جستجوی استاد راهنمای دانشگاهی

Gary Marchioniniمشاهده پروفایل

استاد

• Information Interaction
• Human-Computer Interaction
• Digital Libraries
• +۶ مورد دیگر

Dr. Gary Marchionini is the Cary C. Boshamer Distinguished Professor and Dean of the School of Information and Library Science (SILS) at the University of North Carolina at Chapel Hill. He previously served as a professor at the University of Maryland's College of Library and Information Services and as a member of the Human-Computer Interaction Laboratory. His expertise spans information interaction, human-computer interaction, digital libraries, and information policy. Marchionini holds a PhD in mathematics education from Wayne State University, emphasizing educational computing. His research focuses on interfaces for information seeking, digital video retrieval, and the impact of data science. Notable projects include the Information in Life Video Series (2007), one of the first academic YouTube channels, and leadership in the Open Video Project . He has secured grants from NSF, NASA, Microsoft, and Google, among others. Marchionini's awards include the ASIS&T Award of Merit (2011) and the LITA Kilgour Award (2000). He has served as editor-in-chief of ACM Transactions on Information Systems (2002–2008) and as president of ASIS&T (2010). Current interests include the societal impact of information, personal health records usability, and digital curation strategies. His leadership roles include serving on the iSchools Board of Directors and directing the Center for Information Impact. He has advised numerous grants, including Mellon Foundation-funded initiatives and EPA research library operations. Marchionini's work bridges academic research with real-world applications, emphasizing human-centered design and interdisciplinary collaboration.

Nicolò Cesa-Bianchiمشاهده پروفایل

استاد

• Machine Learning
• Online Learning
• Multi-Armed Bandits
• +۴ مورد دیگر

Nicolò Cesa-Bianchi is a Professor of Computer Science at the University of Milan, Department of Computer Science (Dipartimento di Informatica), and affiliated with the DEIB Department at Politecnico di Milano. His research focuses on foundational aspects of machine learning, particularly online learning, multi-armed bandits, reinforcement learning, and graph analytics. He is an ELLIS Fellow and a corresponding member of the Accademia Nazionale dei Lincei. Research interests include the design and analysis of algorithms for prediction, clustering, and online decision-making, with applications to digital markets, social networks, and bioinformatics. Notable contributions span cooperative online learning, multitask learning, and bandit algorithms. He co-authored the influential book Prediction, Learning, and Games (2006). Professional roles include Board member of ELLIS, co-director of the Milan ELLIS unit, and involvement in EU initiatives like ELSA (Secure & Safe AI) and ELIAS (AI for Sustainability). He teaches graduate courses on statistical methods, machine learning, and reinforcement learning, with a focus on theoretical foundations. Key awards: ELLIS Fellowship (2020), Corresponding Member of the Accademia Nazionale dei Lincei (Italian National Academy of Sciences). His work bridges theory and practice, addressing challenges in adaptive systems, market design, and algorithmic fairness. Current projects explore distributed learning, regret minimization in adversarial environments, and interpretable models.

Milena Dobrevaمشاهده پروفایل

مدرس ارشد

• Cultural Heritage Digitization
• Digital Libraries
• Media Literacy
• +۵ مورد دیگر

Dr. Milena Dobreva is a Senior Lecturer in Information Behavior at the Department of Computer and Information Sciences, University of Strathclyde, Scotland. She holds roles in the Faculty of Science and is affiliated with the Strathclyde iSchool. Her work focuses on innovation diffusion in cultural and scientific heritage sectors, media literacy, and combating misinformation. She has led projects funded by the European Commission, including the Bulgarian Romanian Observatory of Digital Media and the LEARN & EXCHANGE initiative to develop international MOOCs on digital transformation. Her research explores user needs in digital heritage, open innovation tools for cultural institutions, and digital skills training in Sub-Saharan Africa. Professional Activities Principal Investigator on projects addressing digital divide, GLAM innovation labs, and disinformation policy. Member of the Scientific Board of DARIAH and the Europeana Network Association. Peer reviewer for journals like Transformations: A DARIAH Journal and conferences such as ACM/IEEE-CS JCDL. Research Interests Innovation labs for GLAM sectors (Galleries, Libraries, Archives, Museums). Data spaces and digital transformation frameworks for cultural heritage. Information behavior in the context of disinformation and media literacy. Open science infrastructures and policy implementation. Grants & Projects Bulgarian Romanian Observatory of Digital Media (2022–2025): Combats disinformation through regional collaboration. LEARN & EXCHANGE (2022–2024): Develops multilingual MOOCs for digital transformation skills. eCHOIng (2021–2024): Uses open innovation to revitalize cultural heritage institutions. Labs & Collaborations Co-leads GLAM innovation labs research, focusing on digital divide mitigation and heritage digitization. Active in the CEDCHE (Common European Data Space for Cultural Heritage) initiative.

