جست‌وجوی استاد و پژوهشگر

• Databases
• Transaction Management
• Data Management in the Cloud
• +۱۲ مورد دیگر

Heiko Schuldt is a Full Professor of Computer Science at the University of Basel and leads the Databases and Information Systems (DBIS) group. His research spans databases, transaction management, cloud data systems, digital libraries, and multimedia retrieval, with a focus on distributed systems, data streams, and service-oriented architectures. He studied at the University of Karlsruhe (KIT) and received his PhD from ETH Zurich in 2001. From 2003-2006, he served as an associate professor at UMIT, Austria. Education: University of Karlsruhe (Computer Science), ETH Zurich (PhD, 2001) Research Interests: His work integrates databases, cloud computing, and multimedia retrieval, emphasizing scalable systems for lifelog data, sports analysis, and VR/AR environments. Projects include vitrivr, Polypheny-DB, and StreamTeam. Recent Publications: Trends focus on VR/AR multimedia retrieval, cross-modal analysis, and polystore systems. Key contributions include open-source frameworks for video/image retrieval and immersive analytics. Advising: Supervised over 50 theses in areas like mixed reality, polystore optimization, and gesture-based interfaces.

Michel Gendreauمشاهده پروفایل

استاد

• Operations Research
• Transportation
• Logistics
• +۳ مورد دیگر

Michel Gendreau is a Full Professor in the Department of Mathematics and Industrial Engineering at Polytechnique Montréal . His research focuses on the application of Operations Research to Transportation , Telecommunications , and Energy Systems , with an emphasis on Stochastic Optimization and Real-time Planning . He co-directs the Intelligent Transportation Systems Laboratory and is affiliated with the CIRRELT , IVADO , and Trottier Energy Institute . Education : Ph.D. in Computer Science (1984), Université de Montréal His work includes developing metaheuristics for complex optimization problems and dynamic transportation systems . Recent projects address smart supply chains and real-time logistics . He has supervised over 40 doctoral and master's students, including notable graduates like Sanchez-Martinez, Guillen Reyes, and Parada Pradenas. Dr. Gendreau has been recognized with prestigious fellowships from IFORS (2022) and INFORMS (2010). His academic contributions span 420 publications, with recent studies appearing in Reliability Engineering and System Safety and Networks , focusing on stochastic programming , multiperiod routing , and UAV network design . He collaborates extensively with industry partners and has secured grants from organizations like FRQNT and CIRRELT . His research integrates machine learning with operations research to solve real-world challenges in transportation , energy , and logistics .

Erhan Bayraktarمشاهده پروفایل

استاد

• Mathematical finance
• applied probability
• machine learning
• +۴ مورد دیگر

Erhan Bayraktar is a Professor of Mathematics at the University of Michigan, holding the Susan Smith Chair. He serves as Director of the Quantitative Finance and Risk Management Masters Program, which he established in 2015. His academic career at the University of Michigan spans since 2004, progressing from T. H. Hildebrandt Research Assistant Professor to his current full professorship. Professor Bayraktar earned his Ph.D. from Princeton University in 2004, following dual Bachelor's degrees in Electrical Engineering and Mathematics from Middle East Technical University in Turkey. His academic journey reflects a strong foundation in both theoretical and applied mathematical disciplines. Bayraktar's research focuses on mathematical finance, applied probability, machine learning, mean field games, stochastic analysis, stochastic control, and optimal stopping. His work bridges theoretical mathematics with practical applications in finance and risk management. He has developed sophisticated mathematical frameworks for analyzing complex financial systems, market behaviors, and optimal decision-making under uncertainty. His contributions to mean field games have provided new insights into large-scale interacting systems, while his work on stochastic control has advanced methodologies for optimal decision processes. His publication record demonstrates a consistent trajectory of high-impact research, with recent work focusing on Wasserstein space analysis, graphon particle systems, and applications of machine learning to financial mathematics. His research shows increasing interdisciplinary connections between traditional mathematical finance and modern computational approaches. Susan M. Smith Professorship (2010-present) National Science Foundation CAREER Grant (2010-2016) SIAM Activity Group on Financial Mathematics and Engineering Early Career Prize (2010) Professor Bayraktar has mentored 14 Ph.D. students (13 graduated) and approximately 40 post-doctoral researchers. His students hold prestigious positions in academia and industry, including tenure-track positions at Boston University, University of Colorado, University of Sydney, and University of Toronto. He has secured continuous funding from the National Science Foundation, including the current grant DMS-2507940 (2025-2028) and previous grants totaling over 15 years of continuous NSF support. As Director of the Quantitative Finance and Risk Management Masters Program, Bayraktar has built a robust academic community through the Financial/Actuarial Math seminar series, which hosts about 10 outside speakers annually, and by organizing international workshops in stochastic analysis for finance and insurance in Ann Arbor.

