جست‌وجوی استاد و پژوهشگر

Patrick Wuمشاهده پروفایل

استاد

• AI/ML
• Natural Language Processing
• Computational Social Science
• +۳ مورد دیگر

Patrick Wu is a Professor in the Department of Computer Science at American University, with additional affiliations as Faculty Fellow at the Center for Data Science and Faculty Affiliate at the Center for Security, Innovation, and New Technology. He holds a PhD in Political Science and Scientific Computing from the University of Michigan, an MA in Statistics from Michigan, and a BA in Political Science and Statistics from the University of Chicago. His research develops AI/ML and natural language processing approaches for computational social science, focusing on: Political elite and non-elite ideology measurement Affective polarization on social media platforms Detection of hateful/abusive speech and memes Application of large language models to political science research Recent work explores innovative methods for political attitude measurement using LLMs, in-context learning techniques for social media analysis, and frameworks for multimodal representation learning. His publications demonstrate consistent innovation in applying NLP and machine learning to political discourse analysis, with emerging focus on generative AI's impact on political science education and methodology. Wu teaches courses including Object-Oriented Programming and topics in Natural Language Processing/Text as Data.

Lara A. Souzaمشاهده پروفایل

دانشیار

• Plant Communities
• Ecosystem Ecology
• Global Change Biology
• +۳ مورد دیگر

Lara A. Souza is an Associate Professor and Associate Director of the School of Biological Sciences at the University of Oklahoma. Her research focuses on global change impacts on plant communities and ecosystem processes, including climatic change, biological invasions, and resource gradients. She investigates how biodiversity mediates ecosystem properties like productivity and carbon dynamics across spatial and temporal scales, working in temperate prairies, tropical savannas, and montane meadows. Education: PhD in Ecology and Evolutionary Biology (University of Tennessee), MS in Biology (Appalachian State University). Her work integrates field experiments, remote sensing, and data modeling to address global change challenges. She holds no explicit scientific awards listed here but has an extensive publication record. Research emphasizes functional diversity and ecosystem responses to global stressors. Recent studies explore fire exclusion effects, drought impacts, and warming interactions with plant communities. She collaborates on projects involving environmental DNA for endangered species detection and satellite-based ecosystem modeling. No advising or grant details are provided in the text. Lara’s lab focuses on climate-ecosystem interactions, with ongoing projects in Oklahoma and tropical regions. Her work highlights the need for adaptive management strategies in the face of climate shifts and invasive species pressures.

• Structural Health Monitoring
• Seismic Analysis
• Bayesian Calibration
• +۱۴ مورد دیگر

Gaetano Miraglia is a Fixed-term Assistant Professor in the Department of Structural, Building and Geotechnical Engineering (DISEG) at Politecnico di Torino, where he conducts research in structural health monitoring, seismic analysis, and computational modeling. He is a member of the Interdepartmental Center R3C – Responsible Risk Resilience Centre, contributing to interdisciplinary efforts in risk mitigation and infrastructure resilience. His work spans both theoretical and applied domains, with strong emphasis on heritage preservation and sustainable urban development. His research interests include Bayesian calibration of nonlinear models, hybrid simulation, peridynamics, masonry structures, and the integration of satellite interferometric (InSAR) data with in-situ measurements for structural monitoring. He applies advanced computational and machine learning techniques to improve the accuracy and reliability of structural assessments, particularly in historical and monumental buildings. His work supports UN Sustainable Development Goals 9, 11, and 13. His recent publications demonstrate a consistent focus on data fusion, digital twinning, domain adaptation, and real-time damage detection. He frequently collaborates with researchers such as Rosario Ceravolo and Erica Lenticchia, publishing in high-impact journals like Computer-Aided Civil and Infrastructure Engineering , Structures , and Scientific Reports , as well as at major conferences including EWSHM, SAHC, and EVACES. His research is applied in projects such as the monitoring of the Vicoforte Sanctuary and the development of the CAMELOT and HY-LEARN toolboxes. Research Projects: MONITORAGGIO VICOFORTE (2024–2026) – Member of Research Group CAMELOT – PoC Transition (2023–2024) – Member of Research Group HY-LEARN – Model Calibration via Hybrid Simulation and ML (2022–2024) – Scientific Manager (PNRR Mission 4) He teaches in various programs, including as a course collaborator in PhD, Master’s, and Bachelor’s level courses such as Earthquake Engineering , Structural Consolidation , and Seismic Risk of Cultural Heritage . He is also an inventor on national and international patents and software related to the CAMELOT toolbox, highlighting the translational impact of his research. He has no listed scientific awards or formal advisees in the provided text.