Gregorio Iglesiasمشاهده پروفایل

استاد

• Marine Renewable Energy
• Coastal Engineering
• Wave Energy Conversion
• +۵ مورد دیگر

Prof. Gregorio Iglesias is a Professor of Marine Renewable Energy at University College Cork (UCC) and Honorary Professor of Coastal Engineering at the University of Plymouth. His expertise lies in Marine Renewable Energy and Coastal Engineering, with a focus on wave and tidal energy systems, offshore wind integration, and coastal protection strategies. He has secured over €12M in research funding as Principal Investigator and authored/edited key texts such as Wave and Tidal Energy (Wiley) and Ocean Energy and Coastal Protection (Springer). Education: BEng (Civil Engineering, 1992), MEng (Civil Engineering, 1993), PhD (Engineering, 2001). Research Interests: Advanced modeling of wave energy converters, floating offshore wind turbines, coastal erosion mitigation, and climate change impacts on marine energy resources. His work bridges theoretical advancements and practical applications, including coasts like the Port of Gijón (Spain) and the Shannon Estuary. Recent publications highlight climate-driven renewable energy transitions, multi-hazard coastal resilience frameworks, and techno-economic assessments of offshore systems. He chairs the IEC Standards panel for wave energy device testing and serves as Subject Editor for Energy (Elsevier) . Professional Activities: Lead of Marine Renewable Energy research at MaREI (Ireland), former Head of the COAST Engineering Group at Plymouth (2012–2018), and member of PIANC’s Universities Consortium. His work has generated 5,459 citations with an h-index of 41. Teaching: Delivers modules on Ocean Energy (NE4003/NE6005) and Hydraulics (CE3007).

Takahiro Yabeمشاهده پروفایل

استادیار

• Computational Social Science
• Urban Resilience
• Human Mobility
• +۵ مورد دیگر

Dr. Takahiro Yabe is an Assistant Professor at the Department of Technology Management and Innovation (TMI) and the Center for Urban Science + Progress (CUSP) within New York University's Tandon School of Engineering. His research focuses on computational social science and network science approaches to model urban resilience against disasters, pandemics, and technological disruptions. He holds a Ph.D. from Purdue University (2021) and degrees from the University of Tokyo (BS 2015, MS 2017). Previously, he was a Postdoctoral Associate at MIT's IDSS and Media Lab under Sandy Pentland and Esteban Moro. Research interests include urban resilience, human mobility, socioeconomic networks, inequality, and computational modeling. He leads the Resilient Urban Networks (RUN) Lab, an interdisciplinary group developing data-driven tools for urban systems analysis. His work has been published in top journals like Nature Human Behaviour, PNAS, and Nature Machine Intelligence. Recent grants include NSF funding for EV charging infrastructure planning (SAI 2024) and post-disaster mobility governance (HDBE 2024). Notable awards include the NICE STEP Researchers recognition (2024). His lab collaborates with urban planners, policymakers, and global institutions to advance equitable urban resilience strategies. Current projects involve open mobility data standards, disaster recovery policy assessment, and AI-driven urban modeling. Students supervised include PhD candidates Vaidehi Raipat (urban policy), Callie Clark (mobility equity), and DongHak Lee (socioeconomic networks). The lab also hosts visiting scholars like Mavin De Silva (EV charging systems) and supports master's students in mobility analysis and disaster response.

