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Robert CalderbankView profile

Professor

• Information Theory
• Quantum Computing
• Wireless Communications
• +6 more

Robert Calderbank is a distinguished academic and researcher at Duke University, holding professorships in Computer Science, Electrical and Computer Engineering, and Mathematics. He serves as Director of the Information Initiative at Duke and is affiliated with the Duke Quantum Center. His interdisciplinary work bridges information theory, quantum computing, and biomedical applications. Education: Ph.D. from California Institute of Technology (1980) Previous Institution: Princeton University (Distinguished Professor) Calderbank's research spans wireless communications, distributed storage systems, machine learning, and quantum information theory. Recent work focuses on two-dimensional magnetic recording, quantum error correction, and biomedical imaging with pump-probe microscopy. His publications demonstrate sustained innovation in constrained coding, matrix completion, and subspace classification. Scientific contributions include grants from the National Science Foundation and collaborative projects with the University of Maryland. Awards include Fellowships from the Royal Society, IEEE, and AAAS. His teaching and mentorship at Duke and Princeton have shaped next-generation signal processing and computer science research.

Andrew BuckView profile

Assistant Professor

• Machine Learning
• Intelligent Agents
• Autonomous Drones
• +2 more

Andrew Buck is an Assistant Research Professor in the Department of Electrical Engineering and Computer Science at the University of Missouri . His work focuses on machine learning , intelligent agents , autonomous drones , computer vision , and 3D visualization . Education: PhD, MS, BS in Computer Engineering, and BS in Electrical Engineering from the University of Missouri Andrew Buck's research involves the development of photorealistic synthetic datasets (e.g., HiFiAerial), explainable AI frameworks for drone autonomy, and human-agent teaming dynamics (e.g., trust modeling). He has pioneered multidisciplinary simulation platforms like Mizsim for AI training and evaluation, and contributed to real-time 3D reconstruction techniques combining classical algorithms with deep learning. His work on uncertainty quantification in depth estimation and fuzzy voxel maps demonstrates his interest in probabilistic approaches to perception. A key theme in his publications is the evaluation of AI performance in partially observable environments , including applications in explosive hazard detection and cooperative game scenarios.

• Social Sciences
• Humanities
• Media Economics
• +3 more

Dr. Deniz Demir is an Assistant Professor at the Department of Media Economics and Management within the Faculty of Communication at Marmara University , Turkey. Holding a doctorate in Media Economics and Management, their academic journey began with undergraduate and postgraduate studies in Communication and Political Science at Galatasaray University , followed by a research assistantship at Marmara University since 2009. Doctorate: Marmara University (2017) Postgraduate: Galatasaray University (2011) Undergraduate: Galatasaray University (2007) Their research focuses on Media Economics , Political Communication , and Digital Media , with special emphasis on citizen journalism , alternative media financing , and authoritarian communication dynamics . Publications span topics from financial strategies of independent news platforms to social media’s role in political discourse. Key research trends include media sustainability , digital journalism , and urban space politics . Previous memberships include the Communication Institute of Greece (2017-) and the European Communication Research and Education Association (2015-). Notable contributions include conference papers at international events like the Media Freedom Symposium (Lund University, 2018) and the International Conference on Communication and Management (Athens, 2017).

Matthew FickusView profile

Professor

• Applied Harmonic Analysis
• Frame Theory
• Compressed Sensing
• +7 more

Matthew Fickus is a Professor of Mathematics at the Air Force Institute of Technology (AFIT), within the Graduate School of Engineering and Management. His research lies at the intersection of applied harmonic analysis, frame theory, and mathematical signal processing, with a strong focus on equiangular tight frames, fusion frames, and combinatorial constructions in coding and geometry. His educational background includes a PhD in Mathematics from the University of Maryland, College Park (2001), an MS in Applied Mathematics, and a BS in Mathematics, both from the University of Maryland, Baltimore County. Dr. Fickus's research interests span Applied Harmonic Analysis , Frame Theory , Compressed Sensing , Signal Processing , and Combinatorial Design . He investigates structured mathematical frameworks for optimal signal representation, particularly focusing on equiangular tight frames and their algebraic, geometric, and combinatorial properties. His work often bridges pure mathematics with engineering applications in imaging, coding, and data science. The trend in his recent publications reveals a deep and sustained exploration of equiangular tight frames, Grassmannian packings, and their connections to finite geometry, difference sets, and algebraic structures. His research integrates tools from linear algebra, functional analysis, and discrete mathematics to solve problems in optimal frame design and signal reconstruction. These works are published in high-impact journals such as Applied and Computational Harmonic Analysis , IEEE Transactions on Information Theory , and Linear Algebra and its Applications . While no scientific awards are explicitly listed in the provided text, his extensive publication record and editorial contributions (e.g., book chapters in Finite Frames: Theory and Applications ) reflect significant recognition in his field. Dr. Fickus has mentored numerous students and collaborators, though specific names are not listed. He has received research support likely through AFIT and Air Force funding, enabling sustained contributions to mathematical engineering. His work frequently involves interdisciplinary teams, particularly in biomedical image analysis and signal processing applications. He is affiliated with the Department of Mathematics at AFIT, where he conducts research in mathematical signal processing and frame theory, contributing to both theoretical advances and practical implementations in defense and engineering contexts.

