جستجوی استاد راهنمای دانشگاهی

Daryl Fougnie is an Associate Professor of Psychology and Global Network Associate Professor at New York University Abu Dhabi. He is a core faculty member in the Department of Psychology within the College of Arts and Science, actively conducting research and teaching undergraduate courses in cognitive psychology. His research focuses on the fundamental limits of human cognition, particularly in visual perception, attention, and memory. Through psychophysics and computational modeling, the Fougnie Lab investigates how the brain processes and retains visual information, exploring questions about capacity limits, the nature of mental representations, and the interaction between attention and memory. Key areas include visual working memory, attentional selection, retro-cueing, and memory-guided behavior. The 15 most recent publications reflect a strong thematic focus on the probabilistic and resource-constrained nature of working memory, the strategic control of attention, and the neural and cognitive mechanisms underlying perception and memory. Research often employs innovative paradigms such as betting games and reproduction tasks to probe internal representations and decision-making processes. NYUAD Research Enhancement Fund NYUAD Research Enhancement Fund Daryl Fougnie mentors undergraduate students in the Fougnie Lab and supervises capstone research projects in psychology. His lab is actively funded, as evidenced by repeated Research Enhancement Fund awards, and collaborates widely with researchers such as Kartik Sreenivasan, Clay Curtis, and Edyta Sasin. The lab is currently recruiting postdoctoral researchers, indicating ongoing and expanding research activity. The Fougnie Lab at NYU Abu Dhabi serves as a hub for cognitive science research, integrating experimental psychology with computational approaches. It provides research opportunities for undergraduates and fosters collaboration across disciplines, contributing significantly to the understanding of human cognitive architecture.

• Cognitive Psychology
• Visual Perception
• Visual Attention
• +۵ مورد دیگر

Professor Luke Chamberlain is a leading researcher at the Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, where he investigates the role of protein S-acylation in health and disease. His work bridges fundamental biochemistry with therapeutic discovery, focusing on the zDHHC family of enzymes and their impact on cellular signaling, membrane trafficking, and disease mechanisms. Education: PhD in Role of Cysteine-String Protein in Regulated Exocytosis, University of Liverpool (1998) BSc in Microbiology, University of Edinburgh (1994) His research is primarily focused on protein S-acylation (palmitoylation) , a reversible lipid modification that regulates protein localization, stability, and function. He explores how defects in this process contribute to neurodegenerative diseases, cancer, and diabetes. His lab employs advanced techniques such as click chemistry, confocal microscopy, proteomics, and behavioral analyses to dissect molecular mechanisms. The recent publications highlight trends in understanding substrate specificity of zDHHC enzymes , development of inhibitors , and the regulatory role of S-acylation in metabolic and neurological pathways . His work increasingly emphasizes chemical biology approaches to target S-acylation therapeutically. Scientific Awards: No awards explicitly mentioned in the text. Prof. Chamberlain actively mentors postdoctoral researchers and prospective PhD students, offering support for fellowship applications. He is Principal Investigator on multiple grants, including an integrated analysis of S-acylation dynamics (BBSRC-funded) and a Strathclyde-led network with Thailand. His professional activities include serving as an examiner for PhD theses, chairing international conferences such as the FASEB meeting on Protein Lipidation, and participating in research visits to institutions like Tsinghua and Peking University. Labs and Facilities: His research group utilizes the Leica SP8 Confocal Microscope facility at the Strathclyde Institute, enabling high-resolution imaging of protein localization and dynamics in live and fixed cells.