Joo Heung Yoonمشاهده پروفایل

استادیار

• Machine Learning in Medicine
• Critical Care Medicine
• Hemodynamic Monitoring and Prediction
• +۳ مورد دیگر

Joo Heung Yoon, MD is an Assistant Professor of Medicine in the Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine at the University of Pittsburgh School of Medicine. His research develops machine learning models for predicting hemodynamic instability in critical care settings, with applications extending to space medicine environments. His educational background includes: MD from Catholic University of Korea, Seoul, South Korea (2002) Internal Medicine Internship at Maimonides Medical Center - SUNY Downstate (2007) Internal Medicine Residency at New York Medical College (2009) Research Fellowship at Massachusetts General Hospital / Harvard Medical School (2011) Research Fellowship at Beth Israel Deaconess Medical Center / Harvard Medical School (2014) Fellowship in Pulmonary and Critical Care Medicine at University of Pittsburgh School of Medicine (2017) Dr. Yoon specializes in identifying hidden pathologic patterns through machine learning, developing prediction models for shock, hemorrhage, and tachycardia using large-scale clinical data. His work bridges critical care medicine with AI, focusing on real-world ICU implementation through alert systems and user interfaces. He actively explores microgravity applications, aiming to create feasible prediction algorithms for resource-constrained space missions where timely high-stake decisions are critical. His publication trend (2018-2020) reveals consistent advancement in hemodynamic prediction models, transitioning from theoretical frameworks to practical implementation strategies. These works integrate supervised ML and deep neural networks to address circulatory shock, hemorrhage identification, and instability surrogates, demonstrating strong interdisciplinary collaboration between clinical medicine and engineering. Notable awards include: SCCM Gold Snapshot Award (2019) ATS Abstract Award (2018) Excellence in Clinical Service Award (2010) Partners in Excellence Award (2009) Richard D. Levere Teaching Award (2008) As Principal Investigator for NIH K23 grant GM138984 (2020-2025), Dr. Yoon leads research on machine learning-driven shock prediction models. He mentors medical students and house staff daily in the ICU, specializing in cardiopulmonary physiology teaching. His grant portfolio focuses on therapeutic strategies for circulatory shock in critically-ill patients, with strong industry-academic partnerships. Based at UPMC Montefiore, Dr. Yoon collaborates with Carnegie Mellon University's Machine Learning School and Pitt Engineering to develop clinical decision support systems. His team is designing graphic user interfaces for spaceflight applications where resource limitations demand highly efficient predictive analytics for hemodynamic crises.

