جست‌وجوی استاد و پژوهشگر

Uchenna Daniel Aniمشاهده پروفایل

مدرس

• Cyber Security
• Industrial Control Systems (ICS)
• Internet of Things (IoT)
• +۶ مورد دیگر

Dr. Uchenna Daniel Ani is a Lecturer in Cyber Security at the School of Computer Science and Mathematics, Keele University. He leads the MSc Cyber Security programme and chairs the School Taught Programme Ethics Committee. Previously, he was a Senior Research Fellow at the PETRAS National Centre of Excellence for IoT Systems Cybersecurity at University College London (UCL), focusing on cybersecurity in critical infrastructure systems. Dr. Ani holds a PhD in Industrial Control System Cybersecurity from Cranfield University, UK, and degrees from the University of Bedfordshire. His research emphasizes socio-technical security analysis, cybersecurity risk assessment, and the intersection of technical solutions with human and policy factors. Key projects include 'Analytical Lenses for Internet of Things Threats' and 'Modelling for Socio-Technical Security,' collaborating with transport and water infrastructure organizations. His research interests span ICS/IoT Cybersecurity, security modelling/simulations, human-factor security, and digital forensics. He actively contributes to cybersecurity policy and standards development, advising on IoT-enabled infrastructure resilience. Dr. Ani is a Fellow of the Higher Education Academy and member of IET/ACM. Teaching includes modules on Human Factors of Cyber Security, Cryptography, and Cloud Computing. He advocates STEM education through mentoring and public engagement, including roles as a STEM Ambassador and IET Young Professional Ambassador.

Maria Moruzمشاهده پروفایل

پژوهشگر

• Romanian linguistics
• Philology
• Phraseology
• +۳ مورد دیگر

Maria Moruz serves as a Researcher at the Department of Social Sciences and Humanities, Alexandru Ioan Cuza University of Iasi, a position she has held since February 2009. Her academic profile centers on Romanian linguistic research with strong interdisciplinary connections to biblical studies and computational methods. She earned her PhD from Alexandru Ioan Cuza University of Iasi in December 2009 with a dissertation analyzing phraseological units in parallel bilingual corpora, establishing her foundational expertise in comparative linguistics. Maria Moruz's research program integrates traditional philological scholarship with modern computational techniques . Her primary domains include Romanian linguistics , phraseology , and computational linguistics , with significant contributions to Biblical philology through critical editions of historical texts. She examines national specificity in phraseological units while developing linguistic resources for Romanian language processing , bridging historical textual analysis with contemporary NLP applications. Her publication trajectory reveals distinct thematic phases: early computational linguistics work (2004-2012) on Romanian lexical resources and question-answering systems evolved into specialized biblical philology research (2014-present) within the Monumenta linguae Dacoromanorum project. Recent publications focus on Romanian lexicography and biblical marginalia, demonstrating sustained engagement with both digital humanities methodologies and historical textual criticism. Maria Moruz has secured significant research funding as Project Director for a CNCSIS TD grant and served as a POSDRU postdoctoral researcher. Her collaborative work includes membership in the international "Widespread Idioms in Europe and Beyond" project and leadership in multiple Romanian linguistics initiatives. Project Director: CNCSIS TD grant POSDRU Postdoctoral Researcher Collaborator: "Widespread Idioms in Europe and Beyond" project Co-organizer: International Symposium "Explorations in the Romanian and European Biblical Tradition" Founding Member: Romanian Association of Biblical Philology and Hermeneutics She maintains active scholarly infrastructure through editorial work on the Monumenta linguae Dacoromanorum series and organization of specialized symposia, fostering interdisciplinary dialogue between computational linguists, philologists, and biblical scholars.