• Protein S-acylation
• Palmitoylation
• Post-translational modifications
• +۱۲ مورد دیگر

Jeffrey R. Gruen is Professor of Pediatrics (Neonatology) and of Genetics at Yale School of Medicine, and a faculty member in the Investigative Medicine Program at Yale Graduate School of Arts and Sciences. His research is affiliated with multiple centers including the Yale Center for Genomic Health, Wu Tsai Institute, and the Yale Child Health Research Center. Professor of Pediatrics (Neonatology), Yale School of Medicine Professor of Genetics, Yale School of Medicine Member, Investigative Medicine Program, Yale Graduate School Principal Investigator, Gruen Lab Education: MD, Tulane University, 1981 BS in Chemistry, Tulane University, 1977 Residency in Pediatrics, Yale-New Haven Hospital, 1984 Internship in Pediatrics, Yale-New Haven Hospital, 1982 Dr. Gruen's research centers on the genetic and molecular basis of dyslexia and language impairments. His lab pioneered the mapping of the DYX2 locus on chromosome 6 and discovered the DCDC2 gene, a major contributor to reading disability. His team identified READ1, a transcriptional control element that modulates risk for dyslexia, and demonstrated synergistic interactions between genetic variants in DCDC2 and KIAA0319 . His work integrates human genetics, molecular biology, and neuroimaging to understand the biological mechanisms underlying learning disabilities. He leads the Yale Genes, Reading and Dyslexia (GRaD) Study and the New Haven Lexinome Project, aiming to enable early diagnosis and personalized educational interventions. The recent publications reflect a strong trend in integrating genetic data with cognitive, behavioral, and educational assessments. Key themes include genome-wide association studies of dyslexia, gene-environment interactions (particularly involving phonological awareness and home environment), phenotype harmonization across cohorts, and the application of genetic findings to educational policy and practice. Imaging genetics and the study of comorbid conditions like Sluggish Cognitive Tempo are also prominent. Scientific Awards: Innovative Research Award, Kavli Institute, 2022 Dr. Gruen has served as Principal Investigator on numerous NIH-funded studies, including the GRaD Study, the Pediatric Imaging NeuroGenetics (PING) Study at Yale, and the New Haven Lexinome Project. He mentors a broad network of collaborators across institutions such as the University of Colorado, University of Bristol, and Johns Hopkins. His lab trains researchers in human genetics, molecular techniques, and cognitive phenotyping. He leads the Gruen Lab, which focuses on human genetic studies, molecular genetic mechanisms, imaging genetics, and longitudinal intervention studies. The lab collaborates extensively with national and international research centers and utilizes advanced techniques including GWAS, sequencing, chromatin immunoprecipitation, and MRI-based phenotyping.

• Genetics of Dyslexia
• Learning Disabilities
• Language Impairment
• +۱۲ مورد دیگر

Bhama Ramkhelawon, PhD, is the Florence and Joseph Ritorto Associate Professor of Surgical Research in the Department of Surgery and Associate Professor in the Department of Cell Biology at NYU Grossman School of Medicine. She is also the Director of Vascular Surgery Scientific Research, leading a dynamic research program focused on vascular biology and disease mechanisms. Her research centers on understanding the molecular and cellular mechanisms underlying vascular aneurysms, peripheral vascular disease, and the interplay between metabolism, inflammation, and aging in the cardiovascular system. Utilizing advanced techniques such as single-cell transcriptomics, mouse models, and clinical data analysis, her lab investigates how immune cells, platelets, and metabolic pathways contribute to vascular pathologies. Recent publications highlight a strong trend in vascular mechanobiology, aging-related transcriptomic changes, adenosine signaling, and inflammatory responses in vascular tissues. Her work bridges basic science with clinical applications, particularly in post-surgical complications like endoleaks and aneurysm repair outcomes. Bhama Ramkhelawon has made significant contributions to the field with over 80 publications in high-impact journals such as Circulation Research , JCI Insight , and Cell Systems . Her research is supported by active clinical trials focusing on vascular aneurysms and peripheral vascular disease, indicating ongoing funding and translational research efforts. She mentors students and researchers as part of her role as a principal investigator and director. Her lab is involved in multi-disciplinary collaborations, integrating cell biology, immunology, and vascular surgery to advance understanding of cardiovascular diseases.