Hau-Tieng Wuمشاهده پروفایل

استاد

• Applied Mathematics
• Manifold Learning
• Diffusion Maps
• +۴ مورد دیگر

Hau-Tieng Wu is affiliated with Duke University , where he conducts research in applied mathematics and machine learning, with a focus on diffusion-based methods for nonstationary time series and biomedical signals. His work centers on diffusion maps , manifold learning , and spatiotemporal analysis , particularly applied to hemodynamic monitoring via arterial blood pressure (ABP) signals. He has contributed to theoretical advances such as L^∞ spectral convergence and robustness to heterogeneous and colored noise in manifold learning frameworks. While no specific publications or students are listed in the provided text, his research intersects with computational physiology, kernel methods, and geometric data analysis. He has presented his work in academic seminars, indicating active engagement in the applied math and data science communities. No awards, grants, emails, or team information are available in the current data.

Michael Britoمشاهده پروفایل

مدرس

• Digital Marketing
• Social Media Strategy
• Brand Communications
• +۱۲ مورد دیگر

Michael Brito is a Lecturer in Mass Communications and Social Media at the School of Journalism and Mass Communications, College of Humanities and the Arts, San José State University. He is also a seasoned industry leader, currently serving as the Global Head of Data + Intelligence at Zeno Group, where he leads a 50-member analytics team supporting global clients in B2B, consumer, technology, and healthcare sectors. His academic and professional work bridges digital marketing, brand strategy, and data-driven communications. Michael’s research interests include digital marketing, social media strategy, brand communications, narrative intelligence, audience segmentation, and AI applications in PR. He is a recognized thought leader with extensive publications and blog posts exploring brand archetypes, earned media, customer engagement, and the future of digital storytelling. His work emphasizes the integration of data analytics into strategic communications to enhance brand visibility and audience connection. The trends in his recent articles reflect a strong focus on artificial intelligence in public relations, media intelligence, narrative analysis, and the evolution of digital customer journeys. His writings analyze tools like Pulsar and Cision, explore generative AI in search, and critique traditional metrics like earned media value, advocating for more sophisticated, insight-driven approaches. Top 50 Social Intelligence Pioneers by The Social Intelligence Lab Dashboard 25 Class of 2022 by PRWeek Top 25 Digital PR Innovators by PRovoke Media Michael Brito mentors students in digital communications and advises on strategic brand development. He has led major initiatives in media monitoring, social intelligence, and data-informed PR outreach. He founded and contributes to a widely-read blog on social media marketing and is a frequent speaker at industry events, including TEDx. He is also a proud U.S. Marine veteran, bringing leadership and discipline to his academic and professional roles. He is actively involved in the COMM+ lab at SJSU and supports student media through his teaching and mentorship. His work continues to influence both academic curricula and industry best practices in digital communications and brand analytics.

Eunice Eunhee Jangمشاهده پروفایل

استاد

• Language Assessment
• Educational Measurement
• Program Evaluation
• +۸ مورد دیگر

Dr. Eunice Eunhee Jang is a Professor in the Department of Applied Psychology and Human Development at the Ontario Institute for Studies in Education (OISE), University of Toronto. Her research focuses on synergistic learner modeling, dynamic assessment systems, and the intersection of language testing with educational measurement. PhD with specializations in language testing, educational measurement, and program evaluation Develops interactive digital assessment interfaces for struggling readers Author of "Focus on Assessment" (2014) and co-author of OECD Reviews on Evaluation and Assessment in Education Research Interests Dr. Jang's work explores prismatic assessment analytics to understand learner potential and predict learning pathways. She integrates natural language processing and machine learning to create diagnostic feedback systems that support cognitive, metacognitive, and affective growth in technology-rich classrooms. Scientific Awards Jacqueline Ross TOEFL Dissertation Award Caroline Clapham IELTS Master’s Award Tatsuoka Measurement Award Professional Contributions She has served on major advisory boards including EQAO provincial assessments and TOEFL Committees of Examiners. Currently, she is an elected board member for the International Language Testing Association and contributes to the Broader Measures of Success Advisory Committee for People for Education.

