جست‌وجوی استاد و پژوهشگر

Przemyslaw Grabowiczمشاهده پروفایل

استادیار

• fair and explainable machine learning
• data science
• computational social science
• +۱۲ مورد دیگر

Przemyslaw Grabowicz is an Assistant Professor of Computer Science at University College Dublin and an Adjunct Professor at the University of Massachusetts Amherst. He leads the SIMS (Socially Intelligent Media and Systems) Lab and the EQUATE initiative, and is actively involved in the Knowledge Discovery Lab (KDL). His work bridges computer science, social science, and public policy, focusing on responsible AI and digital society. Research Interests: Fair and Explainable Machine Learning Computational Social Science Social Media and Network Science Public Opinion Modeling Algorithmic Bias and Discrimination Prevention Open-World Learning His research develops statistical and machine learning methods to understand and augment public opinion in digital environments, ensuring fairness, transparency, and societal benefit. He emphasizes legal compliance and ethical design in AI systems. Recent Research Trends: His recent publications focus on social media polls, political bias, misinformation, and fairness in machine learning. He investigates how algorithmic systems shape public discourse, especially during elections and global crises, and develops methods to detect and mitigate bias in data and models. Scientific Awards and Recognition: Best Paper Honorable Mention, ICWSM’25 WICI Data Challenge Main Prize (2013) Arnold O. Beckman Research Award Multiple UMass Amherst Interdisciplinary Research Grants Volkswagen Foundation Grants (over €900k total) Advising and Grants: Dr. Grabowicz supervises several PhD students in the SIMS and KDL labs and collaborates with MS students. He has secured significant funding from the Volkswagen Foundation, UMass Amherst, and the University of Illinois, supporting research on political misinformation, media bias, and global agenda setting. He is currently recruiting a postdoc at UCD. Labs and Initiatives: He heads the SIMS Lab and the EQUATE initiative, and contributes to the KDL. His project socialpolls.org explores public opinion through social media, and he maintains an active presence through the Uncommon Good blog on responsible AI.

Rosalyn Moranمشاهده پروفایل

استاد

• Computational Neuroscience
• Computational Psychiatry
• Neurodegenerative Diseases
• +۵ مورد دیگر

Professor Rosalyn Moran is a Professor of Computational Neuroscience and Deputy Director of King's Institute for Artificial Intelligence at King's College London. She holds roles in the Department of Neuroimaging and School of Neuroscience within the Institute of Psychiatry, Psychology & Neuroscience. Her research focuses on computational neuroscience, computational psychiatry, and neurology, particularly integrating brain connectivity with algorithmic principles like the free energy principle. She explores neurotransmitter roles in decision-making and disease modeling, with applications in artificial intelligence and neurodegenerative disorders. Moran serves as an editor for Neuroimage and collaborates with leading institutions. Key projects include global neuroimaging initiatives (UNITY) and low-field MRI advancements in low-resource settings. Her work bridges Bayesian inference, AI, and neurobiology, with recent emphasis on pediatric neuroimaging and treatment-resistant psychosis. Education & Research Interests Rosalyn Moran's research spans computational psychiatry, neuroimaging techniques, and AI applications in healthcare. Her lab investigates serotonin and dopamine signaling, brain connectivity patterns, and predictive coding frameworks. Notable contributions include modeling NMDA receptor dysfunction in encephalitis and developing super-resolution MRI methods for global health contexts. Grants & Collaborations Funded projects include MRC Human Functional Genomics (2024-2028), NIHR Maudsley BRC (2022-2027), and Gates Foundation initiatives for low-field MRI enhancement. Collaborators include Karl Friston (UCL), Read Montague (Virginia Tech), and Klaas Enno Stephan (University of Zurich). Recent events include presenting the Free Energy Principle's role in generative AI (May 2023). Labs & Teams Her lab focuses on computational psychiatry and AI-driven neuroimaging solutions, collaborating with the King’s Global Health Institute to advance medical imaging accessibility in low-income regions.

