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Ziming LiuView profile

Professor

• Digital Libraries
• Information Behavior
• Scholarly Communication
• +6 more

Dr. Ziming Liu is a Professor at the School of Information, San José State University , where he has been a core faculty member since 2000, advancing from Assistant to Full Professor by 2010. He holds a Ph.D. in Library and Information Studies from the University of California, Berkeley (1996), and an M.S. from Zhongshan University, China (1990). Ph.D., Library and Information Studies, University of California, Berkeley (1996) M.S., Library and Information Science, Zhongshan University, China (1990) His research focuses on digital reading, digital libraries, information behavior, and scholarly communication . He has extensively studied how users interact with digital versus print materials, gender differences in online reading, and the evolution of documents in the digital age. His 2008 book, From Paper to Digital: Documents in the Information Age , is a seminal work in the field. His research on digital reading has been featured in major media outlets such as The Washington Post , The Guardian , and Scientific American . The recent scholarly output (2022–2023) shows a continued focus on digital reading behavior , particularly how social media and digital distraction affect reading practices. His work combines empirical user studies with theoretical insights into information behavior, often using comparative and cross-cultural methodologies. The publications appear in leading journals like Journal of Documentation and Information Processing and Management , reflecting sustained scholarly impact. There are no mentions of scientific awards or honors in the provided text. Dr. Liu has taught key courses including INFO 200 – Information Communities , INFO 275 – Library Services for Racially and Ethnically Diverse Communities , and INFO 287 – Seminar in Information Science Education . While no specific students are listed, his role as a professor and publication record imply graduate student mentorship. He has not held administrative or part-time roles, and there is no indication of lab or team leadership in the text.

Huaizu JiangView profile

Assistant Professor

• Computer Vision
• Computer Graphics
• Natural Language Processing
• +5 more

Huaizu Jiang is an Assistant Professor at Khoury College of Computer Sciences, Northeastern University. His research bridges computer vision, graphics, and natural language processing to develop AI systems that understand and reconstruct 3D visual environments. Prior to joining Northeastern, he was a Postdoc Researcher at Caltech and Visiting Researcher at NVIDIA. He holds a Ph.D. from UMass Amherst (advised by Prof. Erik Learned-Miller), and M.E./B.E. degrees from Xi'an Jiaotong University. His research focuses on fundamental challenges in 3D scene understanding, including geometry reconstruction, semantic interpretation, novel view synthesis, motion generation, and optical flow estimation. Core interests span video processing, human-object interactions, multimodal reasoning, and efficient edge-device implementations. Recent publications emphasize diffusion models for motion/scene generation, transformer-based 3D perception, and video interpolation. Key trends include multi-view consistency techniques, text-to-3D synthesis, and efficient real-time algorithms for robotics applications. Awards & Honors: Winner of the VQA Challenge 2020 He advises 15+ graduate students on projects spanning 3D reconstruction, motion synthesis, and vision-language models. His group collaborates with institutions like NVIDIA and Caltech, focusing on generative AI for dynamic scene understanding.

Eva CetinicView profile

Researcher

• Deep Learning
• Explainable AI
• Digital Art
• +5 more

Dr. Eva Cetinic is a DSI Bridge Postdoc Fellow at the University of Zurich, conducting research at the intersection of deep learning, explainable AI, and digital art and humanities. Previously, she held postdoctoral positions at Durham University and the Center for Digital Visual Studies at the University of Zurich, and worked as a Professional Associate and Postdoc at the Rudjer Boskovic Institute in Croatia from 2015 to 2021. Her educational background includes: PhD in Computer Science, University of Zagreb (2019) Dr. Cetinic's research focuses on computational image understanding and multimodal learning for visual art and culture, investigating how text-image models encode socio-cultural patterns and impact artistic creation. Her work critically examines ethical and societal implications of AI while bridging computer science, digital humanities, and art history through interdisciplinary methodologies. Her publication trends (2019-2025) reveal concentrated analysis of generative AI's cultural impact, particularly text-to-image systems. She systematically investigates bias propagation (gender, cultural), user interaction dynamics, and creative processes while developing technical frameworks for art analysis - moving beyond technical capabilities to address real-world implications in artistic and cultural contexts. She currently leads the UZH-funded project 'From Hype to Reality: Artificial Intelligence in the Study of Art and Culture' in collaboration with the University of Cambridge, establishing cross-institutional frameworks for responsible AI adoption. Her research methodology emphasizes practical implementation within humanities workflows through international networks like DARIAH. As a DSI Bridge Postdoc Fellow, Dr. Cetinic operates within the University of Zurich's Digital Society Initiative ecosystem, connecting computational research with the Center for Digital Visual Studies and global digital humanities infrastructures to examine AI's transformative role in cultural production and interpretation.

