جستجوی استاد راهنمای دانشگاهی

Theodore Papamarkouمشاهده پروفایل

استاد

• Bayesian Deep Learning
• Topological Deep Learning
• Healthcare AI
• +۳ مورد دیگر

Professor Theodore Papamarkou is a leading researcher in Bayesian and topological approaches to deep learning, with a focus on healthcare applications. His work addresses scalability challenges in machine learning by integrating Bayesian inference and topological data analysis into deep learning frameworks. He contributes to the UN Sustainable Development Goals through his research in Digital Futures and the Centre for Digital Trust and Society. Key projects include collaborations on financial crime prevention and digital trust. He received the 2023 ECML PKDD best paper award and serves as Editor-in-Chief of ACM Transactions on Probabilistic Machine Learning. His research spans topics like uncertainty quantification, material microstructure analysis, and predictive model interpretability. Professor Papamarkou has contributed to 19 peer-reviewed publications and actively participates in academic activities such as editorial work and conference organization. His interdisciplinary approach bridges computer science, statistics, and healthcare, emphasizing ethical and practical AI applications.

• Security of Deep Learning Systems
• Side-Channel Attacks
• Privacy-Preserving Machine Learning
• +۳ مورد دیگر

Dr. Yuanyuan Yuan is a Researcher at the Department of Computer Science, ETH Zurich, Switzerland, based at CNB H 104.1, Universitätstrasse 6, 8092 Zurich. Her work bridges computer security and machine learning with a focus on practical vulnerabilities in deployed AI systems. Her research centers on exposing and mitigating security flaws in deep learning deployments, particularly targeting trusted execution environments (TEEs) and on-device inference systems. Key contributions include pioneering side-channel attacks against TEE-shielded neural networks (CipherSteal, HyperTheft), bit-flip attack surfaces in DNN executables (BitShield), and novel testing methodologies for neural network robustness. She investigates cache/timing side channels, ciphertext analysis, privacy leakage in partitioned ML, and concept-based explainability. Analysis of her 2023-2025 publications reveals a cohesive focus on offensive security research for AI infrastructures, with consistent contributions to top venues in security and machine learning. Her work demonstrates expertise in low-level system interactions (memory, cryptography) applied to ML security, spanning attack vectors, defensive mechanisms, and validation frameworks. The research trajectory shows increasing sophistication in exploiting hardware-software interfaces while developing practical hardening techniques for real-world deployments.

• Cybersecurity
• Explainable AI (xAI)
• Machine Learning
• +۵ مورد دیگر

Aleksandra Pawlicka is a prominent researcher specializing in cybersecurity , explainable AI , and disinformation detection . Her work bridges ethical considerations with technical innovations in network security and AI applications , particularly focusing on the intersection of human-robot collaboration , fake news analysis , and IoT vulnerabilities . Key research areas: Cybersecurity Ethics, AI Explainability, Disinformation Mitigation Notable collaborations: Marek Pawlicki, Rafal Kozik, Michal Choras Her publications analyze xAI challenges in intrusion detection, machine learning for network security, and ethical dilemmas in cybersecurity. She contributes to projects like ULTIMATE (robotic AI) and SWAROG (fake news detection), emphasizing transparency and practical implementation. Recent work explores adversarial attacks against AI systems , few-shot learning for cybersecurity, and neuro-symbolic reasoning for trustworthy AI. Her 2023 study on ChatGPT's impact on scientific communication highlights evolving technological and ethical landscapes in academic practices.

• Robotics
• Human-Robot Interaction
• Autonomous Agent Systems
• +۳ مورد دیگر

Mauro Dragone is an Associate Professor at Heriot-Watt University's School of Engineering & Physical Sciences, affiliated with the Institute of Sensors, Signals & Systems. He holds a BSc in Computer Science from Bologna University (1999) and a PhD from University College Dublin (2009). Before academia, he worked as a software developer and project manager. His research focuses on robotics, human-robot interaction, IoT, and Ambient Assisted Living (AAL), with leadership roles in EU projects like METRICS/HEART-MET and the OpenAAL initiative. He co-directs the MSc Robotics program and established the Robotic Assisted Living Tested lab within the UK National Robotarium. Key research interests include assistive robotics for frailty, healthcare robotics, and self-adaptive robotic systems. Notable contributions include the FP7 RUBICON project (2011-2014) and the Cognitive Assistive Robotic Environment (CARE) group. He has received awards such as the 2024 Principal's Research Impact Award and 2022 Research Team of the Year. Recent articles emphasize healthcare applications, modular robotics, and trustworthy AI. His work aligns with UN SDGs addressing healthy aging and sustainable cities.