Kelvin Kam-fai TSOI蔡錦輝مشاهده پروفایل

دانشیار

• Hypertension and Cardiovascular Diseases
• Cognitive Impairment and Dementia
• Digital Health
• +۴ مورد دیگر

Prof. Kelvin Kam-fai TSOI is an Associate Professor at the JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong (CUHK). He holds courtesy appointments at the Stanley Ho Big Data Decision Analytics Research Centre and The Jockey Club Institute of Ageing. A Visiting Associate Professor at Nanyang Technological University’s Lee Kong Chian School of Medicine and Visiting Professor at Shenzhen Institutes of Advanced Technology, he specializes in Digital Health and Epidemiology. Education: BSc in Statistics and PhD in Public Health from CUHK. Postdoctoral training in Gastroenterology and Hepatology at CUHK’s Department of Medicine and Therapeutics. Served as Director of the CUHK JC Bowel Cancer Education Centre and worked in the Hospital Authority on chronic disease management projects. Research interests focus on digital innovations for chronic disease management, including AI in hypertension, cognitive screening technologies, and wearable health devices. His work combines traditional epidemiology with big data analytics, emphasizing interdisciplinary collaboration between medicine and engineering. Key projects include developing a mobile blood pressure management platform via DeepHealth Limited, a social enterprise he founded in 2019. Current research explores seasonal effects on blood pressure variability and AI applications in healthcare. He co-founded the International Society for Digital Health and organizes global symposiums on digital health innovation. Grants & Awards: Supported by CUHK’s Sustainable Knowledge Transfer Fund (SKPF). Awards include IBM Honorarium Award (2020) and President’s Prize for Best Paper Presentation (2017).

Anna Monrealeمشاهده پروفایل

دانشیار

• Privacy-Preserving Data Mining
• Big Data Analytics
• Social Network Analysis
• +۷ مورد دیگر

Anna Monreale is an Associate Professor in the Department of Computer Science at the University of Pisa and a key member of the Knowledge Discovery and Data Mining Laboratory (KDD-Lab), a joint research group with the Information Science and Technology Institute of the National Research Council (ISTI-CNR) in Pisa. Her academic career is rooted in the University of Pisa, where she completed her Bachelor's, Master's, and Ph.D. in Computer Science. Her research focuses on privacy-preserving data analytics, with core interests in big data analytics, social network analysis, spatio-temporal mining, and explainable AI. She is particularly known for her work on privacy-by-design in data mining and evaluating privacy risks in analytical processes. Her research bridges technical innovation with ethical and legal considerations in data science. Her recent publications reveal a strong trend toward explainable AI, privacy in federated learning, and risk assessment in mobility and health data. She actively contributes to developing methods for explaining black-box models, assessing privacy exposure, and balancing privacy, utility, and fairness in AI systems. Privacy by Design Ambassador (2014) ISTI-CNR Young++ Researcher Award (2014) Monreale has advised and co-chaired several international workshops, including PriSMO, PinSoDa, and MoKMaSD, and serves on editorial boards such as Transactions on Data Privacy. She teaches advanced data mining, big data ethics, and database systems across multiple graduate and undergraduate programs. She is involved in major EU projects like SoBigData, XAI, TAILOR, and HumMingBird, reflecting her leadership in data science and AI ethics. She is affiliated with the KDD-Lab, a prominent research group focused on knowledge discovery, social mining, and big data analytics, contributing to both theoretical advances and real-world applications in privacy-aware data science.