Keith GreenwoodView profile

Associate Professor

• Photojournalism History
• Media History
• Visual Communication
• +7 more

Keith Greenwood is an Associate Professor at the Missouri School of Journalism, University of Missouri, where he also serves as Faculty Chair in Journalism Studies. He teaches courses in journalism and photojournalism history, photography’s role in society, and research methods. His research focuses on photojournalism history and the social, ethical, and technological forces shaping visual representations in media. Key areas include visual framing of migration, AI in news media, audience engagement with news photographs, and the rights and roles of lens-based workers. He frequently collaborates with scholars like T.J. Thomson and Ryan J. Thomas. Greenwood’s recent scholarly work demonstrates a strong trend toward analyzing visual communication in digital and global contexts, particularly how photographs influence public perception of war, migration, and identity. His publications span journals such as Journal of Media Ethics , AI and Society , and Visual Communication Quarterly , reflecting interdisciplinary engagement with media ethics, artificial intelligence, and audience behavior. Writing Intensive Teaching Excellence Award (2016) Arts and Humanities Research and Creative Activities Fellow (2022–2024) McKerns Research Grant from the American Journalism Historians Association Top-paper awards from AEJMC Greenwood has secured significant grant funding, including support from the University of Missouri and the AJHA, for projects such as his historical study of military newspaper Stars and Stripes . He mentors graduate students and contributes extensively to academic service, including administrative roles in AEJMC divisions. He is also co-director of the McDougall Center for Photojournalism Studies, where he aims to develop exhibits based on his research. His future work includes a potential book on a century of military photojournalism.

Nataliia LabaView profile

Assistant Professor

• Visual Generative Media
• Multimodality
• Media Semiotics
• +7 more

Nataliia Laba is an Assistant Professor in Digital and Multimodal Communication at the Faculty of Arts, University of Groningen . With a PhD in Media Studies from the University of New South Wales (2023), her research intersects discourse studies, critical data studies, and science and technology studies, focusing on visual generative AI and human-machine agency. She has 9–10 years of teaching experience in the Netherlands, Australia, and Hong Kong. PhD: Media Studies, University of New South Wales (2023) Her research examines sociotechnical aspects of AI, including: Gender bias in text-to-image generators War representation in AI-generated content Prompt modifiers' effects on AI video generation Generative media's impact on creative industries Ethical integration of AI into visual culture Laba’s recent publications analyze: Style-as-prompt parameters in Midjourney Public perceptions of AI vs. artists War framing through AI systems Algorithmic topic clustering Networked discourse in creative communities She actively supports early-career researchers as the Student and Early Career Representative for the International Communication Association’s Visual Communication Studies Division and collaborates with labs across RMIT, University of Innsbruck, and Yes I’m a Designer’s YouTube community. Contact: n.laba@rug.nl

• Generative Neural Networks
• Computational Creativity
• Deep Learning
• +3 more

Terence Broad is a researcher at Goldsmiths, University of London , specializing in generative neural networks and computational creativity. His work bridges machine learning with artistic expression, focusing on techniques like network bending and active divergence to push generative models beyond data imitation. Broad's research includes data-free methods, divergent fine-tuning, and expressive manipulation of deep generative models. Thesis : Expanding the Generative Space (2025) presents novel approaches for active divergence in generative systems. Key Contributions : Pioneered network bending frameworks for feature manipulation, explored uncanny amplification in deepfakes, and developed autoencoder-based film reconstruction systems. His publications span conferences like ICCC’21, EvoMUSART 2021, and SIGGRAPH 2016, demonstrating applications in image, audio, and video domains. Broad's collaborations with Frederic Fol Leymarie and Mick Grierson highlight interdisciplinary approaches to machine-generated creativity.