Dina El-Zanfalyمشاهده پروفایل

استادیار

• Computational Design
• Human-Computer Interaction
• Embodied Interaction
• +۵ مورد دیگر

Dina El-Zanfaly serves as an Assistant Professor in the School of Design at Carnegie Mellon University (CMU), where she directs the hyperSENSE: Embodied Computations Lab. Her work bridges computational design and human-centered interaction, focusing on how physicality shapes sensory experiences and cognitive processes through intelligent systems. Education: PhD in Design and Computation, Massachusetts Institute of Technology (MIT) Master of Science in Design and Computation, MIT (Fulbright scholar) Her research critically examines computational methods for augmenting sensory perception, with emphasis on embodied sense-making in hybrid environments. She investigates co-creative interactions between humans and intelligent systems, exploring how computational tools empower designers and non-designers to shape products, social spaces, and interconnected technologies. Key questions address mutual learning between humans and machines through improvisation and creative production. Analysis of her 2022-2025 publications reveals dominant themes in mixed reality interfaces, AI-augmented skill acquisition (particularly in crafts and welding), and tangible co-creation with generative AI. Her work consistently integrates physical computing with mindfulness applications and privacy-aware smart environments, demonstrating interdisciplinary reach across education, manufacturing, and therapeutic contexts. Scientific Awards: Fulbright Scholarship As lab director, El-Zanfaly mentors students in computational making and embodied interaction projects. Her research is supported through initiatives like Fab Lab Egypt and collaborations with MIT, where she co-founded the Computational Making Group. She chairs major conferences including Fab15 in Egypt and serves on the DESFORUM program committee, indicating significant leadership in maker education and design research communities. She founded and leads the hyperSENSE Lab at CMU, which investigates computational embodiment through projects like Origami Sensei and Sand-in-the-loop. Previously, she co-established the Computational Making Group at MIT and co-founded Fab Lab Egypt (the first community maker space in North Africa/Arab world), demonstrating sustained commitment to global maker ecosystems and interdisciplinary team building.

Secil Ugur Yavuzمشاهده پروفایل

استاد

• Eco-social Design
• Research through Design
• Tangible Human-Technology Interactions
• +۷ مورد دیگر

Secil Ugur Yavuz is a Professor at the Faculty of Design and Arts, Department of Design, at Free University of Bozen-Bolzano. Her academic work spans eco-social design, research through design, and tangible human-technology interactions, with a particular focus on sustainable materials and collective making practices. She teaches courses including Design 3 for the Master in Eco-social Design and doctoral programs in Experimental Research through Design, Art and Technologies. Professor Yavuz's research explores the intersection of analog and digital through tangible human-technology interactions, with significant contributions to sustainable material systems. Her FERAL WOOL project investigates ecological and cultural dimensions of wool, while her work with biomaterials like microbial cellulose and open-source bioreactors addresses circular production systems. She employs embodied and speculative approaches to examine microplastic emissions, children's nature engagement through tools like TREESENSE, and social play with interactive toys. Her recent publications reveal a strong thematic focus on material culture, sustainability, and human-centered design across multiple scales. The research demonstrates consistent exploration of how digital and physical realms interact to create meaningful user experiences while addressing ecological challenges. Key trends include the use of embodied interaction methods, speculative design for cultural critique, and co-creative processes that bridge technological innovation with social and environmental responsibility. Yavuz leads the Design Friction Lab, which investigates the philosophical foundations of design through customizable interfaces and DIY approaches. Her work with doctoral students in Experimental Research through Design emphasizes reshaping technologies through collective making processes. The FERAL WOOL research project represents a significant current initiative exploring sustainable textile futures through both ecological and cultural lenses.

Cleotilde Gonzalezمشاهده پروفایل

استاد پژوهشی

• Decision Science
• Cognitive Psychology
• Human-Computer Interaction
• +۵ مورد دیگر

Cleotilde (Coty) Gonzalez is a Research Professor of Decision Sciences at Carnegie Mellon University, with primary affiliation in the Department of Social and Decision Sciences (SDS). She serves as the Founding Director of the Dynamic Decision Making Laboratory (DDMLab) and Research Co-Director of the NSF National Institute for AI for Societal Decision Making (AI-SDM). Her extensive academic affiliations include the Security and Privacy Institute (CyLab), the Societal Computing program in the Software and Societal Systems Department (S3D), the Human-Computer Interaction Institute (HCII) in the School of Computer Science, and the Center for Behavioral Decision Research (CBDR) and Center for Neural Basis of Cognition (CNBC). Dr. Gonzalez holds a Ph.D. in Management Information Systems and has developed Instance-Based Learning Theory (IBLT), a significant contribution to cognitive science that explains how people make decisions based on past experiences. Her research spans experimental studies and computational modeling of cognitive processes in dynamic decision environments, with applications in cybersecurity, human-machine teaming, and societal decision making. Her recent publications reveal a strong focus on human-AI collaboration, collective intelligence, cybersecurity, and cognitive modeling. The research trends show increasing integration of AI systems with human decision processes, particularly examining how humans and AI can complement each other in complex decision environments. Her work increasingly addresses cybersecurity challenges through behavioral science perspectives, exploring how cognitive models can improve defense mechanisms against social engineering attacks. Lifetime Fellow of the Cognitive Science Society Lifetime Fellow of the Human Factors and Ergonomics Society Member of the Governing Board of the Cognitive Science Society Member at Large of the Policy Council of the System Dynamics Society Committee member of the National Academies Division Committee for the Behavioral and Social Sciences and Education Dr. Gonzalez has mentored over 50 post-doctoral fellows and doctoral students, with many going on to successful careers in academia, government, and industry. Her research has been supported by major collaborative efforts including Collaborative Research Alliances (CRA) and Multi-University Research Initiative grants from the Army Research Laboratories (ARL) and Army Research Office (ARO), as well as projects with the Defense Advanced Research Projects Agency (DARPA). She directs the Dynamic Decision Making Laboratory, which conducts research involving laboratory experiments and cognitive computational models to derive theoretical conclusions about dynamic decision making and develop applications for societal problems.