Marco Magginiمشاهده پروفایل

استاد

• machine learning
• neural networks
• kernel machines
• +۶ مورد دیگر

Marco Maggini is a Full Professor in the Department of Information Engineering and Mathematics at the University of Siena, a position he has held since joining the university in 1996. His academic career spans over 25 years with foundational expertise in computer engineering and artificial intelligence, focusing on theoretical and applied machine learning research. His educational background includes: Laurea degree (cum laude) in Electronics Engineering from the University of Florence (1991) Ph.D. in Computer Engineering and Control Systems from the University of Florence (1995) Prof. Maggini's research encompasses machine learning, neural networks, kernel machines, and the integration of symbolic and sub-symbolic knowledge systems. He extends these foundations into practical applications including web mining, search engine technology, pattern recognition, natural language processing, and computer vision. This interdisciplinary approach bridges theoretical computer science with real-world implementation challenges across multiple domains. Analysis of his 15 most recent publications (2023-2025) reveals a dominant focus on multilingual NLP applications, particularly educational puzzle generation for low-resource languages (Italian, Arabic, Persian, Turkish) using LLMs. His work demonstrates consistent innovation in named entity recognition, commonsense reasoning evaluation, and cross-lingual adaptation techniques. Secondary research threads include medical imaging segmentation, molecular property prediction, and AI security vulnerabilities, reflecting his broad technical mastery across computer vision, bioinformatics, and adversarial machine learning. No specific scientific awards were mentioned in the provided documentation, though his editorial roles indicate peer recognition within the academic community. While student mentoring details are absent from the source material, his position as Full Professor and leadership of SAILab imply active graduate supervision. His extensive publication record (120+ papers) and editorial service suggest significant research grant involvement, though specific funding sources remain undocumented. He directs the Siena Artificial Intelligence Laboratory (SAILab), which serves as an interdisciplinary hub for advancing machine learning theory and applications. The lab's current projects emphasize educational technology, multilingual NLP systems, and the integration of symbolic reasoning with neural architectures, maintaining strong industry and international academic collaborations.

David Wagnerمشاهده پروفایل

استاد

• Computer Security
• Security for AI (Large Language Models)
• AI for Security
• +۷ مورد دیگر

David Wagner is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley's College of Engineering. He holds the Carl J. Penther Chair in Engineering and leads the Wagner Research Group, which focuses on computer security, AI security, and systems security. Education Ph.D., Computer Science, UC Berkeley (2000) M.S., Computer Science, UC Berkeley (1999) A.B., Mathematics, Princeton University (1995) Research Interests Wagner's work spans computer security, with a particular focus on security for AI systems (especially large language models) and security for wearable/smartphone devices . He has extensive experience in wireless security , sensor network security , applied cryptography , and software security , including electronic voting systems and program analysis for security. His research group develops tools like OpenCount for election auditing, AuditBear for voting machine analysis, and PrimeVul for vulnerability detection in code. Scientific Awards ACM SIGSAC Test of Time Award (2022) IEEE Symposium on Security and Privacy Test of Time Award (2020) USENIX Test of Time Award (2019) Google Faculty Research Award (2018) Internet Defense Prize (2017) ACM SIGSAC Outstanding Innovation Award (2016) IBM Pat Goldberg Memorial Best Paper Award (2008) UC Berkeley Distinguished Teaching Award (2006) Sloan Research Fellow (2003) NSF CAREER Award (2001) Advising & Grants Wagner has advised numerous graduate students including Sizhe Chen , Zhanhao Hu , and Dennis Jacob . His research has been supported by grants from NSF (CAREER, ITR), Microsoft, Intel, and the Okawa Foundation. Labs & Teams He co-directs the Berkeley Security Research Group , participates in the ACTION Institute , and leads the KACST-UCB Joint Center on Cybersecurity. His team develops open-source security tools and datasets like DiverseVul for vulnerability detection.