Ethan N. Epperlyمشاهده پروفایل

پژوهشگر ارشد

• Randomized algorithms
• Quantum algorithms
• Scientific computing
• +۳ مورد دیگر

Ethan N. Epperly is a Miller Research Fellow in the Department of Mathematics at the University of California, Berkeley, where he conducts cutting-edge research in applied mathematics with a focus on computational techniques for large-scale problems. Dr. Epperly received his PhD in Applied and Computational Mathematics from Caltech, where his research was supported by a Department of Energy Computational Science Graduate Fellowship. His educational background established a strong foundation in both theoretical and applied mathematics. His primary research interests include randomized and quantum algorithms, scientific computing, and large-scale machine learning. Dr. Epperly specializes in designing computational techniques for solving large-scale problems in machine learning, quantum information, and scientific computing, with particular expertise in kernel matrix approximation, low-rank approximation, and numerical linear algebra problems. His work bridges theoretical analysis with practical computational efficiency. Epperly's recent publications demonstrate a strong focus on developing efficient randomized algorithms for matrix computations. His research shows how randomized approaches can achieve accuracy and stability comparable to classical methods while offering significant computational advantages, particularly in settings where computational resources are limited. His work on Krylov subspace methods, Cholesky decomposition variants, and trace estimation has advanced the field of numerical linear algebra. Hertz foundation fellowship finalist Thomas A. Tisch Prize for Graduate Teaching in CMS W. P. Carey & Co. Prize in Applied Mathematics SIAM Student Paper Prize Department of Energy Computational Science Graduate Fellowship As a Miller Research Fellow, Dr. Epperly collaborates with leading researchers including Joel A. Tropp, Robert J. Webber, and Yifan Chen. His work has significant implications for machine learning applications requiring efficient handling of large-scale matrix computations, with potential applications across scientific computing and quantum information processing.

David W. Evansمشاهده پروفایل

استادیار

• Musculoskeletal Pain
• Low Back Pain
• Pain Measurement and Disability
• +۷ مورد دیگر

Dr David W. Evans is an Assistant Professor in Musculoskeletal Health Care at the School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, where he has been a faculty member since 2017. He serves as Programme Lead for the MSc Physiotherapy (pre-registration) programme and teaches across multiple physiotherapy degrees including MSci and MSc programmes. Education: PhD in Low Back Pain, Keele University (2007) BSc (Hons) in Osteopathy, Health Sciences University (formerly British School of Osteopathy), London (1998) His research focuses on understanding and measuring disabling musculoskeletal pain, particularly low back pain, with an emphasis on improving patient outcomes through better treatment matching. His work spans pain mechanisms, measurement of disability, and the effectiveness of physical interventions. He has maintained a clinical practice in musculoskeletal health since 1998. Dr Evans's recent publications (2022–2025) reflect a strong trend in quantitative and clinical research, utilizing wearable technology for lumbar mobility assessment, analyzing pain drawings and spatial pain patterns, and investigating psychological factors such as fear of movement. His work integrates biomechanics, neuroscience, and clinical rehabilitation, often through large-scale studies and systematic reviews. He has also contributed to advancing definitions and educational approaches in manual therapy. Professional Memberships and Roles: Member, Society for Back Pain Research (since 2001) Lead, Pain-focused PPIE Group (since 2021) Member, University of Birmingham REDCap Committee (since 2022) Dr Evans has secured over £2 million in research funding as lead or co-applicant and has published over 50 peer-reviewed papers. He is actively involved in research leadership and has contributed to major clinical trial protocols and systematic reviews in pain and rehabilitation. He is affiliated with research platforms including ORCID, Google Scholar, and ResearchGate, and his work is supported by institutional and national research infrastructures. He coaches javelin throwing at a local athletics club, reflecting a personal commitment to physical activity and sports.

Hyemi Kimمشاهده پروفایل

استاد مدعو

• low frequency climate variability
• tropical meteorology
• ocean-atmosphere interaction
• +۴ مورد دیگر