Eunice Eunhee JangView profile

Professor

• Language Assessment
• Educational Measurement
• Program Evaluation
• +8 more

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
• +3 more

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
• +5 more

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

• Quantum Engineering
• Quantum Optics
• Photonics
• +3 more

Rachel N Clark is a Lecturer in the School of Physics at the University of Bristol, actively contributing to the Quantum Engineering Technologies research group with a focus on quantum photonics and quantum light source development. Education: Master of Physics (MPhys) Master of Science (MSc) Doctor of Philosophy (PhD) Her research spans Quantum Engineering , Quantum Optics , and Photonics with concentrated expertise in solid-state quantum emitters—particularly aluminum nitride color centers—and single photon source engineering. Key investigations include evanescent-field photon collection enhancement, room-temperature quantum emitter characterization, and nanofabrication of quantum photonic devices for improved efficiency and integration. Analysis of her 13 publications (2022-2025) reveals dominant trends in aluminum nitride quantum emitter development, with 60% of works addressing room-temperature quantum light sources and photon collection efficiency. Her research bridges fundamental quantum optics with practical quantum technology applications, emphasizing scalable fabrication methods and metrology standards for quantum photonic systems. No scientific awards were documented in the provided materials. Information regarding graduate students, research grants, or specific laboratory teams beyond her Quantum Engineering Technologies affiliation was not indicated in the source texts.

• Medical Image Processing
• Biomedical Computing
• Computer Vision
• +3 more

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
• +12 more

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 RotaView profile

Assistant Professor

• Computer Vision
• Machine Learning
• Multimodal AI
• +9 more

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.

Robert Dodds Jr.View profile

Research Professor

• Fracture Mechanics
• Computational Mechanics
• Structural Engineering
• +7 more

Robert Dodds Jr. is a Research Professor in the Department of Civil and Environmental Engineering at the University of Tennessee, Knoxville, within the Tickle College of Engineering. His work is centered on fracture mechanics, computational modeling of crack growth, and material failure in advanced alloys and functionally graded materials. His research interests include: Fracture and failure analysis in ductile and brittle materials Cohesive zone modeling and delamination in aluminum-lithium alloys 3D finite element modeling of crack propagation under small-scale yielding Thermomechanical and cyclic plasticity modeling Fracture in functionally graded materials with mixed-mode loading The analysis of his publications from 2002 to 2018 reveals a strong focus on computational fracture mechanics, particularly on cohesive models, T-stress effects, and delamination in aerospace-grade materials. His work bridges experimental validation with high-fidelity simulations, emphasizing engineering applications in structural integrity. His scientific awards include: National Academy of Engineering George R. Irwin Medal (ASTM) Fracture Mechanics Medal (ASTM) Nathan M. Newmark Medal (ASCE) Walter L. Huber Award (ASCE) Fellow, Engineering Mechanics Institute (ASCE) Dr. Dodds has collaborated extensively with researchers such as C. Ruggieri, M. Messner, A. Beaudoin, J. Sobotka, and G. Paulino. While no formal list of advisees is provided, his mentorship is evident through co-authored student-level research. He has not mentioned specific grants or funding sources in the provided text. His research likely involves a computational mechanics lab or research group focusing on fracture simulation and material modeling, though no lab name is specified.

Arun RaiView profile

Professor

• Information Systems
• Digital Innovation
• Artificial Intelligence
• +4 more

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 MhedhbiView profile

Assistant Professor

• Data and Information Management
• Graph Databases
• Artificial Intelligence Systems
• +3 more

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 EngelmannView profile

Senior Lecturer

• History of Epidemiology
• History of Science and Medicine
• Digital Health
• +7 more

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 LoreView profile

Assistant Professor

• Urban Planning
• Data Analytics
• Sustainable Transitions
• +12 more

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.