Vincent Wadeمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۸ مورد دیگر

Professor Vincent Wade is a prominent academic and co-founder of the ADAPT SFI Research Centre, holding the Professorial Chair of Computer Science (established 1990) and a Personal Chair in Artificial Intelligence at Trinity College Dublin's School of Computer Science and Statistics. He co-directs the DREAL Centre for Research Training and leads ADAPT, a globally recognized centre for digital media technology and AI research. His work spans intelligent systems, personalisation, machine learning, and ethical AI applications in healthcare and education. Research interests include AI-driven personalisation, multimodal interaction, knowledge graphs, and ethical considerations in digital technologies. He has published over 350 peer-reviewed papers, earned the prestigious Provost Innovation Award (2018), and holds patents in personalisation technologies. He co-founded EmpowerTheUser, a TCD spin-out focused on simulation-based learning analytics. Major Achievements: 2018 Provost Innovation Award (Trinity College Dublin) 2010 European Language Label Award Fellow of Trinity College Dublin Over 350 scientific publications Key Contributions: Developed the ADELE corpus for social conversation analysis Pioneered cross-site personalisation frameworks Advanced adaptive e-learning systems through platforms like Slicepedia and AMASE His research bridges technical innovation with societal impact, addressing challenges in healthcare, education, and digital ethics.

Janet C.E. Watsonمشاهده پروفایل

استاد

• Modern South Arabian languages
• Arabic dialects
• Phonology
• +۱۲ مورد دیگر

Professor Janet C.E. Watson is a leading scholar in Semitic linguistics at the University of Leeds, affiliated with the School of Languages, Cultures and Societies within the Faculty of Arts, Humanities and Cultures. She is the co-director of the Centre for Endangered Languages, Cultures and Ecosystems (CELCE) and leads major international projects on Modern South Arabian languages. Her work bridges linguistics, anthropology, and environmental studies. Her research focuses on the documentation and analysis of endangered languages in southern Arabia, particularly Mehri, Śḥerɛ̄t (Jibbali), Harsusi, and Bathari. She employs instrumental phonetics, acoustic analysis, and community-based methodologies to study phonology, morphology, and the relationship between language and nature. Her fieldwork spans Oman and Yemen, often in collaboration with local scholars and communities. The recent articles reflect a strong trend in laboratory phonology, language documentation, and computational approaches to under-resourced languages. Key themes include emphatic consonants, silent articulations, spatial language, and the integration of traditional ecological knowledge into linguistic analysis. Her work is increasingly interdisciplinary, connecting language with biodiversity, cultural heritage, and digital preservation. Fellow of the British Academy (2013) Leverhulme Trust Research Fellowships (2007–2008, 2010–2011, 2019–2021) British Academy Small Research Grant British Council International Research Fellowship (host, 2023) Professor Watson has supervised numerous PhD students working on Arabic dialects, Mehri, and language revitalization. Her grants include major funding from the Leverhulme Trust, British Academy, AHRC, and King Faisal Centre. She collaborates with institutions in the UK, Oman, Yemen, USA, and Europe. She founded the Language@Leeds Leadership Chair and co-founded CELCE with Prof. Jon Lovett. She leads multimodal documentation projects, including the creation of an Arabic-based script for unwritten languages, children’s e-books in Mehri, and digital archives at ELAR (SOAS). Her team includes local researchers, PhD students, and international collaborators, emphasizing community engagement and capacity building.