Yue Huمشاهده پروفایل

استادیار

• Robotics
• Human-Robot Interaction
• Assistive Robotics
• +۳ مورد دیگر

Yue Hu is an Assistant Professor at the University of Waterloo, affiliated with the Faculty of Engineering. His research focuses on Human-Robot Interaction (HRI), assistive robotics, and control systems with a particular emphasis on safety, adaptability, and user experience. Key areas include robot emotional expressions, physical interaction safety, and real-time systems for social robots. He leads the Active and Interactive Robotics Lab , developing solutions for mobility assistance, teleoperation systems, and cybersecurity in robotics. His work integrates biomechanical modeling, computer vision, and machine learning to create robots that better understand and adapt to human needs. Notable projects include real-time pose estimation for mobility support, encrypted network traffic analysis for robot security, and personality shaping in social robots. He emphasizes ethical design and human factors in robotics, conducting studies on refugee education and unanticipated robot actions. Yue Hu holds a full-time faculty position and collaborates with industry and academic partners to advance assistive technologies and interactive systems. His research bridges theoretical foundations with practical applications, aiming to improve quality of life through innovative robotic solutions.

Wolfgang Nejdlمشاهده پروفایل

استاد

• Search and information retrieval
• Information systems and databases
• Semantic Web and Web 2.0
• +۴ مورد دیگر

Wolfgang Nejdl is a Full Professor of Computer Science at Leibniz Universität Hannover since 1995 and the Head of the L3S Research Center since 2001. His research focuses on Web Science, search and information retrieval, semantic web technologies, peer-to-peer infrastructures, databases, technology-enhanced learning, and artificial intelligence. Education: M.Sc. (1984) and Ph.D. (1988) in Computer Science from Vienna University of Technology. Previous Positions: Assistant Professor in Vienna (1988–1992), Associate Professor at RWTH Aachen (1992–1995), and visiting professor/researcher at Xerox PARC, Stanford, University of Illinois at Urbana-Champaign, EPFL Lausanne, and PUC Rio. His research spans foundational and applied Web technologies, including social networks, trust and reputation, Web infrastructure, digital libraries, semantic web, collaborative filtering, and privacy-preserving systems. Recent projects like PHAROS, OKKAM, LiWA, and LivingKnowledge highlight his work in audio-visual search, web entities, web archive management, and diversity bias algorithms. Wolfgang Nejdl published over 230 scientific articles and held leadership roles as General Chair for AH'08 and PC Chair for WWW'09. He co-founded iSearch IT Solutions in 2006 to commercialize digital library and web engineering research from L3S projects. Scientific Awards: Founding member and head of the L3S Research Center The L3S Research Center, with a 2009 budget of €6 million (75% third-party funding), focuses on connecting the Web to real-world entities through research in Web Science, service computing, and security. Funding comes equally from the European Union and national/industry sources.

Lucius Caviolaمشاهده پروفایل

پژوهشگر ارشد

• Ethics
• Moral Philosophy
• Moral Psychology
• +۴ مورد دیگر

Lucius Caviola is a Senior Research Fellow in Psychology at the Global Priorities Institute, University of Oxford. His work focuses on moral psychology, ethics, and effective altruism, particularly examining decision-making in pro-social contexts like charitable giving, moral circle expansion, and societal risk management. Education : 2019–2023: Postdoc, Harvard University 2022–2023: Visiting Scholar, New York University 2015–2019: DPhil in Experimental Psychology, University of Oxford 2014–2015: MSc in Experimental Psychology, University of Oxford 2010–2013: BSc in Psychology, University of Basel Research Interests : Caviola investigates psychological barriers to societal welfare improvement, including speciesism, effective altruism dynamics, and moral intuitions about AI and biotechnologies. His work bridges philosophy, psychology, and public policy to design practical interventions. Recent Research Trends : His 2023–2025 publications emphasize AI ethics (e.g., AI sentience debates), moral psychology of speciesism, and societal responses to existential risks. He explores how temporal and social factors shape moral judgments in emerging technologies and pro-social contexts. Labs/Teams : Affiliated with the Global Priorities Institute, focusing on high-impact research in global priorities and existential risk mitigation.