Scot M. Millerمشاهده پروفایل

دانشیار

• Atmospheric Science
• Greenhouse Gases
• Air Pollution
• +۱۱ مورد دیگر

Scot M. Miller is an Associate Professor in the Department of Environmental Health and Engineering at the Whiting School of Engineering, Johns Hopkins University. He leads the Greenhouse Gas Research Group, focusing on quantifying emissions of greenhouse gases and air pollutants using satellite, aircraft, and tower observations. His research spans global scales, from Arctic ecosystems to urban and industrial sources in the U.S. and China. His research interests include atmospheric science, greenhouse gas emissions, inverse modeling, big data analytics, and climate policy. He integrates tools from statistics, high-performance computing, and satellite remote sensing to improve emission estimates and inform environmental regulations. Recent publications highlight trends in methane, ethane, and sulfuryl fluoride emissions, carbon cycle dynamics, and innovative methods for analyzing massive satellite datasets. His work increasingly leverages OCO-2 and OCO-3 satellite data to study carbon dioxide and methane fluxes across diverse ecosystems. Scientific awards include the NSF CAREER Award, JHU Catalyst Award, and the Carnegie Distinguished Postdoctoral Fellowship. He was also recognized with Harvard’s Certificate of Excellence in Teaching. Miller advises multiple PhD students, including Mingyang Zhang, Dylan Gaeta, and Leyang Feng, and has secured grants from NASA, NSF, NOAA, and JHU. He is a member of the NASA OCO Science Team and collaborates with institutions such as Northern Arizona University, Carnegie Institution, and NOAA. His lab is involved in urban environmental monitoring in Baltimore and interdisciplinary climate policy research.

Jane Binnerمشاهده پروفایل

استاد

• Financial Resilience
• Financial Services Indices
• Financial Innovation
• +۷ مورد دیگر

Professor Jane Binner is Chair of Finance in the Department of Finance at Birmingham Business School, University of Birmingham. She leads research at the intersection of finance, economics, and data science, with a strong emphasis on big data and artificial intelligence applications. Research Interests: Her work spans Financial Resilience , Financial Innovation , Big Data Analytics , and Econometric Modelling . She applies advanced multivariate techniques to economic and financial data, contributing to both academic and commercial domains. Her research has significant policy and industrial relevance, involving collaborations with government and private sector entities. Her recent publications reflect a strong trend in computational finance and economic policy, focusing on topics such as Brexit, pandemic response, monetary aggregates, and social media analytics. These works demonstrate interdisciplinary rigor and real-world impact, particularly in forecasting and policy evaluation. Scientific Awards: Fellow of the Institute for Nonlinear Dynamical Inference (INDI) Advising and Grants: While specific student advisees are not listed, Professor Binner has attracted over £1 million in external research funding from major bodies including EPSRC/ESRC, Leverhulme Trust, National Science Foundation, and industrial partners like Boots and Experian. She has served as Impact Lead and Director of the Financial Resilience Cluster, highlighting her leadership in research impact and multidisciplinary collaboration. Labs and Teams: She leads the Financial Resilience Cluster at the University of Birmingham, fostering cross-disciplinary research in finance. She also collaborates internationally, including as a visiting professor at the University of Wisconsin and through her INDI Fellowship.

• Accounting
• Public Policy
• Carbon Accounting
• +۸ مورد دیگر

Jane Andrew is a Professor and Head of Discipline at the University of Sydney Business School, specializing in Accounting. She joined the University of Sydney in 2010 after holding various academic positions at the University of Wollongong. Andrew serves as co-editor-in-chief for Critical Perspectives on Accounting (since 2018) and is an Associate Editor for Abacus, with editorial board memberships for several prominent accounting journals. Professor Andrew's research explores the relationship between accounting information and public policy, with particular focus on climate change accounting, prison privatisation, and neoliberalism. Her work examines how accounting practices influence policy decisions, particularly in areas traditionally managed by governments, including prisons, immigration detention, and environmental regulation. She has made significant contributions to understanding the role of accounting in processes of neoliberalisation and the privatisation of public services. Her recent publications demonstrate a growing focus on data privacy, surveillance capitalism, and the financialisation of social services. Her work spans critical accounting, political economy, and interdisciplinary research, often collaborating with scholars from law, political science, and criminology. Andrew's research has practical policy implications, as evidenced by her submissions to parliamentary inquiries and engagement with government departments. Professor Andrew actively supervises PhD students and teaches postgraduate courses including ACCT6001 Intermediate Financial Reporting, ACCT6002 International Accounting, and BUSS4001 Business Honours Research Methods. Her supervision spans diverse topics including accountability in microfinance, time budgeting in consulting firms, and the interplay between accounting practices and architectural design. Her scholarly impact extends beyond traditional publication through submissions to public inquiries, policy-relevant research reports, and media articles where she actively engages in evidence-based policy discussions with industry and government partners.