Damon L. Woodardمشاهده پروفایل

استاد

• Artificial Intelligence
• Hardware Security
• Biometrics
• +۵ مورد دیگر

Damon L. Woodard is a Professor in the Department of Electrical and Computer Engineering at the University of Florida (UF) and serves as Director of the Florida Institute for National Security (FINS) and the Applied Artificial Intelligence (AAI) Group. His research focuses on applied artificial intelligence, hardware security, and biometrics, with particular emphasis on adversarial AI, AI-enabled hardware assurance, and explainable AI (XAI). He holds IEEE and ACM Senior Member status and is a Kavli Frontiers Fellow. Education: Ph.D. in Computer Science and Engineering, University of Notre Dame M.E. in Computer Science and Engineering, Penn State University B.S. in Computer Science and Computer Information Systems, Tulane University Research Interests: Dr. Woodard explores cutting-edge areas such as AI hardware acceleration, multi-modal AI systems, and counter-AI strategies. His work bridges cognitive science and technology through projects like text stylometry and psychological analysis frameworks. Key focus areas include semiconductor reverse engineering, hardware trojan detection via SEM imaging and machine learning, and secure IoT biometric systems. Highlighted Awards: National Academy of Science Kavli Frontiers Fellow IEEE Senior Member ACM Senior Member AAAI Membership Leadership & Contributions: As FINS Director, he oversees national security initiatives integrating AI and hardware assurance. His AAI Group develops resource-efficient AI solutions for constrained environments. Notable projects include the SECURE segmentation metric for IC reverse engineering and the MaGNIFIES GAN framework for electronic system inspection. Labs & Teams: Leads the Applied Artificial Intelligence Group and collaborates across disciplines through FINS, fostering innovation in AI-driven security and semiconductor integrity.

Tuyen (Robert) Leمشاهده پروفایل

دانشیار

• Digital Project Delivery
• Big Data in Construction Management
• Civil Infrastructure Management
• +۱۱ مورد دیگر

Dr. Tuyen (Robert) Le is an Associate Professor in the Glenn Department of Civil Engineering at Clemson University, South Carolina. He leads the Human-centered Construction Informatics Group, investigating digital and automation technologies across the architecture, engineering, construction, and facility-management (AEC/FM) sectors. Education B.S., Civil Engineering – Ho Chi Minh City University of Technology (2011) M.S., Construction Engineering and Management – Ho Chi Minh City University of Technology (2014) Ph.D., Construction Engineering and Management – Iowa State University (2017) Research Interests Dr. Le’s scholarship converges on digital project delivery and big-data analytics in construction management. His work leverages Building Information Modeling (BIM) , Civil Integrated Management (CIM) , and AI-driven methodologies such as machine learning and natural-language processing to optimize life-cycle performance of transportation and civil infrastructure systems. Additional foci include schedule/cost analytics, human–AI collaboration, and socio-economic implications of technology adoption in the future-of-work landscape for engineers and construction workers. Publication Trends Between 2016 and 2020 Dr. Le published extensively on computational techniques that transform raw construction and transportation data into actionable intelligence, emphasizing data modeling, visualization, semantic classification, and life-cycle integration for asset management. Professional Memberships Construction Research Council (CRC) American Society of Civil Engineers (ASCE) Advising & Graduate Opportunities Dr. Le’s research group is actively recruiting motivated Ph.D. students. Successful applicants receive full graduate assistantships covering tuition plus monthly stipends for up to four years. Selection prioritizes academic excellence (GPA, GRE, English proficiency) and demonstrated programming or research experience. Laboratory & Team He directs the Human-centered Construction Informatics Group , a multidisciplinary lab housed in 202C Lowry Hall that collaborates with industry and government to advance digital transformation in the built environment.

• Machine Learning
• Business Analytics
• Natural Language Processing
• +۴ مورد دیگر

Subhra Patra is Clinical Assistant Professor in Information Systems at UT Arlington. PhD in Computer Science from Homi Bhabha National Institute (2013) with thesis on computational intelligence for nuclear reactors. Applies machine learning to diverse domains including sentiment analysis, economic forecasting, and environmental modeling. Educational background: Ph.D. Computer Science, Homi Bhabha National Institute (2013) M.S. Electronic Science, Berhampur University (2006) M.S. Physics, Khallikote Unitary University (2004) Research spans business analytics applications and computational methods, including NLP for fake news detection, time series forecasting, and neural network architectures. Recent work focuses on operationalizing analytics in business contexts. Teaching responsibilities include Python programming, database systems, and data visualization. Previously held positions at VIT Chennai and KL University.