• Vascular Biology
• Cardiovascular Disease
• Inflammation
• +۷ مورد دیگر

Jason Hein is an Associate Professor in the Department of Chemistry at the University of British Columbia's Faculty of Science. His research focuses on the development of automated reaction analysis technology and self-driving laboratories that integrate robotics with synthetic organic chemistry. Dr. Hein leads the Hein Lab, which pioneers innovative solutions for mechanistic organic chemistry, catalytic reaction mechanisms, and chemical manufacturing processes. His research interests center on creating modular robotic tools and integrated analytical hardware for automated reaction profiling, with applications in pharmaceutical manufacturing, battery materials processing, and sustainable chemistry. The lab's work combines advanced robotics, artificial intelligence, and process analytical technology to develop self-optimizing chemical systems that accelerate discovery and improve manufacturing efficiency. Analysis of Hein's recent publications reveals a strong focus on AI-driven laboratory automation, with particular emphasis on crystallization optimization for battery materials, computer vision for process monitoring, and interoperable software systems for self-driving laboratories. His work bridges fundamental mechanistic understanding with practical industrial applications, particularly in lithium extraction from waste brines and pharmaceutical process development. NSERC Postdoctoral Fellowship Dr. Hein's research program includes significant grant funding supporting the development of self-driving laboratory technologies and their application to challenging chemical problems. His lab actively collaborates with industry partners in pharmaceuticals and clean energy sectors to translate fundamental insights into deployable technologies. Current projects focus on battery-grade lithium carbonate production, continuous manufacturing processes, and AI-optimized chemical synthesis. The Hein Lab operates as a multidisciplinary research environment combining expertise in organic chemistry, robotics engineering, computer science, and data analytics to create the next generation of autonomous chemical discovery systems.

• Mechanistic Organic Chemistry
• Automated Reaction Analysis
• Self-Driving Laboratories
• +۷ مورد دیگر

Martin Rajman is a Senior Scientist at École Polytechnique Fédérale de Lausanne (EPFL) with multiple affiliations across the institution. He holds positions in the School of Computer and Communication Sciences (SIN - Teaching, SCI IC MR Group, SSC - Teaching) as well as in the Vice Presidency for Strategic Development (VPS Artificial Intelligence) and the Vice Presidency for Academic Affairs (SNAI Administration). He serves as the Executive Director of Nano-tera.ch, a large Swiss Research Program funding collaborative multi-disciplinary projects in Health and the Environment. Rajman's research spans the intersection of artificial intelligence, natural language processing, and information retrieval. His work demonstrates a consistent focus on developing practical applications of computational linguistics and machine learning techniques. Early in his career, he contributed significantly to syntactic parsing, stochastic language models, and vector space representations for text. More recently, his research has expanded into deep learning applications for 3D reconstruction, empathetic conversational agents, and distributed analytics systems. His publications reveal a trajectory from foundational NLP research toward increasingly applied and interdisciplinary work connecting AI with healthcare, environmental monitoring, and human-computer interaction. Analysis of his recent publications (2015-2024) shows a clear evolution toward more applied AI research with strong interdisciplinary connections. While maintaining his core expertise in natural language processing and information retrieval, his work has expanded into computer vision, healthcare applications, and sustainable computing. The publications demonstrate increasing collaboration across disciplines, with applications in medical imaging, mental health support systems, environmental monitoring, and human-centered AI. His leadership role in the Nano-tera.ch program reflects this interdisciplinary approach, connecting computing research with real-world challenges in health and environmental contexts. Rajman has mentored several PhD students including Ailomaa Marita, Eckard Emmanuel, Melichar Miroslav, and Veselý Martin. His research has been supported through the Nano-tera.ch program, which has funded more than 100 research projects with over 95 million CHF in public funding. He has also managed more than 20 European projects during his tenure as Director of the EPFL Global Computing Center. As Executive Director of Nano-tera.ch, Rajman leads a significant research initiative connecting EPFL with national and international partners. His work bridges academic research with industry applications, notably through collaborations with eBay on product ranking technology and with Elsevier on article recommendation systems. His leadership extends to managing large-scale research programs while maintaining an active research agenda and mentoring the next generation of computer scientists.