• Open Research
• Open Scholarship
• Scholarly Communication
• +۳ مورد دیگر

Demmy Verbeke serves as Senior Lecturer in Open Research at KU Leuven's Faculty of Arts while simultaneously holding leadership positions within KU Leuven Libraries. He heads Artes, the department responsible for collections and services for Humanities and Social Sciences, contributing to the strategic leadership of KU Leuven Libraries as a whole through his membership on the management team. Verbeke earned his PhD in Linguistics and Literature: Latin and Greek from KU Leuven in 2005 with a dissertation on Latin letters and poems in 16th-century music editions. Prior to joining the library in 2012, he worked as a project manager in the heritage sector and as a postdoctoral researcher focusing on Renaissance humanism in the Low Countries and British Isles, multilingualism, book history, and the classical tradition. His research centers on scholarly communication and digital scholarship in the humanities, with particular emphasis on non-profit and community-driven forms of academic publishing. Verbeke's work explores how libraries can adapt to evolving scholarly communication models while maintaining equitable access to knowledge. He investigates the role of academic libraries in supporting open science infrastructure and sustainable publishing models that serve scholarly communities rather than commercial interests. Analysis of his recent publications reveals a consistent focus on transformative library practices, open access funding models, and the evolving role of academic libraries in scholarly communication. His work spans theoretical examinations of open scholarship principles and practical implementations of fair open access initiatives, with growing attention to cybersecurity challenges facing digital library infrastructure. Verbeke actively contributes to open science governance as a member of KU Leuven's Open Science Task Force, coordinator of the Open Science working group on scholarly publishing futures, and co-manager of the KU Leuven Fund for Fair Open Access. He serves on national and international advisory boards including Open Library of Humanities and Open Book Collective, demonstrating significant influence in shaping open access infrastructure. As head of Artes, he leads library services specifically tailored to humanities scholars while advancing digital scholarship initiatives. His dual appointment uniquely positions him to bridge library practice and academic research, fostering collaborations between library professionals and humanities scholars to develop innovative research support services that address the specific needs of humanities scholarship in the digital age.

• Computer Science
• Virtual Reality
• Scientific Visualization
• +۵ مورد دیگر

David H Laidlaw is a Professor of Computer Science at Brown University, specializing in virtual reality, scientific visualization, and medical imaging. His work spans interdisciplinary applications in neuroscience, biomedical research, and educational tools. Brown University Affiliation Department of Computer Science His research focuses on: Immersive visualization for complex data analysis Diffusion MRI and neuroimaging techniques Human-computer interaction in virtual environments 3D interaction methods for scientific exploration Collaborative visualization tools for multidisciplinary teams Recent trends in his publications highlight advancements in: Graph neural networks for biomedical data Memory-efficient segmentation algorithms Perceptual studies in VR environments Annotation and analysis of placental vasculature Technological innovations in foot dynamics research He teaches courses in virtual reality design and scientific visualization, including: CSCI 1370 - Virtual Reality Design for Science CSCI 1951S - Virtual Reality Software Review CSCI 1951T - Surveying VR Data Visualization Software CSCI 2370 - Interdisciplinary Scientific Visualization

• Medical Image Processing
• Biomedical Computing
• Computer Vision
• +۳ مورد دیگر

Björn Menze is a Professor in the Chair of Computer Science Applications in Medicine at the Technical University of Munich (TUM). His research focuses on interdisciplinary applications of computer science in healthcare, particularly medical image analysis and biomedical computing. Institution: Technical University of Munich (TUM) Department: Chair of Computer Science Applications in Medicine His work bridges computer science and medicine, emphasizing machine learning and AI-driven solutions for medical imaging challenges. Detailed publications and awards are not included in the provided text.

• Data Mining
• Machine Learning
• Relational Learning
• +۱۲ مورد دیگر

Jennifer Neville is a Senior Principal Researcher at Microsoft Research Redmond and holds the Samuel Conte Chair Professor of Computer Science and Statistics at Purdue University. With over 100 publications and 10K citations, her research spans data mining, machine learning, and AI algorithms for relational and networked domains including social networks, epidemiology, and web analytics. Education: BS in Computer Science, University of Massachusetts Amherst (2000) MS in Computer Science, University of Massachusetts Amherst (2004) PhD in Computer Science, University of Massachusetts Amherst (2006) Her work focuses on relational learning techniques that exploit connections between entities to enhance pattern discovery. Recent research explores large language models (LLMs), emphasizing alignment with user intent through interaction at scale, while addressing statistical biases from graph structures. Selected scientific awards include the NSF Career Award (2012), ICDM Best Paper (2009), and IEEE’s 10 to Watch in AI (2008). She served on the AAAI Executive Council (2015-2018) and chaired multiple conferences including SIAM Data Mining (2019) and ACM Web Search (2016). Contact: neville@cs.purdue.edu jenneville@microsoft.com