Qi Zhangمشاهده پروفایل

استادیار

• Artificial Intelligence
• Reinforcement Learning
• Trustworthy AI Systems
• +۴ مورد دیگر

Qi Zhang is an Assistant Professor in the Department of Computer Science and Engineering, AI Institute at the Molinaroli College of Engineering and Computing, University of South Carolina. His research focuses on developing safe, reliable, and trustworthy AI systems through advancements in reinforcement learning and decision-making algorithms for uncertain environments. He holds a Ph.D. from the University of Michigan (2020) and a B.E. from Shanghai Jiao Tong University (2015). Research interests include artificial intelligence, reinforcement learning, multi-agent systems, and decision-making under uncertainty. Key themes involve leveraging domain knowledge for robust AI solutions and ensuring ethical, transparent, and risk-aware system designs. His work spans applications in autonomous systems, healthcare, robotics, and materials science. Current projects emphasize improving algorithmic trustworthiness, safety, and adaptability across diverse contexts. He is affiliated with the AI Institute at USC and maintains an active research lab focused on these areas.

Oshani Seneviratneمشاهده پروفایل

استادیار

• Decentralized Systems
• Blockchain Technology
• Health Informatics
• +۵ مورد دیگر

Oshani Seneviratne is an Assistant Professor of Computer Science at Rensselaer Polytechnic Institute (RPI), leading the BRAINS Lab. She holds a Ph.D. and S.M. from MIT (Computer Science) and a B.Sc. (Hons) from the University of Moratuwa, Sri Lanka. Her research focuses on decentralized systems, blockchain, health informatics, and federated learning. She previously directed RPI's Health Data Research division. Education Ph.D. in Computer Science, MIT S.M. in Computer Science, MIT B.Sc. (Hons) in Computer Science and Engineering, University of Moratuwa Research Interests Her work bridges decentralized technologies with clinical and financial applications. Key areas include blockchain-based frameworks for federated learning, explainable AI in healthcare, and semantic web technologies for data interoperability. She emphasizes ethical AI, data provenance, and scalable systems for real-world challenges. Recent Work Trends Recent publications highlight advancements in smart contract auditing, LLM applications in financial systems, and blockchain-enhanced data provenance. Her work often combines technical innovation with societal impact, such as improving health data sharing and combating misinformation. Awards & Grants No awards explicitly listed, but her research has been supported by grants related to blockchain, health informatics, and decentralized systems. Advising & Labs Leads the BRAINS Lab, focusing on resilient, intelligent networked systems. Collaborates on projects like the Punya platform for clinical apps and BlockIoT for health data integration. Future Work Expanding into AI explainability for clinical decision support, decentralized mental health monitoring, and blockchain interoperability solutions.

Kylie L. Anglinمشاهده پروفایل

استادیار

• Educational Policy
• Data Science
• Natural Language Processing
• +۳ مورد دیگر

Kylie L. Anglin is an Assistant Professor in the Department of Educational Psychology at the University of Connecticut, specializing in Research Methods, Measurement, and Evaluation (RMME). She holds a Ph.D. in Education Policy from the University of Virginia (2021), an MPP in Leadership and Public Policy (2018), and a BA in Political Science (2013) from Southwestern University. Her research focuses on developing natural language processing (NLP) techniques to monitor program implementation in impact evaluations, enhancing causal validity and replicability in education research. Dr. Anglin teaches graduate courses in research methods, data science, and text analytics. Her work has been published in journals such as the Journal of Research on Educational Effectiveness , Prevention Science , and AERA Open . She has received the NAEd/Spencer Dissertation Fellowship and participated in the IES Pre-doctoral Training Program. Her research emphasizes scalable methods for analyzing policy variation, improving intervention adherence, and leveraging large language models for education evaluation. She actively mentors students interested in education policy or data science, and her contact details are available at kylie.anglin@uconn.edu .