• Political Geography
• Geopolitics
• Technology and Security
• +۴ مورد دیگر

Professor Louise Amoore holds a faculty position at Durham University's Department of Geography, where she serves as Professor of Political Geography and Deputy Head of Department. Her work explores intersections of geopolitics, technology, and security, with a focus on algorithmic governance and data-driven practices. Co-editor of Progress in Human Geography Appointed to UK ethics body on biometric technologies Recipient of RCUK Global Uncertainties leadership fellowship Her research examines how data and algorithms reshape security paradigms, democracy, and societal norms. Recent projects analyze generative AI, cloud computing, and machine learning's political implications. She has secured funding from Leverhulme Trust, ESRC, EPSRC, AHRC, and NWO. Key article trends reveal expertise in algorithmic sovereignty (2024), border governance (2024), predictive security models (2023), data reuse ethics (2022), and post-9/11 surveillance practices (2021). Her work critically interrogates machine learning's epistemological foundations (2019) and data sovereignty implications (2018). RCUK Global Uncertainties leadership fellowship (2012-2015) Leverhulme Trust funding ESRC, EPSRC, AHRC, NWO grants Current PhD supervisees include Anna Okada and Charlotte Lock. She co-developed the Algorithmic Life book (2015) and serves as editor for Progress in Human Geography , maintaining active research collaborations in Europe.

Xinran Zhuمشاهده پروفایل

استادیار

• Learning Sciences
• Learning Analytics
• AI in Education
• +۳ مورد دیگر

Xinran Zhu is an Assistant Professor at the University of Illinois Urbana-Champaign College of Education, specializing in Learning Design & Leadership and Instructional Design, Technology, & Organization. Her research intersects learning sciences, learning analytics, and AI in education, focusing on designing technology-supported learning environments for authentic classroom settings. Ph.D. in Learning Sciences and Technologies, University of Pennsylvania (2024) M.A. in Educational Psychology, University of Connecticut Graduate studies in learning technologies, University of Minnesota Her research spans three main areas: (1) design and implementation of educational technologies, particularly social annotation tools for knowledge building; (2) AI integration in education to augment collaborative learning; and (3) computational discourse analysis using network analysis and NLP to generate actionable insights. Recent projects include SynthesisAI , a GenAI-powered chatbot for knowledge synthesis, and the Synthesis Lab , a precursor tool for integrating peer ideas in collaborative writing. Dr. Zhu teaches courses on ubiquitous learning, advanced learning technologies, and eLearning system design. She employs co-design methodologies to develop and implement technologies in both lab and real-world classroom settings, emphasizing student agency and ethical AI partnerships.

Kaat Alaertsمشاهده پروفایل

استاد

• Neurorehabilitation
• Oxytocin Research
• Autism Spectrum Disorder
• +۶ مورد دیگر