• Artificial Intelligence
• Computational Linguistics
• Natural Language Processing
• +۷ مورد دیگر

Professor Siegfried Handschuh holds dual academic appointments as Associate Professor at the University of Passau and Ordinary Professor for Data Science at the University of St. Gallen. His research spans semantic technologies, information linguistics, and artificial intelligence applications in the humanities, with significant funding from the EU, Science Foundation Ireland, and Enterprise Ireland. His research focuses on making big data workable for humanities scholars through innovative AI approaches. Handschuh's work addresses critical challenges in digital humanities including inconsistent and non-integrated data with varying quality. His research interests encompass semantic technologies, information linguistics, information extraction, and distributional semantics, with particular emphasis on applying AI to art history and cultural heritage. Handschuh has coordinated numerous international research projects including the Digital Aristotle project initiated by Microsoft founder Paul Allen, which aimed to develop AI-powered educational tools. His Neoclassica project teaches machines to recognize neoclassical objects through formal language processing, while the PACE initiative establishes the Passau Centre for eHumanities as a research hub. Other significant projects include EU-Project MARIO for healthy aging with care robots and various studies on human-machine interaction. His scientific contributions focus on developing new tools for humanities researchers that leverage artificial intelligence to uncover novel contexts and relationships in cultural data. Handschuh's work bridges computer science with humanities disciplines, creating practical applications for semantic technologies in cultural heritage analysis.

• Semantic Technologies
• Information Linguistics
• Information Extraction
• +۴ مورد دیگر

Mahdi Soltanolkotabi is a Professor in the Departments of Electrical and Computer Engineering, Computer Science, and Industrial and Systems Engineering at the University of Southern California's Viterbi School of Engineering. He serves as the inaugural Director of the USC Center on AI Foundations for Science (AIF4S). His academic journey includes a Ph.D. in Electrical Engineering from Stanford University (2014) under Emmanuel Candes, followed by a postdoctoral position at UC Berkeley's AMPLAB mentored by Ben Recht and Martin Wainwright. Dr. Soltanolkotabi's research spans both theoretical and applied dimensions of data science. On the theoretical side, he develops mathematical foundations for modern data science, focusing on generative AI, deep learning, machine learning, signal processing, and computational imaging. His work draws upon nonconvex optimization, high-dimensional probability, statistical estimation, empirical processes, and learning theory. On the applied side, he develops reliable AI systems for healthcare and scientific applications, collaborating with physicians and domain scientists to enhance AI reliability, develop new architectures, and create rigorous evaluation frameworks. His recent publications demonstrate strong focus on medical AI applications, image reconstruction, and theoretical foundations of deep learning. His work bridges the gap between theoretical guarantees and practical implementations, particularly in medical imaging where reliability is critical. His research group has made significant contributions to understanding the behavior of nonconvex optimization algorithms in high-dimensional settings. David and Lucile Packard Fellow Information Theory Society Best Paper Award NIH Director's new innovator award Sloan Research Fellowship NSF Career award Airforce Office of Research Young Investigator award (AFOSR-YIP) Viterbi school of engineering junior faculty research award Faculty awards from Google and Amazon Dr. Soltanolkotabi has received multiple research grants including Amazon Research Awards for projects on "Artificial intelligence for fast and portable medical imaging" and "Reliable AI for Generation of Medical Reports from MRI Scans." He actively collaborates with medical professionals and leads educational outreach initiatives with local schools through USC's Viterbi Adopt-a-School program. His work demonstrates a strong commitment to translating theoretical advances into practical healthcare solutions while maintaining rigorous mathematical foundations.

