part of the wb-web and EPALE teams, serving as an EPALE Ambassador. She has moderated and participated in numerous podcasts and discussion formats, particularly the potenziaLLL series, focusing on practical applications of educational theory. Her work often involves thematic dossier curation on critical topics like media literacy, digital teaching methods, and collaborative learning approaches. She has developed significant expertise in digital teaching methodologies, including Barcamps, Design Thinking, Scrum for agile instruction, and technical solutions for hybrid teaching environments. Her research also encompasses critical media literacy, cultural education, health literacy, and food literacy within adult education contexts, demonstrating a comprehensive approach to contemporary educational challenges.

• Natural Language Processing
• Legal Informatics
• Greek Language Processing
• +۴ مورد دیگر

Ion Androutsopoulos is a Professor in the Department of Informatics at Athens University of Economics and Business (AUEB), where he leads the AUEB NLP Group. With over 180 publications spanning three decades, he is a prominent figure in Natural Language Processing research, particularly known for his work bridging NLP with legal informatics, Greek language processing, and biomedical applications. His research interests focus on several interconnected areas of Natural Language Processing: Legal Informatics : developing NLP systems for legal document analysis, legal judgment prediction, and legal reasoning, with recent work including GreekBarBench and Archimedes-AUEB systems Greek Language Technology : creating specialized tools for Modern Greek processing, including GR-NLP-TOOLKIT and Greeklish transliteration systems Biomedical Text Mining : working on diagnostic captioning and medical image analysis through participation in ImageCLEFmedical challenges Financial NLP : developing systems like EDGAR-CRAWLER for financial document analysis and XBRL tagging His recent publications (2023-2025) show an increasing focus on Greek-specific NLP resources and practical applications of large language models in legal reasoning. His work often combines theoretical NLP advances with practical implementations, particularly through his leadership of the AUEB NLP Group which regularly participates in international evaluation campaigns. Professor Androutsopoulos has supervised numerous PhD students who have become active researchers in their own right, including John Pavlopoulos, Prodromos Malakasiotis, and Ilias Chalkidis. His collaborative network spans multiple institutions and disciplines, reflecting the interdisciplinary nature of modern NLP research.

Yuning Dingمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Educational Technology
• Automatic Essay Scoring
• +۳ مورد دیگر

Yuning Ding is a PhD Student and Research Assistant in the junior research group 'EduNLP' at the Research Center CATALPA (Center of Advanced Technology for Assisted Learning and Predictive Analytics), FernUniversität in Hagen, since January 2022. Her work focuses on Natural Language Processing applications for educational technology, specifically developing systems for automatic essay scoring and generating formative feedback for learners and summative feedback for teachers. Her educational background includes: M.Sc. in Applied Cognitive and Media Science with Specialization in Cognition & Artificial Intelligence at University of Duisburg-Essen (2017-2019) B.Sc. in Applied Cognitive and Media Science at University of Duisburg-Essen (2014-2017) B.A. in Communications at University of International Relations, Beijing (2009-2013) Ding's research centers on leveraging NLP to enhance writing education through AI-driven assessment and feedback systems. Her work bridges computational linguistics and pedagogy, with particular emphasis on argument mining, cohesion analysis, and cross-lingual content scoring. She investigates how transformer models and multi-task learning can improve the reliability and educational value of automated writing evaluation, while addressing critical issues like fairness and adversarial vulnerability in scoring systems. Her research demonstrates how NLP can provide actionable insights for both students and educators in writing development. Analysis of her publication trends reveals a strategic progression from foundational work on content scoring and error analysis toward sophisticated integrated systems. Recent work emphasizes multimodal feedback generation, argument-cohesion integration, and cross-lingual transfer, with increasing focus on real-world implementation challenges including fairness, robustness, and user experience. Her research spans multiple languages and educational contexts, reflecting a commitment to globally applicable educational technology. Within CATALPA, Ding actively collaborates across disciplines through the center's vibrant knowledge-sharing culture. She participates in project presentations and colloquia that facilitate cross-pollination of ideas between computer science, linguistics, and educational theory. Her work on the DARIUS corpus and FEAT-writing system demonstrates tangible contributions to educational resource development and interactive learning environments.