Hyemi Kim is an Adjunct Professor at the School of Marine and Atmospheric Sciences (SoMAS), Stony Brook University. Her research focuses on climate variability across subseasonal to decadal timescales, including topics like the Madden-Julian Oscillation (MJO), tropical-extratropical interactions, and extreme weather events such as atmospheric rivers and tropical cyclones. Education: Ph.D., 2008, School of Earth and Environmental Sciences, Seoul National University, South Korea Research Interests: Hyemi Kim's work spans four primary areas: (1) Climate prediction from subseasonal to decadal scales, (2) Tropical-extratropical interactions, (3) Extreme events (atmospheric rivers, storm tracks, tropical cyclones), and (4) Machine learning applications for subseasonal-to-seasonal (S2S) prediction. Publication Trends: Her research output emphasizes the MJO, its interactions with other climate modes (QBO, ENSO), and implications for extreme weather. Recent works analyze atmospheric rivers, storm tracks, and tropical cyclone activity, often linking these to large-scale climate variability. Publications frequently employ climate models (e.g., CESM1, SubX, NMME) to assess predictability and improve forecasting frameworks. Labs & Teams: She collaborates with institutions like the National Center for Atmospheric Research (NCAR) and contributes to multi-model experiments such as the Subseasonal Experiment (SubX) and North American Multi-Model Ensemble (NMME).

Haochen Liمشاهده پروفایل

استادیار

• Environmental Fluid Dynamics
• Computational Fluid Dynamics
• Physics-informed Machine Learning
• +۷ مورد دیگر

Haochen Li is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of Tennessee, Knoxville, within the College of Engineering. He leads the multidisciplinary Water Infrastructure Laboratory (Ψ Lab), which focuses on advancing urban water infrastructure through high-fidelity computational fluid dynamics (CFD), physical modeling, and physics-informed machine learning (ML). Education: PhD in Environmental Engineering, University of Florida, 2019 MS in Mechanical Engineering, University of Florida, 2019 MS in Civil Engineering, University of Florida, 2015 BS in Coastal Engineering, Hohai University, 2013 His research centers on environmental fluid dynamics , particularly multiphase and multiphysics flows in urban water systems. He investigates turbulence, particulate matter transport, pathogen fate, and chemical dynamics using advanced CFD simulations, volumetric particle image velocimetry (PIV), and AI-driven models. His lab develops open-source tools like InterAdsFoam for adsorption systems and integrates ML with CFD to optimize infrastructure design, retrofit, and regulatory frameworks. The recent publications reflect a strong trend toward hybrid CFD-ML frameworks for water infrastructure, with applications in clarifier design, stormwater basin optimization, and real-time sensing. His work emphasizes model validation, scalability, and practical deployment, including web-based tools for engineers. Scientific Awards: Rudolph Hering Medal, ASCE, 2023 Editor choice, Journal of Environmental Engineering ASCE, 2021 Editor choice, Journal of Environmental Engineering ASCE, 2020 Graduate School Fellowship, University of Florida, 2015 Academic Achievement Award, University of Florida, 2013 Haochen Li actively advises researchers and students in his lab, including Kai Liu, Mohamed Shatarah, and Ahmed Abdelmeguid. His team works on AI-empowered reactive flows, physics-informed ML, and CFD applications in energy and environmental systems. He has served as a reviewer for top journals and is a member of the ASCE/EWRI Computational Fluid Dynamics Committee. His lab is equipped with state-of-the-art HPC platforms and physical modeling facilities for experimental validation.

Stephani L. Wrabelمشاهده پروفایل

استاد

• Education Policy
• Social and Emotional Learning
• Program Evaluation
• +۹ مورد دیگر