Christian Egwimمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Big Data Analytics
• Machine Learning
• +۴ مورد دیگر

Christian Egwim is a Researcher in the Department of Computer Science at the University of Bath. With a PhD in Applied Artificial Intelligence from the University of Hertfordshire and a BSc in Computer Science from the University of Ibadan, he specializes in Artificial Intelligence, Big Data Analytics, Machine Learning, Software Engineering, Digital Technology Innovation, Environmental Monitoring, and Circular Economy. Education: PhD in Applied Artificial Intelligence, University of Hertfordshire BSc in Computer Science, University of Ibadan His research focuses on applying AI and IoT technologies to address environmental challenges, including air quality monitoring, pollution prediction, and sustainable building design. Current projects include the D-BuD initiative, which uses big data and machine learning to optimize pollution dispersion in architectural designs. His scholarly work spans topics like feature selection, ensemble modeling, and agentic AI. Collaborations include partnerships with institutions in the UK and Nigeria, contributing to advancements in environmental and construction-related AI applications.

Azza Abouziedمشاهده پروفایل

دانشیار

• Human-Data Interaction
• Database Systems
• Human-Computer Interaction
• +۷ مورد دیگر

Azza Abouzied is Associate Professor of Computer Science at New York University Abu Dhabi and Global Network Associate Professor at the Tandon School of Engineering. She serves as Vice Provost for Faculty Advancement and Engagement at NYUAD starting September 2024. Her research bridges database systems and human-computer interaction, focusing on intuitive tools for data querying and decision-making in uncertain, collaborative environments. PhD, Yale University (2013) MPhil, Yale University MSc, Dalhousie University BSc, Dalhousie University Her research centers on human-data interaction, designing systems that make data accessible to non-experts. She combines techniques from UI design, machine learning, and databases to build tools that simplify complex data tasks. Her earlier work focused on example-driven querying and synthetic data generation, while her recent work explores in-database prescriptive analytics and decision support in domains like disinformation mitigation and epidemic planning. Her publications span database and HCI venues, with a recurring theme of enhancing usability without sacrificing scalability. She co-founded Hadapt, a Big Data analytics platform, and has led interdisciplinary research through the Human-Data Interaction Lab and the Center for Interacting Urban Networks. Her teaching includes foundational courses such as Database Systems, Operating Systems, and Data, as well as the critical thinking course Techruption. VLDB Test of Time Award (2019) Best Paper Award in Database Systems Honorable Mention in HCI Publications Azza mentors undergraduate capstone students and advises prospective PhDs, research assistants, and postdocs. She is actively involved in academic leadership, having chaired NYUAD’s faculty council in 2024 and co-chaired the SIGMOD 2025 program. Her work emphasizes empowering users to critically engage with data and AI, both in research and education.

Anirban Chakrabortiمشاهده پروفایل

استاد

• Econophysics
• Sociophysics
• Complex Systems
• +۱۴ مورد دیگر

Anirban Chakraborti is a Professor at the School of Computational and Integrative Sciences, Jawaharlal Nehru University (JNU), New Delhi, India, where he has been a faculty member since 2014. He previously held academic positions at École Centrale Paris (France) as Chercheur Senior (Associate Professor) and Chargé de Recherche (Assistant Professor), and earlier roles at Banaras Hindu University, Brookhaven National Laboratory (USA), and Helsinki University of Technology (Finland). He is a leading figure in the interdisciplinary field of econophysics and complex systems. Education: Diplôme d’Habilitation à Diriger des Recherches (2013), Université Pierre et Marie Curie – Paris VI, France (Physics) Ph.D. in Physics (2003), Saha Institute of Nuclear Physics, Jadavpur University, India Post-M.Sc. in Physics (1999), Saha Institute of Nuclear Physics, Jadavpur University, India (Ranked First) M.Sc. in Physics (1998), University of Calcutta, India (Ranked First) B.Sc. in Physics (1996), Scottish Church College, University of Calcutta, India His research interests lie at the intersection of physics, economics, and data science. He is particularly known for pioneering work in econophysics , including the statistical mechanics of money, wealth distribution, agent-based market models, and network-based analysis of financial and social systems. He also works on complex systems , computational finance , statistical physics , and nanosciences , with applications in sensing and imaging. His work often involves modeling socio-economic phenomena using tools from statistical physics. His recent publications span topics such as financial fluctuations, wealth inequality, network analysis of conflicts, order book dynamics, and nanomaterial characterization. These works reflect a strong trend toward interdisciplinary research combining physics, economics, and data analytics, with a focus on real-world applications in finance, inequality, and social systems. Scientific Awards: Indian National Science Academy Young Scientist Medal (2009) He has advised Ph.D. students such as Kiran Sharma and leads the ETC (Experimental-Theoretical-Computational) Lab at JNU, which brings together physicists, computer scientists, and mathematicians. The lab has been involved in international collaborations, including projects funded by the Estonian Ministry of Education and Research and consultancies with TCS Innovation Labs and DONO Consulting. His research has been supported through grants and collaborative projects, reflecting strong industry and global academic engagement.