Mascha Kurpicz-Brikiمشاهده پروفایل

استاد

• Applied Natural Language Processing
• Fairness and Diversity in AI
• Augmented Intelligence for Mental Health
• +۲ مورد دیگر

Prof. Dr. Mascha Kurpicz-Briki is a computer science professor at the Bern University of Applied Sciences, leading the Applied Machine Intelligence research group within the Institute for Data Applications and Security (IDAS). Her work focuses on human-centered applications of natural language processing in mental health and societal challenges, particularly addressing bias mitigation in AI systems. Education: PhD in energy-efficient cloud computing from University of Neuchâtel Expertise: Applied NLP, fairness in AI, augmented intelligence for health Leadership: Deputy lead of Applied Machine Intelligence Research Group Her research emphasizes augmented intelligence - creating AI systems that support rather than replace humans. Current projects investigate NLP applications for: Burnout and depression detection in clinical psychology Fairness measurement in word embeddings and language models Human augmentation through AI in industrial and healthcare settings Recent publications highlight her contributions to: Bias detection frameworks for European languages Machine learning in eating disorder diagnostics Generative AI integration in art therapy She maintains active memberships in IEEE, ACM, ACL, and the Swiss Center for Augmented Intelligence, with expertise in German, English, and French language technologies.

• Artificial Intelligence
• Cybersecurity
• Security of AI
• +۴ مورد دیگر

Isabel Cecília Correia da Silva Praça Gomes Pereira is a Coordinator Professor at the School of Engineering of the Polytechnic Institute of Porto (ISEP), where she serves as Director of the Master on Informatics Engineering and Advisor of ISEP Presidency for R&D. She is also a Senior Researcher at GECAD (Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development), a research unit ranked as Excellent by the Portuguese Science & Technology Foundation. Dr. Praça holds a PhD in Electrical and Computer Engineering - Industrial Informatics from the University of Trás-os-Montes e Alto Douro, and completed her post-doctoral studies in Artificial Intelligence - Multi-Agent Systems with support from the Portuguese National Science Foundation (SFRH/BPD/30111/2006). Her academic journey includes progressive appointments from Assistant to Adjunct Professor and finally to Coordinator Professor at ISEP. Her research focuses on Artificial Intelligence applied to cybersecurity and security of AI , with significant contributions to applying AI in various domains including cybersecurity (projects like AIDA, SAFE, VESTA), industry (SeCoIIA, Cyberfactory), and energy systems (SPET, MAS-Society). She leads a research team at GECAD working on these topics and has strong connections with over 100 companies and technology transfer centers across more than 30 countries. Analysis of her recent publications reveals a strong trend toward AI security, with particular emphasis on adversarial attacks against AI systems, secure implementation of AI in critical domains, and privacy-preserving AI techniques. Her work spans both theoretical foundations and practical applications across multiple sectors including energy, healthcare, and network security, demonstrating her ability to bridge academic research with real-world applications. Dr. Praça has been recognized as an expert by several prestigious organizations including the European Union Agency for Cybersecurity (ENISA), where she contributes to working groups on Security of AI and the European Cybersecurity Skills Framework. She also serves as an expert for NATO's Defence Innovation Accelerator for the North Atlantic (DIANA) and represents ISEP in the European Cybersecurity Organization (ECSO). As an educator, she teaches Machine Learning and Multi-agent Systems in the MSc in AI program, and Security of Communications and Infrastructures in the Cybersecurity branch of the MSc in Informatics. She currently supervises 4 PhD students in AI security and privacy and has guided 45 Master's theses, demonstrating her commitment to developing the next generation of researchers and practitioners in her field. Her research is supported by numerous international and national grants, including multiple Horizon Europe and Horizon 2020 projects where she serves as Principal Investigator or Co-PI. She has participated in over 35 R&D projects totaling significant funding, with a strong track record of translating research into practical applications through industry partnerships.