Age Chapmanمشاهده پروفایل

استاد

• Data Provenance
• Decentralized Systems
• Machine Learning Ethics
• +۱ مورد دیگر

Age Chapman is Professor of Computer Science at the University of Southampton. She leads research in data provenance, decentralized systems, and ethical AI through projects like ESPRESSO focused on secure personal data search. Her work bridges computer science with healthcare, heritage preservation, and social justice applications. Research interests include: privacy-preserving data architectures, algorithmic fairness in healthcare, and provenance tracking for AI systems. She directs PhD research across these domains and collaborates with the Alan Turing Institute and healthcare organizations. Publications demonstrate strong focus on decentralized data management (80% of recent papers) with growing emphasis on AI ethics. Awards include the SIGMOD Test of Time Award for seminal provenance research. Current grants support work on sovereign data ecosystems and healthcare AI fairness. She leads the Digital Health and Biomedical Engineering research group and collaborates internationally through the Alan Turing Institute and European partnerships. Manages labs exploring data trust architectures and healthcare AI systems.

Keer Yangمشاهده پروفایل

استادیار

• FinTech
• Machine Learning
• Financial Intermediaries
• +۱ مورد دیگر

Keer Yang is an Assistant Professor at the University of California, Davis, Department of Finance. His research explores the intersection of FinTech, Machine Learning, Financial Intermediaries, and Corporate Finance, focusing on how technology can improve financial market efficiency and inclusivity. Education Ph.D., Finance, University of Minnesota, 2022 B.S., Mathematics and Applied Mathematics, Zhejiang University, China M.Res., Economic Theory and Econometrics, Toulouse School of Economics, France Yang’s work investigates FinTech’s role in reshaping financial markets. He employs machine learning for causal inference and big data analysis to address gaps in traditional finance research, particularly regarding trust dynamics and racial disparities in lending. His publications include studies on trust as an entry barrier in FinTech and racial barriers in small business lending. His research highlights the transformative potential of machine learning in corporate finance, emphasizing equitable financial systems through technological innovation. No scientific awards were explicitly mentioned in the provided text.

Zhao Zhaoمشاهده پروفایل

استادیار

• Wearable Systems
• Human-Computer Interaction (HCI)
• Human-Robot Interaction (HRI)
• +۴ مورد دیگر

Zhao Zhao is an Assistant Professor at the School of Computer Science, University of Guelph. Her work focuses on wearable systems, human-robot interaction, and gamification for health and education. She holds a PhD from Carleton University (2019) and completed a postdoctoral fellowship at the University of Toronto (2019–2023) before roles at McMaster University and her current position. Education includes a BSc in Computer Science from University of Electronic Science and Technology of China (2011), MSc from Carleton University (2014), and PhD in Electrical and Computer Engineering (2019). Research interests span physiological computing, AI-assisted creativity tools, and adaptive systems leveraging wearable sensors. Key research areas include: 1) Wearable-based gamification for health and education, 2) Emotion sensing via physiological signals, and 3) Human-robot interaction enhanced by wearable data. Her lab uses Empatica EmbracePlus wristbands and Emotiv EEG headsets to analyze real-time physiological responses in diverse interaction scenarios. Recent publications (2020–2025) emphasize personalized exergame systems, child-robot interaction studies, and AI linguistic competency analysis. She actively seeks graduate students and industry partnerships in wearable technology, education tech, and HRI.

• Transportation and Logistics
• Supply Chain Management
• Operations Research
• +۷ مورد دیگر

Prof. Keng Hock, Mark Goh is a Professor at the National University of Singapore (NUS) Business School, holding a joint appointment as Director (Industry Research) at The Logistics Institute-Asia Pacific (TLI-AP). He specializes in logistics, supply chain strategy, and operations research. He earned his PhD from the University of Adelaide on a fully funded scholarship and has held adjunct and visiting roles globally. His research focuses on supply chain risk management, healthcare logistics, and strategic decision-making, with over 400 publications in top journals. Notable contributions include work on multi-criteria supplier selection, supply chain resilience, and AI ethics in e-commerce. He has received the Supply Chain Educator Award and is recognized in global directories like *Who’s Who in Asia and the Pacific Nations*. Prof. Goh advises public and private sector organizations on logistics strategy and sits on industry committees such as the World Economic Forum’s Global Advisory Council on Logistics. His current projects emphasize syncretic value-driven logistics models and sustainable recycling frameworks. He leads collaborative research teams addressing global supply chain challenges through interdisciplinary approaches. His articles reflect cutting-edge advancements in AI-driven decision models, risk networks in construction, and data ownership strategies in digital platforms. These contributions underscore his role as a thought leader in logistics and operations research, blending academic rigor with real-world industry applications.