• Machine Learning
• Deep Learning
• Generative AI
• +۷ مورد دیگر

Frank NIELSEN is a Professor at École Polytechnique with expertise in information geometry, data science, and machine learning. He holds a PhD (1996) and HDR (2006) in computer science and has established himself as a leading researcher in geometric approaches to information science. His educational background includes a PhD in computer science (1996) followed by a Habilitation à Diriger des Recherches (HDR) in 2006, the highest academic qualification in France that qualifies one to supervise doctoral candidates. Dr. NIELSEN's research focuses on the Geometric Science of Information , where he develops theoretical frameworks for understanding data through geometric and information-theoretic lenses. His work bridges Computational information geometry Statistical manifold theory Bregman divergences and their applications Machine learning with geometric foundations High-dimensional data analysis He aims to address the challenge of inappropriate data representation in current Data Science by building a theory of Computational Information Geometry to enable Intrinsic Data Science with principled distances. His extensive publication record shows a clear trend toward developing geometric frameworks for understanding statistical divergences, with recent work focusing on Bregman geometry, Fisher-Rao metrics, and their applications in machine learning. His research spans theoretical developments in information geometry to practical implementations like the pyBregMan Python library, demonstrating both theoretical depth and practical relevance. Dr. NIELSEN has made significant contributions through his teaching and publications. He has taught courses at École Polytechnique including INF442, INF517, and INF591. His authored textbooks include Introduction to HPC with MPI for Data Science (2016), A Concise and Practical Introduction to Programming Algorithms in Java (2009), and Visual Computing: Geometry, Graphics, and Vision (2005). He has also edited influential volumes such as Computational Information Geometry for Image and Signal Processing (2016) and Geometric Theory of Information (2014). He actively organizes and participates in academic events, serving on program committees for major conferences including GSI (Geometric Science of Information), CVPR, and ICCV. His work has established him as a key figure in the growing field of geometric approaches to information science.

• Data science
• Geometric science of information
• Information geometry
• +۴ مورد دیگر

Dr. Zhenghao Chen is a Lecturer in Data Science at the University of Newcastle, affiliated with the School of Information and Physical Sciences. He earned his Ph.D. from the University of Sydney in 2022, following a B.Eng. H1 degree from the same institution in 2017. Prior to his current position, Dr. Chen served as a Postdoctoral Research Fellow at the University of Sydney (2022-2024), a Research Engineer at TikTok (2024), and as a Visiting Research Scientist at Microsoft Research and Disney Research (2022-2023). Dr. Chen's educational background includes: Doctor of Philosophy, University of Sydney (2022) Bachelor of Information Technology (B.Eng. H1), University of Sydney (2017) Dr. Chen's research spans multiple domains within artificial intelligence, with particular expertise in Computer Vision, Natural Language Processing, and Machine Learning. His work in Generative AI has garnered significant recognition, with applications in both academic and industrial settings. His research interests are reflected in his Fields of Research percentages: Deep Learning (30%), Computer Vision (30%), Natural Language Processing (20%), and Multimodal Analysis and Synthesis (20%). His publications in top-tier venues like CVPR, ICCV, ECCV, and journals like IEEE TPAMI demonstrate the breadth and impact of his work. Analysis of Dr. Chen's recent publications (2022-2025) reveals a consistent focus on neural compression techniques, 3D perception, and multimodal AI systems. His work spans medical imaging (CXR bone suppression), video compression, point cloud processing, and neural surface reconstruction. A notable trend is his exploration of efficient AI systems that work well under resource constraints, as evidenced by his involvement in the EMCLR workshop. His research often bridges theoretical advances with practical applications across multiple domains. Dr. Chen has received several prestigious awards: Microsoft Research Asia StarTrack Fellowship (2025) ACM SIGMM Award for Outstanding PhD Thesis in Multimedia Computing (2024) Australia Government Research Training Program (RTP) Fellowship (2019) Google Australia Prize for Excellence in Computer Science (2017) Dr. Chen is actively involved in the academic community, serving on the Program Committee for major AI conferences including CVPR, ICCV, ECCV, SIGGRAPH, AAAI, and others. He also organizes workshops in Multimedia and ICCV conferences, and serves as a reviewer for prestigious journals. His teaching responsibilities include courses on Intelligent Visual Signal Understanding, Video Intelligence and Compression, Database and Information Management, and Computing Fundamentals at both the University of Sydney and University of Newcastle.