• Information Systems
• Modeling and Simulation
• Artificial Intelligence
• +۳ مورد دیگر

Dr. Erke Arıbaş is a Lecturer at Istanbul Technical University's Faculty of Computer and Informatics , specializing in the Department of Computer Engineering . His research spans interdisciplinary domains including artificial intelligence, simulation modeling, and biophysics applications. Education: PhD in Computational Science and Engineering (2001-2013), Istanbul Technical University MA in Information Systems Design and Management (2001), Istanbul Technical University (Evening Education) BS in Physics (1992-1996), Istanbul Technical University BS in Physics (1996-2000), University of Missouri-Rolla His research focuses on generative AI applications , autonomous systems , and multi-phase flow simulations with thermal modeling. He has contributed to fields ranging from smart city cybersecurity to biomechanical modeling of blood flow. Article trends show expertise in AI-personality modeling integration , unmanned aerial vehicle design , and biofluid dynamics with specialized focus on red blood cell aggregation and arterial hemodynamics.

Philippe Giguèreمشاهده پروفایل

دانشیار

• Mobile Robotics
• Deep Learning
• Computer Vision
• +۴ مورد دیگر

Philippe Giguère is an Associate Professor at the Department of Computer Science and Software Engineering, Faculty of Science and Engineering, Laval University. His research focuses on mobile robotics , sensor fusion , and deep learning for autonomous systems in challenging environments (forests, underwater, harsh weather). He leads projects in 3D localization, terrain identification, and robotic perception. Labs : Norlab, DAMAS Affiliations : Centre de recherche en robotique, vision et intelligence machine (CerVIM), Institut Intelligence et Données (IID), CRDM (Big Data Center) His teaching includes courses on deep learning and mobile robotics . Publications cover SLAM , sensor calibration , and autonomous navigation . He works with MATLAB, Python, and ROS frameworks.

Wei Wangمشاهده پروفایل

استاد

• Big Data Analytics
• Machine Learning
• Data Mining
• +۵ مورد دیگر

Wei Wang is the Leonard Kleinrock Chair Professor in Computer Science and Computational Medicine at University of California, Los Angeles (UCLA) , and the founding Director of the Scalable Analytics Institute (ScAI) . She is also a core faculty member of the UCLA Jonsson Comprehensive Cancer Center, Institute for Quantitative and Computational Biology, and Bioinformatics Interdepartmental Graduate Program. Education: Ph.D. in Computer Science, UCLA (1999) M.S. in Systems Science and Industrial Engineering, SUNY at Binghamton (1995) Research Interests: Dr. Wang’s research spans big data analytics , machine learning , data mining , natural language processing , bioinformatics , computational biology , and AI for science . Her work focuses on designing scalable algorithms for complex pattern discovery in large-scale, heterogeneous data, with applications in medicine, genomics, and scientific discovery. Scientific Awards & Honors: ACM Fellow (2020) IEEE Fellow (2022) NSF CAREER Award (2005) Microsoft Research New Faculty Fellow (2005) Phillip and Ruth Hettleman Prize (2007) Okawa Foundation Research Award (2013) ACM SIGKDD Service Award (2016) IEEE ICDM Outstanding Service Award (2012) IBM Invention Achievement Awards (2000, 2001) Multiple Best Paper Awards at SIGKDD, ICDE, and ACM BCB Advising & Research Team: Dr. Wang currently advises 15 PhD students and 1 postdoctoral fellow . Her lab focuses on AI-driven scientific discovery, scalable analytics, and interdisciplinary applications in biomedicine and materials science. Labs & Institutes: Director, Scalable Analytics Institute (ScAI) , UCLA Member, UCLA Jonsson Comprehensive Cancer Center Member, Institute for Quantitative and Computational Biology Member, Bioinformatics Interdepartmental Graduate Program

Yanqi Suمشاهده پروفایل

پژوهشگر ارشد

• Software Engineering
• Artificial Intelligence
• Automated Testing
• +۳ مورد دیگر

Yanqi Su is a postdoctoral researcher at the TUM School of Computation, Information and Technology (CIT) at the Technical University of Munich, affiliated with the Chair of Software Engineering & AI . She will soon complete her Doctorate at The Australian National University under Prof. Zhenchang Xing, following academic training at Nanjing University of Aeronautics and Astronautics. Education : PhD (in progress, ANU), Master’s/Bachelor’s in Computer Science and Technology (Nanjing University of Aeronautics and Astronautics) Research Focus : Her work centers on enhancing exploratory testing through Knowledge Graphs and Large Language Models (LLMs) , with notable contributions to test scenario generation , automated exploratory testing , and bug-component triaging . She has discovered ~300 bugs in applications like Firefox (desktop/Android), many resolved in collaboration with developers. Publication Trends : Her research spans LLM applications for GUI/code analysis , automated security testing , and AI ethics . Key subfields include model context protocols , vulnerability detection , code optimization , and human-AI collaboration in software development. Scientific Recognition : Recipient of the Distinguished Paper Award at ASE 2021 , her work appears in top-tier venues (ICSE, ASE, TSE, TOSEM).