Malcolm Heywoodمشاهده پروفایل

استاد

• Genetic Programming
• Coevolution
• Reinforcement Learning
• +۱۲ مورد دیگر

Dr. Malcolm Heywood is a Professor in the Faculty of Computer Science at Dalhousie University, Halifax, Canada. He leads the Network Information Management and Security (NIMS) Lab and is actively involved in research on genetic programming, coevolution, reinforcement learning, and big data analytics. His research interests span: Genetic Programming and Evolutionary Computation Coevolution and Competitive Learning Problem Decomposition and Hierarchical Models Streaming Data Analysis and Anomaly Detection Network Security and Insider Threat Detection Reinforcement Learning in Games (Atari, ViZDoom, Dota 2) Dr. Heywood's recent publications focus on emergent behaviors in reinforcement learning using Tangled Program Graphs (TPG), benchmarking genetic programming for streaming data, and applications in cybersecurity and computational finance. His work demonstrates a strong trend toward scalable, efficient evolutionary models for complex, real-world problems. His scientific awards include: Silver placed at Human-Competitive (Humies) Competition (2018) Best Paper at EuroGP (2017) Best Paper at DETA track, ACM GECCO (2017) Best Paper at RWA track, ACM GECCO (2018) Nomination for Best Paper at DETA track, ACM GECCO (2019) He has supervised numerous graduate students, including PhD and Master's candidates, many of whom have continued research in evolutionary computation. His lab has developed open-source code distributions for Tangled Program Graphs and Symbiotic Bid-Based GP. Dr. Heywood teaches courses in Computer Organization, Introduction to AI with Gaming Applications, and Genetic Algorithms and Programming.

Marta Kryvenمشاهده پروفایل

استادیار

• Computational Cognitive Science
• Artificial Intelligence
• Cognitive Psychology
• +۷ مورد دیگر

Marta Kryven is an Assistant Professor in the Faculty of Computer Science at Dalhousie University. Her research integrates artificial intelligence, cognitive science, and experimental psychology to develop computational models of human cognition, focusing on planning, perception, and behavior. She is actively engaged in interdisciplinary research and is accepting graduate students. Research Interests: Computational models of cognition and behavior Large Language Models and their alignment with human thought Spatial navigation and environmental interaction Program synthesis and induction Representation learning and cognitive modeling Human-AI alignment and interpretability Her recent publications demonstrate a strong trend in combining symbolic AI with neural models to simulate human-like reasoning, particularly in spatial and social contexts. She frequently collaborates with leading researchers at MIT, especially Joshua Tenenbaum. Her work appears in top-tier venues such as NeurIPS, Cognitive Science, and Nature Computational Science. Scientific Awards: No awards explicitly mentioned in the provided text. Advising and Grants: Marta Kryven is currently accepting applications from graduate students and has several projects available for both undergraduate and graduate researchers. While specific grants are not listed, her active publication record in high-impact journals suggests ongoing funded research. She also offers consulting in AI system design, behavioral modeling, and data science for businesses. Labs and Teams: She is part of the Big Data Analytics, AI & Machine Learning research cluster at Dalhousie University. Her work is closely affiliated with cognitive science and AI research groups, likely involving collaboration with MIT’s Center for Brains, Minds and Machines. She leads a research group focused on human-like AI and computational cognitive modeling.