• Emotional Communication
• Linguistics
• Cognitive Science
• +۵ مورد دیگر

Dr. Martijn Goudbeek is an Associate Professor at Tilburg University's Tilburg School of Humanities and Digital Sciences (TSHD), specifically within the Department of Communication and Cognition. His research focuses on the intersection of emotion, language, and cross-cultural communication, with a strong emphasis on vocal and linguistic expression of affect. He has contributed significantly to understanding how emotional states influence language production and perception, particularly across cultural and linguistic boundaries. His work spans experimental psychology, computational linguistics, and human-robot interaction. He is affiliated with the Communication and Cognition department and teaches courses like 'The Emotional Brain' and 'Statistics and Experimental Methods.' Key research themes include vocal emotion recognition in multilingual contexts, the role of rhythm and acoustic cues in affective communication, and the reproducibility of language evaluation methods. He has led projects such as the Multilingual Emotional Football Corpus (MEmoFC) and explored how cultural factors shape nonverbal expressions like smiles and gestures. His studies often combine empirical experiments with computational modeling, addressing topics ranging from politeness in mood-influenced communication to the design of socially intelligent chatbots and robots. Dr. Goudbeek’s interdisciplinary approach bridges cognitive science, linguistics, and digital technologies. While no specific grants or awards are listed, his extensive publication record reflects sustained contributions to understanding human emotion expression and its technological applications. His work frequently engages with questions of reproducibility in NLP and dialogue systems, emphasizing methodological rigor in computational linguistics.

Chuan Yueمشاهده پروفایل

استاد

• Cybersecurity
• Web Security
• Mobile Security
• +۷ مورد دیگر

Chuan Yue is a Professor of Computer Science at the Colorado School of Mines (Mines), leading research in Cybersecurity with a focus on Web, Mobile, Cloud, CPS/IoT, and AI systems security. He founded the Center for Cyber Security and Privacy (CCSP) at Mines and serves as its point of contact. His research emphasizes usable security, privacy, vulnerability analysis, and cybersecurity education. Education: B.E. and M.E. in Computer Science from Xidian University (China, 1996/1999), Ph.D. in Computer Science from College of William and Mary (2010). Pre-Mines career: Bell Labs (1999-2003) and University of Colorado Colorado Springs (UCCS, 2003-2013). Awards include the Daniels Fund Faculty Fellowship (2016-2019) and an Outstanding Paper Award at CODASPY 2018. Research interests span security/privacy in web-based systems, human-computer interaction, and distributed computing. His work is funded by NSF, DOD, and Meta. Key contributions include PolicyChecker for GDPR compliance analysis, WtaGraph for web tracking detection, and studies on smart home privacy negotiation. Over 50 peer-reviewed publications in top venues like IEEE S&P, CCS, and CHI. Advised numerous PhD, Master’s, and undergraduate researchers, emphasizing interdisciplinary collaboration with industry/government. Developed security tools like LoginInspector (best paper at LISA 2012) and SafeSky cloud middleware.

• Artificial Intelligence
• Geospatial Data Science
• Knowledge Graphs
• +۵ مورد دیگر

Professor Manolis Koubarakis is a faculty member at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on geospatial data science, knowledge graphs, entity resolution, and AI applications in Earth observation. He leads projects like ExtremeEarth and Plato, advancing semantic data cube systems and geospatial question answering engines. His work bridges AI and geospatial technologies, with contributions to frameworks like pyJedAI and Strabo 2 for managing big geospatial data. Research Interests include: Geospatial Question Answering Systems Entity Resolution and Entity Linking Ontology-Based Data Access (OBDA) Knowledge Graph Construction and Applications Earth Observation Data Analytics AI for Geoinformatics Notable Projects: ExtremeEarth: Combines Copernicus satellite data with machine learning for environmental analytics. Plato: Semantic data cube system enabling advanced querying of multidimensional datasets. GeoQA2: A geospatial question answering engine evaluated on large benchmarks. JedAI Family: Tools for scalable entity resolution in structured/semi-structured data. His publications span 20+ years, with recent emphasis on: AI-driven Earth observation systems Geospatial RDF benchmarking 3D geospatial interlinking Large language models for legal and health content delivery