Paolo Rotaمشاهده پروفایل

استادیار

• Computer Vision
• Machine Learning
• Multimodal AI
• +۹ مورد دیگر

Paolo Rota is a tenure-track Assistant Professor at the University of Trento, affiliated with the Department of Information Engineering and Computer Science (DISI) and the Center for Mind/Brain Sciences (CIMeC). His research lies at the intersection of computer vision, machine learning, and multimodal AI, with a strong emphasis on vision-language models and activity recognition. His research interests include zero-shot action recognition, temporal action localization, open-world recognition, and person image synthesis. He explores how large multimodal models can be leveraged for practical applications in video analytics and industrial AI, often developing training-free or source-free adaptation methods that improve model generalization. Recent publications show a consistent trend in utilizing large vision-language models (e.g., CLIP, LMMs) for tasks such as image classification, domain adaptation, and action recognition, emphasizing simplicity, zero-shot capabilities, and real-world applicability. His work frequently appears in top venues including CVPR, NeurIPS, ICCV, and ICIAP. He actively mentors PhD students including Benedetta Liberatori, Jiaqi Liu, Yan Shu, Shiyao Xu, and Alessandro Conti, often co-advising with faculty such as Elisa Ricci and Nicu Sebe. He also contributes to teaching, including delivering lectures on machine learning for the MSc in Data Science program. He co-founded Mountain Maps, a startup using AI to enhance outdoor navigation and mountain exploration. His work bridges academic research and practical innovation, aiming to increase the real-world impact of AI systems.

Arun Raiمشاهده پروفایل

استاد

• Information Systems
• Digital Innovation
• Artificial Intelligence
• +۴ مورد دیگر

Arun Rai serves as Regents’ Professor and Howard S. Starks Distinguished Chair at Georgia State University's Robinson College of Business, where he co-founded and directs the Center for Digital Innovation. His career spans interdisciplinary research bridging information systems with societal impact through industry-university collaborations across global sectors. His educational foundation includes: Ph.D. from Kent State University MBA from Clarion University of Pennsylvania M.S. from Birla Institute of Technology & Science Rai's research explores digital innovation , AI governance , and societal impacts of technology through investigations of platform ecosystems, supply chain transformation, and digital solutions for poverty and health disparities. His work uniquely connects technical systems design with behavioral and organizational outcomes across contexts from rural India to global corporations. Recent publications (2023-2025) reveal intensifying focus on AI-human collaboration , digital risk assessment , and platform governance tensions , with growing emphasis on healthcare applications and equity implications. The trajectory shows evolution from organizational IT adoption toward complex sociotechnical systems addressing global challenges. His scientific recognition includes: Fellow of the Association for Information Systems Distinguished Fellow of the INFORMS Information Systems Society LEO Award for Lifetime Exceptional Achievement Rai has mentored over 60 doctoral students (30+ as chair) with alumni now holding leadership positions globally. His research attracts major funding from Apollo Hospitals, China Mobile, IBM, Intel, UPS, and federal agencies, enabling real-world implementations like the Global Supply Chain Solutions Program during UPS's digital transformation. Current initiatives focus on generative AI in education and healthcare IT policy impacts. As director of the Center for Digital Innovation, he cultivates cross-sector partnerships advancing digital transformation through collaborative research on AI governance, platform ecosystems, and societal impact measurement.

Amine Mhedhbiمشاهده پروفایل

استادیار

• Data and Information Management
• Graph Databases
• Artificial Intelligence Systems
• +۳ مورد دیگر

Amine Mhedhbi is an Assistant Professor at Polytechnique Montréal , where he leads the Data & AI Systems Lab . He earned his PhD in 2023 from the University of Waterloo. His work bridges data management , graph databases , and AI systems , with a focus on performance, debuggability, and user interface design for data applications. Education : PhD (University of Waterloo, 2023) Research Interests center on modern analytical data systems , including multimodal data management , language model integration , and graph query optimization . His projects like FLockMTL and GraphflowDB aim to combine semantic analysis, AI, and traditional database operations. Scientific Awards include the NSERC Discovery Grant , the Cheriton School Distinguished Dissertation Award , the VLDB Best Paper Award , and fellowships from Microsoft and Meta . Key Collaborations : Semih Salihoğlu, Jimmy Lin, Elena L. Glassman Labs & Teams : Affiliated with DAIS Lab , IVADO , and co-founded the applied research team at Distyl AI in 2023.