Stephani L. Wrabel is a Senior Policy Researcher at the RAND Corporation and Professor of Policy Analysis at the RAND School of Public Policy. She conducts influential research on education policy, social and emotional learning, and defense-funded youth programs, with her work shaping both federal and state policies. Institution: RAND Corporation School: RAND School of Public Policy Position: Professor of Policy Analysis Email: Stephani_Wrabel@rand.org Education: Ph.D. in Urban Education Policy, University of Southern California M.Ed., University of Florida B.A., Boston University Her research focuses on improving educational outcomes for students and military-connected populations through rigorous evaluation and policy analysis. She specializes in standards-based accountability, educational equity, program evaluation, and social and emotional learning. Her work often centers on vulnerable youth, including those in the National Guard Youth ChalleNGe and JROTC programs, and she has led major federal evaluations, including for the U.S. Department of Education’s Center to Improve SEL and School Safety. Analysis of her recent publications shows a consistent focus on youth development, military-civilian integration, educational equity, and evidence-based policy. Her research spans program evaluation, technical assistance frameworks, and longitudinal impact studies, with a strong emphasis on practical, policy-relevant findings. She frequently publishes both comprehensive reports and executive summaries to reach diverse stakeholders. Scientific Awards: No awards listed in the provided text. Wrabel leads major research initiatives and serves as principal investigator on defense-funded education studies. Her work involves collaboration with federal agencies, education departments, and military organizations. She has developed practical tools for program evaluation, particularly for Marine and Family Division programs, supporting effective resource use and program improvement. Her leadership in large-scale evaluations demonstrates significant grant and project management experience. She is actively involved in research teams focused on education reform and military youth programs. Her work with the Center to Improve Social and Emotional Learning and School Safety involved a multi-year technical assistance network, indicating leadership in collaborative, interdisciplinary teams.

Martin Rajmanمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Computational Linguistics
• Natural Language Processing
• +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.

Yan Chenمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Computer Science Education
• Real-Time Data Analysis
• +۳ مورد دیگر

Yan Chen is an Assistant Professor at the Virginia Tech College of Engineering , where he leads the PRIME Lab (Programming with Intelligent Machines & Environments) . His work focuses on creating interactive Human-AI systems to enhance real-time data analysis and programming education, particularly addressing barriers in collaborative learning environments. University of Toronto (Postdoctoral Fellow) University of Michigan (Ph.D., Information Science) University of Colorado, Boulder (BS/MS in Applied Math & Electrical & Computer Engineering) His research bridges Human-Computer Interaction (HCI) and Computer Science Education , with a focus on real-time data analysis , AI-driven programming assistance , and scalable learning tools . He employs LLMs and human-centered design to simplify complex computational processes, enabling data workers to detect critical patterns efficiently. Recent publications highlight trends in generative AI for education , proactive AI programming support , and collaborative analytics . Key themes include real-time classroom insights , intergenerational smartphone learning , and automated feedback systems . Scientific recognition includes: 🏆 Best Paper at L@S 2024 🏅 Best Paper Honorable Mention at CHI 2023 🏅 Best Paper Honorable Mention at UIST 2022 🏆 Best Short Paper at VL/HCC 2020 He mentors a team of PhD and MS students in projects spanning AI-assisted education, web automation, and collaborative coding tools, with active recruitment for future research directions.

Jochen Wolfمشاهده پروفایل

استاد

• Evolutionary Biology
• Speciation Genomics
• Genome Evolution
• +۷ مورد دیگر

Jochen Wolf is Chair of the Evolutionary Biology Division at Ludwig-Maximilians-Universität München (LMU) and a Max Planck Fellow of the Max Planck Institute for Biological Intelligence since 2022. His research integrates evolutionary biology, genomics, and ecology to address fundamental questions about speciation, adaptation, and biodiversity across multiple biological systems. Dr. Wolf's research program applies an integrative approach to understand microevolutionary processes and genetic mechanisms underlying species divergence. His work combines large-scale genomic analyses with laboratory and field experiments to characterize genomic divergence across populations and species. Key empirical systems include natural populations of birds (particularly corvids, swallows, and cuckoos), marine mammals (pinnipeds and killer whales), plant communities, and experimental evolution in fission yeast. His research spans multiple scales from immediate microevolutionary processes to broader evolutionary patterns across time. His recent publications reveal a sophisticated integration of genomic, epigenetic, and ecological perspectives. A notable trend shows increasing focus on structural genomic variation, chromosomal rearrangements, and epigenetic mechanisms as drivers of evolutionary processes. His work demonstrates how these molecular mechanisms interact with ecological factors to shape patterns of biodiversity and adaptation. Dr. Wolf's research has gained significant recognition through publications in top-tier journals including Nature, Science, and Nature Ecology & Evolution. His groundbreaking studies on crow hybrid zones, killer whale ecotypes, and experimental evolution of speciation have been featured in prominent media outlets such as The New Yorker, The Guardian, Scientific American, and Der Spiegel, demonstrating the broad impact of his work. As Principal Investigator, Dr. Wolf actively mentors doctoral students and postdoctoral researchers, fostering the next generation of evolutionary biologists. His lab maintains strong international collaborations, particularly through affiliations with SciLifeLab in Uppsala. Research in his group is supported by multiple funding sources including German Research Foundation grants and European Union programs, enabling both fundamental research and applications to conservation biology. The Wolf lab operates within LMU's Division of Evolutionary Biology, which provides access to state-of-the-art facilities including the Leibniz Supercomputing Centre. The lab maintains strong connections with the Max Planck Institute for Biological Intelligence and SciLifeLab in Uppsala, creating a rich collaborative environment for interdisciplinary research in evolutionary genomics. This network enables comprehensive studies spanning from molecular mechanisms to ecological and evolutionary consequences across diverse biological systems.