Professor Kaat Alaerts is a leading researcher at KU Leuven's Faculty of Movement and Rehabilitation Sciences, where she serves as Head of the Neurorehabilitation Research Group and Professor in the Department of Rehabilitation Sciences. Her work bridges neuroscience, psychology, and rehabilitation science to develop innovative interventions for stress regulation and social-cognitive functioning, with a particular focus on autism spectrum disorder and related conditions. Her primary research interests span neurorehabilitation , oxytocin research , autism spectrum disorder , stress regulation , mindfulness and meditation , neurostimulation , and social cognition . Dr. Alaerts employs a multidisciplinary approach that combines neuroscientific, physiological, and behavioral methods to study both clinical effectiveness and underlying brain mechanisms of neuromodulatory interventions. The research output demonstrates a strong focus on exploring the therapeutic potential of oxytocin, particularly for autism spectrum disorder. Her work examines both the standalone effects of oxytocin and its synergistic effects when combined with mindfulness training or other interventions. A growing body of research also investigates the gut-brain axis in autism and the role of microbiome composition in social and stress-related difficulties. Dr. Alaerts has received notable recognition including the KAGB Clinical Medicine Award in September 2024 for her work on oxytocin administration in children with autism. Her research group has also been honored with multiple "Belgium's got talent" prizes from the Belgian College of Neuropsychopharmacology and Biological Psychiatry. As a dedicated mentor, Dr. Alaerts supervises numerous PhD students and postdoctoral researchers, including Margaux Evenepoel, Jellina Prinsen, Elise Tuerlinckx, and others who have made significant contributions to the field. Her research is supported by multiple substantial grants, including several ongoing projects running through 2028-2029 that investigate oxytocin's role in stress regulation for breast cancer survivors, autism, and other conditions. The Neuromodulation Laboratory, which Dr. Alaerts leads, focuses on three core domains: oxytocin neuropsychopharmacology, contemplative science and combinatory approaches, and neuroregulation techniques. The lab operates within a multidisciplinary network that includes the LBI - KU Leuven Brain Institute and maintains strong collaborative relationships across various research institutions.

Gerard D Schellenbergمشاهده پروفایل

استاد

• Alzheimer's Disease Genetics
• Neurodegenerative Disorders
• Genomics
• +۴ مورد دیگر

Gerard D Schellenberg is a Professor of Pathology and Laboratory Medicine at the University of Pennsylvania Perelman School of Medicine, with graduate affiliations in Genomics and Computational Biology and Neuroscience. His research focuses on the genetic architecture of Alzheimer's disease and related neurodegenerative disorders, particularly through large-scale genomic studies and neuropathological correlations. Education: B.S. in Biochemistry (minor: Cell Biology), University of California at Riverside, 1973 Ph.D. in Biochemistry (minor: Cell Biology), University of California at Riverside, 1978 NIH Post Doctoral Fellowship, National Institute of Health, 1980-1982 Senior Research Fellow positions at University of Washington departments (1978-1983) Dr. Schellenberg's research program centers on identifying genetic risk factors for Alzheimer's disease through genome-wide association studies (GWAS), whole-genome sequencing, and multi-omics integration. His work emphasizes population diversity, with significant contributions to understanding genetic risk in African American cohorts and sex-specific effects in neurodegeneration. Key focus areas include tauopathies, TDP-43 pathology, and the role of immune-related genes in disease progression. He has pioneered studies on progranulin mutations and their variable phenotypic expression across neurodegenerative conditions. Recent publications reveal a strong trajectory toward multi-ethnic genetic studies, with emphasis on Alzheimer's disease genetics in underrepresented populations , sex differences in cognitive resilience , and novel risk genes like MGMT and DCDC2. His team integrates neuropathological data with genomic findings to establish causal mechanisms, frequently publishing in high-impact journals like Nature Genetics and Alzheimer's & Dementia . Key Scientific Contributions: Leadership in the Alzheimer's Disease Sequencing Project (ADSP) expanding ethnic diversity in genetics research Development of the Alzheimer's Disease Variant Portal (ADVP) for harmonized genetic data Pioneering work on APOE-ε4 modifying loci in African ancestry populations Identification of sex-specific genetic predictors for memory maintenance Dr. Schellenberg directs genomic research initiatives that bridge basic science with clinical neuropathology. His laboratory maintains extensive collaborations with neuropathology cores for autopsy-confirmed diagnoses and leverages multi-ethnic cohorts to address health disparities in dementia research. Current work focuses on elucidating how genetic variants influence tau and TDP-43 pathology across diverse populations, with implications for precision medicine approaches to neurodegenerative diseases.

Valentyn Panchenkoمشاهده پروفایل

استاد

• Financial Econometrics
• Time Series Analysis
• Dependence Measures and Copulae
• +۱۱ مورد دیگر

Professor Valentyn Panchenko is a leading academic in Economics at the UNSW Business School, specializing in advanced econometric methodologies and financial modeling. Holding a PhD from the University of Amsterdam and an MPhil from the Tinbergen Institute, his research bridges theoretical econometrics with real-world financial applications, emphasizing big data analysis, network structures, and dependence modeling in economic systems. His expertise spans financial econometrics, time series analysis, non-parametric statistics, and agent-based economic simulations. He focuses on Granger causality, model evaluation, structural economic modeling, and bounded rationality with heterogeneous agents. His work has secured significant grants including ARC Discovery Projects and DECRA fellowships, enabling cutting-edge research on market dynamics and economic interactions. Professor Panchenko's publications appear in top-tier journals like the Journal of Econometric Theory, AEJ: Micro, Journal of Economic Dynamics & Control, and Journal of Banking & Finance. His methodological contributions include novel approaches to copula-based forecasting, nonlinear causality testing, and evolutionary learning models in strategic economic environments. While specific student advising details aren't provided, his research leadership demonstrates sustained impact across econometric theory, financial markets, and experimental economics.