• Computer Vision
• Natural Language Processing
• Machine Learning
• +۳ مورد دیگر

Dr. Marta Zlatic is a Principal Research Associate at the Department of Zoology , part of the School of Biological Sciences at the University of Cambridge. She leads the Zlatic Lab, focusing on the structural and functional relationships within neural circuits. Her research explores how nervous systems integrate sensory information and prior experiences to enable decision-making, emphasizing learning and memory , sensorimotor transformations , and connectomics . Using Drosophila melanogaster larvae as a model organism, her work combines optogenetics , electron microscopy , and functional imaging to decode circuit principles. Recent publications highlight trends in connectome analysis and behavioural neuroscience , with subfields spanning synaptic architecture , neural network modeling , and genetic manipulation techniques . She collaborates with interdisciplinary teams and maintains active research partnerships at the MRC Laboratory of Molecular Biology. Group members include Bernd Breuer, Nicolo Ceffa, Michael Clayton, and other researchers advancing understanding of Drosophila neurobiology. The lab contributes to Cambridge's Athena Swan Bronze Award initiatives for equality and inclusion in research environments.

• Systems neuroscience
• Circuit mechanisms of behaviour
• Learning and memory
• +۲ مورد دیگر

Holger Knaut is an Associate Professor in the Department of Cell Biology at NYU Grossman School of Medicine . His research focuses on understanding the molecular and mechanical mechanisms underlying collective cell migration, tissue morphogenesis, and cytoskeletal dynamics using zebrafish models and quantitative imaging techniques. Key research areas: Collective cell migration, RhoA signaling, focal adhesions, actin polymerization Methodologies: Genetics, live-cell imaging, biomechanical analysis Notable findings: Discovery of rear traction forces in tissue migration, integration of adhesion codes in pattern formation His publications in top journals like Nature Cell Biology and Science demonstrate his expertise in developmental biophysics and cell signaling regulation. Contact: Holger.Knaut@nyulangone.org

• Collective Cell Migration
• Actin Polymerization
• RhoA Signaling
• +۴ مورد دیگر

Arnab Nandi is a Professor of Computer Science and Engineering at The Ohio State University, with a courtesy appointment in Biomedical Informatics. He holds leadership roles including Steering Committee Member for the Human-in-the-Loop Data Analytics (HILDA) Workshop and has served as Workshops co-chair for SIGMOD 2025-26 and Demonstrations co-chair for SIGMOD 2024. His research focuses on bridging human interaction and data infrastructure, spanning database systems, human-in-the-loop data analytics, and next-generation query interfaces. Nandi's work emphasizes interactive data exploration through projects like DICE (Distributed Interactive Cube Exploration), GestureDB (Querying Beyond Keyboards), and Omni (Multimodal Data Exploration). His recent research explores integrating LLMs into database education, augmented reality interfaces for data analytics, and multimodal approaches to video querying. Nandi has received numerous honors including the NSF CAREER Award, Google Faculty Research Award, IEEE TCDE Early Career Award, and the University's Alumni Award for Distinguished Teaching. He was also named to Columbus Business First's '40 under 40' and became an ACM Distinguished Member in 2024. As an educator, he teaches courses including CSE 3241 (Introduction to Database Systems), CSE 5242 (Advanced Database Systems), and CSE 5251 (Introduction to Software Startups). His educational innovations include DBTutor, which integrates LLMs into database systems education. At Ohio State, Nandi co-founded the OHI/O Program, which fosters tech culture through hackathons, and The STEAM Factory, an interdisciplinary research collaboration network. Prior to academia, he was founder and CEO of Mobikit, a connected vehicles data analytics startup acquired by Azuga Inc. (a Bridgestone company). His research has been supported by the NSF and industry partnerships, with applications spanning precision agriculture (CropFusion), clinical data pipelines (ICARUS), and interactive visualization systems (Perceptvis).