Lukas Engelmannمشاهده پروفایل

مدرس ارشد

• History of Epidemiology
• History of Science and Medicine
• Digital Health
• +۷ مورد دیگر

Lukas Engelmann is a Senior Lecturer at the University of Edinburgh , specifically within the Science, Technology and Innovation Studies department under the School of Social and Political Science . His research focuses on the history and sociology of biomedicine , with particular interest in epidemiological reasoning , visual cultures of disease , digital epidemiology , and decolonial approaches to medical history . The Epidemy Lab , which he founded, explores the historical development of epidemiology and its contemporary influence on data-driven public health and pandemic policy-making . Engelmann's work has been funded by prestigious grants including an ERC Starting Grant (2021-2025) for his research on the history of epidemiological reasoning, and support from the Wellcome Trust for projects examining the social dimensions of digital health . His book 'Mapping AIDS' (2018) established him as a leading scholar in medical visualization , while 'Sulphuric Utopias' (2020) with Christos Lynteris explores the technological history of maritime sanitation and its political implications. Recent publications emphasize the visual and data practices that have shaped epidemiology, including works on epidemic modeling during the COVID-19 pandemic , the history of plague mapping , and the ethical implications of digital phenotyping . He has also contributed to interdisciplinary discussions on syndemics , co-infection epistemology , and the commercialization of bacteriology in the early 20th century. His scientific contributions have earned recognition through editorial roles in journals like Big Data and Society , and collaborative projects such as 'Working with Diagrams' (2022) which investigates the epistemological role of visual tools in medical knowledge production. Scientific Awards and Funding: ERC Starting Grant (2021-2025) Wellcome Trust Institutional Support Fund British Academy/Leverhulme Small Research Grant Chancellor's Fellowship (University of Edinburgh) 'Sulphuric Utopias' listed in The Guardian's 30 Books to Understand the World (2020)

Madison Loreمشاهده پروفایل

استادیار

• Urban Planning
• Data Analytics
• Sustainable Transitions
• +۱۲ مورد دیگر

Madison Lore is an incoming Assistant Professor in the Department of City and Regional Planning at Cornell University's College of Architecture, Art, and Planning, beginning her tenure in January 2026. Her interdisciplinary research integrates urban planning, data science, and sustainability, focusing on how large-scale data and information environments shape public behaviors and perceptions around sustainable transitions in housing, transportation, and energy systems. She holds a Ph.D. from the School of Community and Regional Planning at the University of British Columbia, a Master's in Applied Mathematics, and a dual Bachelor's in Mathematics and Physics from Rensselaer Polytechnic Institute. Her academic journey reflects a strong technical foundation applied to pressing urban challenges. Madison’s research interests span urban data science, machine learning, infrastructure and land use planning, social policy, and sustainable transportation. She investigates how algorithmic and data-driven methods can be used responsibly to uncover social norms, institutional influences, and individual support for sustainable policies, particularly in contexts of information overload. Her recent publications demonstrate a strong trajectory in applying hybrid deep learning and natural language processing to urban text data, evaluating equity in public mobility, and modeling transportation preferences through digital footprints. These works reflect a consistent theme: leveraging data analytics to promote equitable and sustainable urban futures. Vanier Canada Graduate Scholarship (2023–2026) Bombardier Sustainable Transportation Fellowship (2022) The Bill and Nancy Siegmann Applied Mathematical Modeling Prize (2018) Leonhard Euler Award for Excellence in Mathematical Modeling (2016) Climate Social Science Network Grant on Big Oil’s Climate Disinformation (2024) Madison has presented her work at major conferences including the Association of Collegiate Schools of Planning, the International Conference on Travel Behavior Research, and the American Planning Association National Conference. While no formal advisees are listed, her role as an incoming assistant professor suggests future mentorship of graduate students in urban planning and data analytics. She is affiliated with the PLACE Lab and brings expertise from prior work in nuclear physics and applied mathematics into her current urban sustainability research.