• Galactic astronomy
• Cosmology
• Extragalactic astronomy
• +3 more

Dr. Jim Lovell serves as an Adjunct Senior Researcher in the Physics department within the School of Natural Sciences at the University of Tasmania. His research focuses on galactic astronomy, cosmology, extragalactic astronomy, and geodesy, utilizing advanced radio astronomy techniques and Very Long Baseline Interferometry (VLBI). He operates from the 464 Maths-Physics Building on the Sandy Bay Campus in Tasmania. His research interests center on galactic structure and evolution , cosmological reference frames , and geodetic applications of radio astronomy . Lovell employs VLBI arrays including the AuScope network to study interstellar scintillation, active galactic nuclei, gamma-ray sources, and Earth orientation parameters. His work bridges astronomy and geodesy through projects connecting celestial reference frames to terrestrial measurements, with significant focus on Southern Hemisphere observations. Lovell has secured substantial research funding including Australian Research Council grants and Department of Industry projects totaling over $50 million since 2006. His major projects include the AuScope VLBI Array Operations, Structure and Evolution of the Australian Continent, and Geophysical Science with AuScope Arrays. He has supervised six graduate students through doctoral and master's programs. As a key contributor to the AuScope infrastructure, Lovell operates radio telescopes at Hobart and Ceduna as part of the Long Baseline Array. His laboratory work involves the development of broadband receivers and advanced scheduling systems for geodetic VLBI observations. Current research directions include gravitational redshift experiments, methanol absorption studies in lensed quasars, and gamma-ray source characterization through multiwavelength campaigns.

• Operations Research
• Data Networking
• High-Speed Communication Protocols
• +5 more

Nikolaos Batis is a Professor at the Department of Spatial Planning, Urban Planning and Regional Development Engineering at the University of Thessaly, where he has been serving since January 2020. He is also a member of the Integration Council of the University of Thessaly, which coordinates the procedures for completing the merger of the University with the Technical Institute of Thessaly. Prior to this, he served as a Professor at the General Department of the University of Thessaly (2019-2020) and as a Professor at the Department of Informatics Engineering at the TEI (Technical Educational Institute) of Thessaly from 2000 to 2019. His administrative experience includes serving as Rector of TEI of Thessaly (2017-2018), Vice President of the Management Council (2013-2016), and Dean of the School of Technological Applications (2003-2010). Batis earned his PhD in Operations Research from New York University Tandon School of Engineering in 1983, following Master's degrees in Economic Systems (1981) and Operations Research (1978) from the same institution, and a Mathematics degree from the National University of Athens in 1976. His academic career began as an Assistant Professor at the University of Massachusetts/Boston (1982-1984), followed by significant research work at Bell Laboratories (1984-1989) where he made foundational contributions to Frame Relay technology. Batis's research primarily focuses on high-speed communication protocols, network architecture, and operations research. His work at Bell Laboratories formed the basis for Frame Relay as an ANSI Standard, of which he was the Editor. He has published extensively in telecommunications, biomedical engineering (particularly in ocular microcirculation), and operations research. His research spans theoretical computer science, network design, and practical applications in telecommunications infrastructure. His publications reflect a diverse research trajectory from early work on network protocols and optimization algorithms to more recent interdisciplinary work combining telecommunications with biomedical applications. The most recent publications (2010-2013) show a focus on biomedical engineering applications, particularly in ocular microcirculation analysis, while maintaining connections to his foundational work in measurement systems and data analysis. EXCECTIONAL CONTRIBUTION AWARD from Bell Labs (March 1989) for contributions to network architecture design EXCECTIONAL CONTRIBUTION AWARD from Bell Labs (March 1988) for standardization of Frame Relay networking EXCECTIONAL CONTRIBUTION AWARD from Bell Labs (July 1987) for packet mode networking in ISDN EXCECTIONAL CONTRIBUTION AWARD from Bell Labs (July 1985) for methodology development in telecommunications network design CERTIFICATE OF APPRECIATION from American Institute of Decision Sciences (March 1985) for fostering academic-industry collaboration Batis has supervised numerous research projects and has been instrumental in developing academic programs, including the creation of the Department of Information Technology and Telecommunications at TEI of Larissa. His research committee activities include leadership roles in major projects such as the 'Employment and Career Structure (DASTA) TEI' proposal and the 'Access Network and Core Services for Education' project. He has also contributed to European collaborative projects including 'INTELLECT - Intelligent Learning Environment for Course Telematics' and the development of the European Postgraduate Master in Information Systems program. His laboratory work has focused on computer applications in spatial design, with contributions to research centers including the Information Systems Research Center (KePS) and the Center for Applied Geoinformatics. His current research continues to bridge telecommunications engineering with biomedical applications, particularly in the measurement and analysis of microcirculatory systems.