• Applied Electromagnetics
• Antennas and Propagation
• Microwave Imaging
• +۳ مورد دیگر

David Orlando Rodriguez Duarte is a Fixed-term Assistant Professor at the Department of Electronics and Telecommunications (DET) at Polytechnic University of Turin (Politecnico di Torino), Italy. He is a member of the Interdepartmental Center PolitoBIOMed Lab - Biomedical Engineering Lab and actively contributes to the applied electromagnetics research group. His academic work bridges electromagnetic theory with practical medical applications, particularly in developing innovative imaging technologies for healthcare. Dr. Rodriguez Duarte is completing his Ph.D. degree with the Department of Electronics and Telecommunications at Politecnico di Torino while holding a prestigious Marie Sklodowska-Curie Fellowship. He is deeply involved in the EMERALD project, which focuses on modeling and designing microwave imaging systems for cerebrovascular diseases. The department's research group has over 10 years of experience advancing both theoretical and applied electromagnetism, with significant contributions in electromagnetic theory, wave propagation, and applications in communication systems and radar technology. His research spans multiple interconnected domains in applied electromagnetics. He specializes in antenna design specifically tailored for medical applications, with particular expertise in microwave imaging systems for neurological conditions. His work in electromagnetic field theory focuses on biomedical contexts, especially stroke monitoring and detection. He develops practical implementations that bridge theoretical concepts with clinical applications, addressing critical healthcare challenges. His research directly supports SDG Goal 3: Good health and well-being through the development of accessible diagnostic technologies. Dr. Rodriguez Duarte's scholarly output demonstrates a clear progression toward developing practical, portable microwave imaging solutions using off-the-shelf components. His recent work increasingly integrates machine learning techniques with traditional microwave sensing approaches, enhancing diagnostic accuracy for neurological conditions. There's a strong emphasis on creating real-time imaging solutions that can be deployed at the bedside for immediate patient care, particularly for time-sensitive conditions like stroke. Marie Sklodowska-Curie Fellowship for research on microwave imaging systems for cerebrovascular diseases Dr. Rodriguez Duarte serves as primary supervisor for two doctoral candidates: Alex Ramiro Masaquiza Caiza (40th cycle, 2024-present) and Martina Gugliermino (39th cycle, 2023-ongoing). Their research focuses on 'EM field study in medicine: characterization of materials for phantoms and stroke monitoring algorithms.' He has secured research funding through the EMERALD European project (2018-2021) and continues to develop grant-supported work in biomedical microwave imaging. His ERC sector alignments include PE7_6 (Communication technology), PE7_11 (Medical applications), and PE7_3 (Simulation engineering). He is an integral member of the PolitoBIOMed Lab - Biomedical Engineering Lab, where his team develops microwave imaging technologies for brain stroke monitoring. The lab focuses on creating practical implementations of electromagnetic theory for medical diagnostics, with emphasis on point-of-care applications. Their work addresses a critical healthcare need as stroke affects approximately one in six people worldwide and requires prompt diagnosis for effective treatment, making their research vital for improving patient outcomes through early detection technologies.

Davor Runjeمشاهده پروفایل

مدرس

• Artificial Intelligence
• Theoretical Computer Science
• Software Engineering
• +۴ مورد دیگر