Hui Luمشاهده پروفایل

استادیار

• Operating Systems
• Systems Virtualization
• Cloud Computing
• +۶ مورد دیگر

Dr. Hui Lu is an Assistant Professor in the Department of Computer Science and Engineering at The University of Texas at Arlington (UTA), where he has been serving since September 2023. Prior to joining UTA, he was an Assistant Professor at SUNY Binghamton from 2017 to 2023. His academic journey includes a Ph.D. in Computer Science from Purdue University (2017), and Master’s and Bachelor’s degrees in Electronic Engineering from Shanghai Jiao Tong University. Ph.D., Computer Science, Purdue University, 2017 M.S., Electronic Engineering, Shanghai Jiao Tong University, 2009 B.S., Electronic Engineering, Shanghai Jiao Tong University, 2006 Dr. Lu's research centers on systems software with a focus on operating systems, virtualization, cloud computing, file and storage systems, and computer networks. His work emphasizes performance optimization and security in cloud-native environments. He has collaborated with leading industrial research labs including HPE Labs, IBM Research, Microsoft Research, AT&T Labs, and NEC Labs. His recent publications span top-tier venues such as OSDI, SOSP, USENIX ATC, and VLDB. The article trends reflect a strong emphasis on secure container technologies, memory tiering, packet processing optimization in virtualized networks, and efficient cloud storage systems. His work increasingly integrates hardware-aware optimizations and lightweight security mechanisms. NSF CAREER Award (2023) UT System Rising STARs Award (2023) Summer Faculty Fellowship, Air Force Research Lab (2019) Dr. Lu has successfully advised multiple Ph.D. students, including Jiaxin Lei, who is now an Assistant Professor at Kean University. His research is supported by major grants from the National Science Foundation (NSF) and the Air Force Research Lab (AFRL), focusing on secure containers, non-volatile memory management, and cloud-native virtualization. He has served as Principal Investigator (PI) on multiple funded projects, demonstrating strong leadership in research and innovation. He is actively involved in teaching core courses such as Operating Systems and advanced topics in systems and architecture. He mentors a growing group of Ph.D. students and welcomes motivated individuals to join his research group.