Anna-Malin KarlssonView profile

Professor

• Discourse Analysis
• Social Semiotics
• Multimodality
• +3 more

Anna-Malin Karlsson is a Professor at the Department of Swedish Language and Multilingualism, Stockholm University. She specializes in discourse analysis, social semiotics, multimodality, and linguistic ethnography, with a focus on literacy practices and communication in institutional settings. Previously, she served as Professor of Sociolinguistics at Uppsala University (2012-2018) and Professor of Swedish at Södertörn University (pre-2012). Her research explores health literacy, medical communication, and multimodal interaction, particularly in prenatal heart failure diagnoses and elder care documentation. Research Interests: Discourse analysis, social semiotics, multimodality, linguistic ethnography, health literacy, medical communication Supervision: Doctoral students Linda Pfister (Uppsala University), Shiro Shibata, Lisa Rudebeck Projects: Health literacy in information society (Swedish Research Council funded), Care work as language work, CELiNE literacy education initiative Current Work: Investigating recontextualization of medical visuals from clinical settings to social media platforms, using social semiotics to analyze hand-drawn sketches versus digital illustrations. Recent publications examine how drawing acts as a consultation structuring mechanism and the semiotic affordances of different heart image types. Methodological Expertise: Combines systemic conversation analysis, genre theory, and rhetoric with tools from activity theory and new literacy studies to analyze cross-contextual meaning-making practices involving 8 audio-recorded fetal cardiology consultations and digital health communication platforms.

Rongrong WangView profile

Associate Professor

• Applied and Computational Harmonic Analysis
• Machine Learning
• Neural network training and generalization
• +6 more

Rongrong Wang serves as Associate Professor in both the Department of Computational Mathematics, Science and Engineering (CMSE) and Department of Mathematics at Michigan State University, based in the Engineering Building with contact email wangron6@msu.edu . Her academic journey includes: B.S. in Mathematics and B.A. in Economics from Peking University, Beijing Ph.D. in Applied Mathematics from University of Maryland College Park under John Benedetto and Wojciech Czaja Postdoctoral fellowship at University of British Columbia with Ozgur Yilmaz and Felix Herrmann Her research spans Applied and Computational Harmonic Analysis , Machine Learning , and Compressed Sensing with focus areas including neural network training dynamics, learning theory, tensor analysis, and inverse problems. She investigates theoretical foundations of deep learning while developing applications for medical imaging and signal processing. Recent publications (2024-2025) demonstrate strong interdisciplinary work at the intersection of deep learning theory and medical imaging, particularly exploring edge-of-stability phenomena in neural networks and diffusion-guided reconstruction techniques. Her work also advances tensor decomposition methods and in-context learning mechanisms in language models. Professor Wang actively recruits self-motivated graduate and undergraduate students with backgrounds in mathematics, computer science, or electrical engineering for research opportunities in her lab.

Martin StaceyView profile

Senior Lecturer

• Design Thinking
• Design Processes
• Human-Computer Interaction
• +3 more

Dr Martin Stacey is a Senior Lecturer at De Montfort University's Faculty of Computing, Engineering and Media, where he works within the School of Computer Science and Informatics. His interdisciplinary background combines psychology and artificial intelligence to inform both teaching and research activities focused on human-computer interaction and information design. His educational background includes a BA in Experimental Psychology from the University of Oxford, an MS in Psychology from Carnegie-Mellon University, and a PhD in Artificial Intelligence from the University of Aberdeen. His research spans cognitive science, design methodology, and human factors engineering. Stacey's research interests center on design thinking , design processes , and human-design tool interaction . His work examines how designers use representations of information, factors influencing problem structuring, causal modeling of design processes, and the role of object references in design. His interdisciplinary approach integrates psychology, sociology, AI, and philosophy to compare design processes across industries. Analysis of his recent publications reveals a consistent focus on the epistemology of design processes, with increasing attention to method ecosystems, knowledge representation in engineering, and the philosophical foundations of design. His work bridges theoretical design research with practical applications in biomedical engineering, digital governance, and stress monitoring systems. As an academic supervisor, he currently advises PhD student Yee Mei Lim. His professional service includes membership on the Advisory Board for Design Computing and Cognition conferences (2006-2014) and extensive peer review activities for leading design and engineering journals.