• Database Systems
• Human-Computer Interaction
• Human-in-the-Loop Data Analytics
• +۵ مورد دیگر

Alexander Clarke is an Associate Professor at the University of Oxford's Kennedy Institute of Rheumatology within the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, and serves as an Honorary Consultant Rheumatologist at the Nuffield Orthopaedic Centre. His educational background includes medical qualification from UCL in 2001, rheumatology training in London, and a PhD on autophagy in lupus completed in 2013 under Tim Vyse at King's College London. He joined Oxford in 2014 as a postdoctoral fellow with Katja Simon at the Weatherall Institute of Molecular Medicine before establishing his independent research group in 2018. Clarke's research focuses on the intersection of immunology and metabolism, particularly investigating how metabolic pathways regulate immune cell function in autoimmune diseases. His work primarily examines B cell metabolism, autophagy mechanisms, and their roles in conditions like systemic lupus erythematosus. He leads the Clarke Group dedicated to 'Metabolism and Immunity' research. Analysis of his recent publications (2022-2025) reveals a consistent research trajectory centered on immunometabolism, with particular emphasis on germinal center B cells, mitochondrial regulation in lymphocytes, and connections between metabolic pathways and autoimmune pathogenesis. His work bridges fundamental cellular mechanisms with clinical applications in rheumatology. His major scientific recognitions include: Wellcome Trust Clinical Research Training Fellowship Wellcome Trust Clinical Research Career Development Fellowship (2018) Clarke's research program is supported by prestigious Wellcome Trust funding, enabling his group to investigate critical questions at the interface of immunology and metabolism. His work has significant implications for understanding autoimmune disease mechanisms and developing novel therapeutic approaches targeting metabolic pathways in immune cells. The Clarke Group maintains active research programs investigating how metabolic regulation influences immune cell function, with particular focus on B cells in germinal center reactions and their dysregulation in autoimmune conditions.

• Immunology
• Rheumatology
• B Cell Metabolism
• +۴ مورد دیگر

Kate Warren is a Senior Lecturer at the Centre for Art History & Art Theory within the School of Art & Design, Australian National University (ANU), part of the ANU College of Arts & Social Sciences. Her expertise spans modern and contemporary Australian and international art, with specialized focus on film, photography, video, and new media practices. As both an active curator and academic, she bridges theoretical research with public engagement in visual culture. Education: PhD in Art History, Monash University BA (Honours) in Cinema Studies, University of Melbourne BSc, University of Melbourne Research Focus: Warren's scholarship critically examines how visual arts are represented in popular media, particularly Australian magazines and television from the mid-to-late twentieth century. Her work reveals how public reception shaped visual literacy and art understanding, connecting art historiography with media studies and cultural history. She investigates audience engagement models that transformed passive viewers into active participants within Australia's visual ecosystem. Publication Trends: Her recent output (2017-2023) demonstrates consistent exploration of photography's evolving role, video art's political dimensions, and digital mediation of artistic practices. Warren analyzes how memes, celebrity culture, and publishing platforms reshape art discourse, highlighting tensions between institutional narratives and grassroots reception. Her work consistently positions Australian art within global conversations while emphasizing local specificity. Advising and Projects: Warren supervises higher degree research students at ANU and leads the 'University Art Museums Review' initiative (2024-2026), which evaluates how academic art collections drive pedagogical innovation and community impact. This project examines collection stewardship models that balance historical preservation with contemporary relevance. Curatorial Practice: With formative experience at the Australian Centre for the Moving Image (2007-2011), Warren has curated significant independent exhibitions including 'I don’t want to be there when it happens' (2017) and 'Atong Atem: Come Home' (2017). As editor of Peephole Journal, she cultivates experimental film criticism that challenges conventional academic discourse.

• Contemporary Australian Art
• Art Historiography
• Film and Cinema
• +۵ مورد دیگر