Heidi Johansen-Bergمشاهده پروفایل

استاد

• Neuroscience
• Cognitive Neuroscience
• Neuroplasticity
• +۳ مورد دیگر

Heidi Johansen-Berg is Pro-Vice Chancellor (Strategic Initiatives) at the University of Oxford and Associate Head (Research and Innovation) in the Medical Sciences Division. She holds a Professorship in Cognitive Neuroscience and a Wellcome Principal Research Fellowship at the Nuffield Department of Clinical Neurosciences, where she leads the Plasticity Group at the Oxford Centre for Functional MRI of the Brain (FMRIB). Her research centers on neuroplasticity mechanisms in the sensorimotor system, with emphasis on white matter plasticity, activity-dependent myelination, and implications for stroke rehabilitation and age-related brain decline. She integrates multimodal neuroimaging with behavioral studies to investigate how the brain adapts to learning, experience, and damage, translating findings into therapeutic interventions for neurological conditions. Recent publications reveal strong thematic trends in sleep-motor interactions post-stroke, exercise-induced neuroprotection in aging and adolescence, and experience-dependent white matter remodeling. Her work demonstrates how physical activity modulates brain structure-function relationships across the lifespan, with direct applications for neurorehabilitation protocols. Scientific recognition includes: Fellow of the Royal Society (FRS) Fellow of the Academy of Medical Sciences (FMedSci) Wellcome Principal Research Fellowship Professor Johansen-Berg directs the WIN Plasticity Group and co-leads the WIN Neuroplastics Network and Oxford University Centre for Integrative Neuroimaging (OxCIN). Her research program drives translational initiatives in stroke recovery and brain health maintenance, with ongoing projects examining digital sleep therapies, myelin dynamics, and exercise neuroscience through large-scale clinical trials and advanced imaging methodologies.

Jason Nelsonمشاهده پروفایل

استاد

• Digital Literature
• Electronic Literature
• Digital Poetry
• +۳ مورد دیگر

Jason Nelson is a Professor of Digital Culture in the Department of Linguistic, Literary and Aesthetic Studies at the University of Bergen, Norway. He is a creator of digital poems and fictions, builder of surrealist and politically focused art games and digital creatures. His work is exhibited widely in galleries and journals around the globe at FILE, ACM, LEA, ISEA, SIGGRAPH, ELO and numerous other venues. Nelson serves on organizational boards including the Australia Council Literature Board and the Electronic Literature Organization. Nelson's research focuses on the intersection of digital technology, creative writing, and artistic expression. He explores how AI and machine learning can be harnessed for creative purposes, developing new forms of digital literature and interactive art. His work often involves building expansive visual worlds through collaborative AI processes, creating interactive digital poetry, and developing novel approaches to digital narrative. Nelson's research spans digital humanities, electronic literature, AI-generated art, and interactive media, with particular emphasis on how these technologies transform creative processes and experiences. Over the past decade, Nelson's work has increasingly focused on the creative potential of AI technologies, especially in the areas of text-to-image generation and multimodal authorship. His projects often blend game engines with poetic expression, creating immersive experiences that challenge traditional boundaries between human and machine creativity. Recent works explore themes of multispecies futures, time perception, and the transformation of physical spaces through augmented reality. Nelson has received numerous scientific awards and fellowships including: Fulbright Fellowship at the University of Bergen Moore Fellowship at the National University of Ireland Winner of the Digital Writing Prize, Queensland Literary Awards (15,000 AUD) Winner of the Woollahra Library Digital Poetry Prize (5,000 AUD) Runner-Up Prize at the Videomedeja digital art exhibition Finalist for the Turn-on Literature Prize Finalist for the Queensland Literary Awards, Digital Writing Category Multiple finalist nominations for the New Media Writing Prize Nelson actively participates in academic advising and has secured significant research funding, including a 125,000 AUD grant from the Australia Council of the Arts, Literature Board for his project "Cube Cryptext and Nomencluster," which was recognized as the world's largest interactive art-game. His work "Nine Billion Branches" received multiple awards including the Digital Writing Prize from the Queensland Literary Awards. He has also received a 75,000 NOK grant for the "Flood Mosaic Artwork" project featured in the Floodlines Exhibition at the State Library of Queensland. Nelson is affiliated with the Center for Digital Narrative at the University of Bergen, where he collaborates with researchers like Scott Robert Rettberg and Alinta Krauth. Together they form EphemerLab, exploring new creative processes that move beyond simple "ask and generate" AI methods. Their work involves stitching together hundreds of individual image fragments and components into cohesive visual and narrative concepts, pushing the boundaries of what's possible with current AI technologies.