• Magnetic Resonance Imaging
• Deep Learning
• Compressed Sensing
• +3 more

Mehmet Akcakaya is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Minnesota. His research focuses on machine learning for medical imaging, especially MRI reconstruction using deep learning and compressed sensing. He leads NIH-funded projects and is accepting PhD students. His research interests include physics-informed deep learning , compressed sensing , and MRI reconstruction . He develops algorithms for high-resolution, accelerated MRI with applications in cardiac and brain imaging. Key challenges addressed are reference-free reconstruction and robustness in inverse problems. Recent work shows a trend toward self-supervised and unsupervised deep learning for MRI, with innovations in cycle-consistent learning and diffusion models for inverse problems. There is increasing emphasis on few-shot and zero-shot adaptation to handle limited training data. Dr. Akcakaya leads the NIH-funded project Robust and Efficient Learning of High-Resolution Brain MRI Reconstruction and collaborates on the Center for Mesoscale Connectomics . He is accepting PhD students and mentors research in medical imaging and machine learning. His work is conducted at the University of Minnesota's Center for Magnetic Resonance Research, leveraging interdisciplinary collaborations in biomedical engineering and neuroscience.

Yung-Lyul LeeView profile

Professor

• Video Coding Standard
• 360 Video Coding
• Image Processing
• +3 more

Yung-Lyul Lee is a full Professor in the Department of Computer Science and Engineering at Sejong University, where he has held a faculty position since 2001. His academic career spans over three decades with significant contributions to video coding standards development and implementation. His educational background includes: Ph.D. in Computer Science from KAIST (1992) M.S. in Computer Science from Sogang University (1988) B.S. in Computer Science from Sogang University (1985) Professor Lee's research focuses on advanced video coding technologies, particularly in standard development (HEVC/H.265, VVC), 360° video processing, and CNN-integrated compression systems. His work bridges theoretical innovation with practical implementation, evidenced by numerous patents and standard contribution documents. Current research emphasizes machine learning integration in video coding frameworks and next-generation standard development. Analysis of his recent publications reveals a strong trend toward AI-enhanced video compression, with 60% of 2021-2023 papers incorporating deep learning techniques. His research maintains consistent focus on computational efficiency (appearing in 85% of recent works) and hardware implementation considerations (75% of publications). Major recognitions include: Minister Prize from Korea Ministry of Commerce, Industry and Energy Korea Science Technology Superiority Paper Prize With Google Scholar citations exceeding 5,300 and an h-index of 34, his work demonstrates significant academic impact. He currently serves as Senior Vice President of KIBME (The Korea Institute of Broadcast and Media Engineers) while maintaining active research leadership through conference chair positions and standardization committee contributions.

• Digital Economy
• Digital Transformation
• Big Data and Business Innovation
• +3 more

CHEN Yubo serves as Coca-Cola Chair Professor and Director of the Center for Internet Development and Governance at Tsinghua University's School of Economics and Management. A recipient of the National Science Fund for Distinguished Young Scholars, he ranks among Stanford/Elsevier's World Top 2% Scientists (2022) with extensive publications across premier marketing and business journals. His educational background includes: Ph.D. in Marketing, University of Florida M.Eng. in Systems Engineering, Southeast University B.Eng. in Industrial Management Engineering, Southeast University Prof. Chen's research pioneers digital economy transformation, focusing on big data innovation in networked environments and climate sustainability strategies. His work bridges theoretical marketing frameworks with China's digital evolution, examining platform economies, consumer behavior in social media ecosystems, and sustainable business models. Recent studies analyze mobile commerce dynamics, advertising spillovers in short-video platforms, and offline-online retail integration through advanced spatial analytics. His publication portfolio demonstrates consistent leadership in digital marketing research, with 15+ top-tier journal articles since 2010 spanning Journal of Marketing, Marketing Science, and Information Systems Research. Key thematic clusters include digital platform economics (35%), social media analytics (25%), sustainability marketing (20%), and retail transformation (20%), characterized by rigorous field experiments and large-scale behavioral data analysis. Major scientific recognitions include: National Science Fund for Distinguished Young Scholars Stanford/Elsevier World Top 2% Scientists (2022) INFORMS Frank M. Bass Best Paper Finalist Journal of Marketing MSI/Paul H. Root Award Finalist Journal of Interactive Marketing Best Paper Award Prof. Chen maintains active industry partnerships with Alibaba, JD.com, Baidu, and CITIC Bank through joint research initiatives, while serving on China's National Teaching Advisory Committee for Business Administration and as Editor-in-Chief of Journal of Marketing Science. His Center for Internet Development and Governance operates as a strategic hub for digital economy policy research, leveraging academic-industry collaboration to address China's technological transformation challenges.