• Numerical Methods
• Partial Differential Equations
• Computational Mathematics
• +۳ مورد دیگر

Francisco Manuel Bernal Martínez is an Associate Professor in the Department of Mathematics at Carlos III University of Madrid. His research focuses on numerical methods, partial differential equations, and computational mathematics, with applications in industrial engineering and materials science. He leads projects such as 'Financiación adicional 5º año (2022)' and collaborates on initiatives like 'Clustering Automático de Comportamientos de Invertebrados en Libertad mediante Imagen 3D.' His work emphasizes domain decomposition algorithms, radial basis functions, and stochastic control problems. He has advised at least one PhD thesis and holds grants from regional and national funding bodies. Key research interests include meshless methods, probabilistic domain decomposition, and uncertainty quantification in energy systems. Recent publications highlight advancements in hybrid algorithms for large-scale PDEs and volatility modeling. Bernal Martínez actively participates in academic networks and has presented at international conferences on computational methods and industrial mathematics.

Wu Jieمشاهده پروفایل

استاد

• Mobile Computing
• Wireless Networks
• Cloud Computing
• +۵ مورد دیگر

Dr. Jie Wu is the Laura H. Carnell Professor and serves as Director of the Center for Networked Computing at Temple University's Department of Computer and Information Sciences. He has held leadership roles including Chair of the department (2009-2016), Associate Vice Provost for International Affairs (2015-2017), and Director of International Affairs in the College of Science and Technology. Previously, he was a distinguished professor at Florida Atlantic University (1989-2009) and held NSF program director roles (2007-2009). Education: PhD in Computer Engineering, Florida Atlantic University (1989) MSc in Computer Science, Shanghai University of Science and Technology (1985) BSc in Computer Science, Shanghai University of Science and Technology (1982) Research focuses on mobile/wireless networks, cloud computing, distributed systems, and cybersecurity. He has led NSF-funded projects and pioneered protocols for ad hoc networks. His work integrates machine learning with network trust mechanisms. Awards highlight his contributions: AAAS/IEEE Fellowships, ACM Distinguished Membership, and multiple best paper recognitions. He chairs major conferences like IEEE MASS and ICDCS, and serves on editorial boards for IEEE Transactions on Mobile Computing and others. Professional service includes leadership roles in IEEE Technical Committees, CCF (Chinese Computer Federation), and organizing over 20 international conferences. His lab at Temple University drives innovations in networked systems and distributed computing.

Yuchi Zhangمشاهده پروفایل

دانشیار

• E-commerce
• Digital Promotions
• Social Media Strategy
• +۳ مورد دیگر

Yuchi Zhang is an Associate Professor of Marketing and Program Director of the Master's of Science in Marketing Program at Santa Clara University's Leavey School of Business. He holds a Ph.D. in Marketing from the University of Maryland and a B.S. in Economics from the Wharton School, University of Pennsylvania. His research focuses on e-commerce, digital promotions, and social media strategy, employing Bayesian methods, machine learning, and field experiments to study consumer decision-making in technology-enabled environments. He has published in top journals like Marketing Science and Journal of Marketing Research. Dr. Zhang teaches undergraduate and graduate courses in Principles of Marketing and Social Media Marketing. He has received outstanding teaching and research awards at Santa Clara University, reflecting his dual commitment to pedagogy and scholarly impact. His work explores topics such as omnichannel retailing strategies, the impact of social media influencers, and the interplay between online and offline consumer behavior. He currently oversees the MS Marketing Program, emphasizing practical industry-relevant training.

• Behavioral Economics
• Big Data
• Computational Social Science
• +۶ مورد دیگر

Giuseppe Alessandro Veltri is a Full Professor at the University of Trento's Department of Sociology and Social Research. His expertise spans Behavioral Economics, Big Data, Computational Social Science, and Social Psychology. He currently teaches courses such as 'Big Data' and 'Social Dynamics Lab' within the Data Science and Previsione Sociale programs. His research focuses on understanding human behavior through digital methodologies, including studies on vaccine hesitancy, darknet markets, and the psychological aspects of pandemics. Veltri is also actively involved in designing computational tools like TextualLLMap to analyze societal biases in AI systems. His work bridges theoretical frameworks with empirical data, emphasizing interdisciplinary approaches to social science challenges. Research interests include the application of computational methods to study risk perception, online behavior, and policy design. Recent studies explore how behavioral insights can improve public health strategies during crises and how transparency in digital platforms influences consumer decisions. Veltri's contributions also extend to methodological innovations, such as optimizing online experiments and addressing gaps in cognitive sociology.