Davor Runje is a lecturer at Algebra University with extensive industry experience as a software engineer, computer scientist, and serial entrepreneur. He has co-founded multiple technology ventures including AIRT (an AI startup), DRAP (a digital agency acquired by Imago Ogilvy in 2018), and PlayMedia Systems (1997), which became a global leader in AMP MP3 playback technology. His research interests span artificial intelligence, theoretical computer science, parallel and distributed computing, and cryptography. Runje has made significant contributions to programming for multiprocessor/multicore systems, with work that later became the Task Parallel Library in the .NET framework during his time at Microsoft Research. His publication portfolio shows a clear evolution from theoretical computer science and concurrency research (2003-2009) toward machine learning and AI (2019-2025), with particular focus on neural networks, model interpretability, and security aspects of large language models. His recent work demonstrates expertise in constrained monotonic neural networks, attention mechanisms for tabular time-series, and vulnerabilities in large language models. His notable achievements include: Microsoft Research SSCLI and Phoenix 2005 awards Two US patents 20 publications in theoretical computer science and artificial intelligence Chairing the Croatian Independent Software Exporters board (2020-2024) As an active industry leader, Runje has participated in numerous legal and tax reform initiatives aimed at increasing the competitiveness of the Croatian IT sector in global markets, representing approximately one-third of the Croatian IT industry through his leadership role.

Klaus Muellerمشاهده پروفایل

استاد

• Visual Analytics
• Explainable Machine Learning and AI
• Algorithmic Fairness and Transparency
• +۷ مورد دیگر

Klaus Mueller is a Professor in the Computer Science Department at Stony Brook University , with additional appointments in Biomedical Engineering and Radiology. He serves as Director of the Visual Analytics and Imaging (VAI) Lab, Liaison for the SUNY Korea CS Program, and Interim Chair of the Department of Technology and Society . His career spans roles at Brookhaven National Lab and leadership positions at SUNY Korea. Dr. Mueller earned his PhD in Computer and Information Science (1998), MS in Computer and Information Science (1996), and MS in Biomedical Engineering (1990) from The Ohio State University , alongside a BS in Electrical Engineering (1987) from the Polytechnic University of Ulm, Germany. His research focuses on visual analytics , explainable AI , algorithmic fairness , computational imaging , and medical imaging . He has pioneered GPU-accelerated CT reconstruction techniques, bias mitigation frameworks (e.g., D-BIAS), and tools like DOMINO for causal reasoning. His work bridges data science , human-computer interaction , and medical applications , often integrating large language models for visualization tasks. Recent publications highlight advances in multivariate volume rendering , LLM-driven bias detection , and mDDPM-based medical image synthesis . His articles span IEEE Transactions , Nature Machine Intelligence , and conferences like IEEE VIS and ACM CHI . Award highlights include NSF CAREER (2000), SUNY Chancellor Award (2011), IEEE Golden Core Award (2016, 2022), induction into the National Academy of Inventors (2018), and elevation to IEEE Fellow (2024). He has chaired major conferences and served as Editor-in-Chief of IEEE Transactions on Visualization and Computer Graphics (2019-2022). He teaches graduate and undergraduate courses in visualization , medical imaging , and GPGPU programming , and leads the Visual Analytics Seminar (CSE 648). His lab ( VAI Lab ) fosters interdisciplinary research in GPU-accelerated analytics and ethical AI.

Melike Erol Kantarciمشاهده پروفایل

دانشیار

• 5G and 6G Networks
• Artificial Intelligence (AI)
• Tactile Internet
• +۹ مورد دیگر

Dr. Melike Erol-Kantarci is an Associate Professor at the School of Electrical Engineering and Computer Science, University of Ottawa, and a Canada Research Chair in AI-enabled Next-Generation Wireless Networks. She founded the Networked Systems and Communications Research (NETCORE) Laboratory and holds a courtesy appointment as Assistant Professor at Clarkson University's Electrical and Computer Engineering Department. With over 6,000 citations and an h-index of 40, she contributes to IEEE as a Senior Member, chairs the Green Smart Grid Communications special interest group, and serves as Editor for IEEE Communications Letters and IEEE Access . Research Focus: 5G/6G wireless networks AI/ML-driven network optimization Smart grid communications Cyber-physical system security Edge computing and IoT Reconfigurable Intelligent Surfaces (RIS) Scientific Contributions: Her recent publications highlight generative AI integration in 6G, intent-driven network management using hierarchical reinforcement learning, physical layer security for connected vehicles, and explainable AI frameworks in communications. The 15 most recent works (2024-2025) span topics like beamforming optimization, federated learning security, UAV-assisted networks, and semantic communication systems. Leadership: As director of the NETCORE Laboratory, she leads cutting-edge research in networked systems, bridging wireless communication paradigms with energy sustainability and security requirements for next-generation networks.