Saud Alhusainiمشاهده پروفایل

استادیار

• Neurology
• Movement Disorders
• Parkinson's Disease
• +۴ مورد دیگر

Saud Alhusaini MD PhD is an Assistant Professor of Neurology at the Warren Alpert Medical School of Brown University and serves as a Neurologist/Movement Disorders Specialist at Rhode Island Hospital. His research integrates imaging genomics and multimodal brain imaging approaches to investigate neurological disorders including Parkinson's disease, essential tremor, and epilepsy. He is affiliated with the Carney Institute for Brain Science and collaborates extensively with clinicians, geneticists, electrophysiologists, MRI specialists, neuropsychologists, and data scientists. Education: PhD from the Royal College of Surgeons in Ireland (RCSI) MSc in Neuroscience from Trinity College Dublin MD from University of Dublin, School of Medicine Adult neurology residency at McGill University/Montreal Neurological Institute Clinical research fellowship at Yale School of Medicine Clinical fellowship at Stanford University Medical Center Dr. Alhusaini's research focuses on identifying key endophenotypes and subclinical biomarkers to elucidate the underlying mechanisms of complex neurological conditions. His work spans multiple areas including movement disorders, epilepsy, and brain structure genetics. He has made significant contributions to understanding the genetic architecture of brain structures through his involvement with the ENIGMA consortium, which conducts large-scale collaborative analyses of neuroimaging and genetic data across institutions worldwide. An analysis of his publication record reveals a consistent pattern of high-impact research at the intersection of neurology, genetics, and advanced imaging techniques. His recent work demonstrates particular expertise in Parkinson's disease genetics, epilepsy network analysis, and movement disorder diagnostics. The breadth of his research, spanning from basic genetic mechanisms to clinical applications, highlights his comprehensive approach to understanding neurological disorders. Dr. Alhusaini has received funding from the Rhode Island Research Foundation, Brown Physicians, Inc., and Advance RI-CTR to support his research initiatives. His collaborative approach is evident through his numerous multi-institutional projects and extensive co-author network across Brown University departments including Neurology, Neurosurgery, and Pathology and Laboratory Medicine.

Amy Zavatskyمشاهده پروفایل

دانشیار

• Biomechanics
• Orthopaedic Biomechanics
• Gait Analysis
• +۴ مورد دیگر

Amy Zavatsky is a Reader in Engineering Science at the University of Oxford and Tutorial Fellow at St Edmund Hall, with faculty service since 1996. Her work bridges mechanical engineering and clinical orthopaedics, focusing on lower extremity biomechanics and gait analysis within the Department of Engineering Science. Education: BSc in Bioengineering, University of Pennsylvania DPhil in Engineering Science, University of Oxford (Thouron Award recipient) Research Focus: Prof. Zavatsky pioneers orthopaedic biomechanics research with emphasis on foot/ankle kinematics, knee osteoarthritis mechanisms, and gait compensations. Her work integrates theoretical modeling with in vitro experimentation to develop clinical applications for cerebral palsy, flatfoot, and running injuries. Current projects advance multi-segment foot modeling and cognitive-efficient data visualization for clinical gait analysis. Publication Trends: 2021-2025 works reveal three converging themes: (1) Open-source foot modeling ( OpenOFM ), (2) Data visualization for clinical decision-making, and (3) Sensor optimization using statistical methods. These publications consistently bridge engineering innovation with orthopaedic clinical practice through collaborations with the Oxford Gait Laboratory. Scientific Recognition: Philip Leverhulme Prize (2003) for outstanding early-career scholarship University Teaching Award (2008) for biomechanics instruction and MSc Biomedical Engineering development Departmental Teaching Awards: Silver (2021), Bronze (2022) Institution of Mechanical Engineers Thomas Stephen Prize (1993) Academic Leadership: Prof. Zavatsky directs undergraduate engineering tutorials at St Edmund Hall while teaching mechanical/civil/biomedical engineering courses. She previously served as Director of Graduate Studies (2016-17), Acting MSc Biomedical Engineering Director (2006-07), and Junior Proctor (2012-13). Her DPhil supervision targets lower-limb biomechanics projects requiring strong engineering fundamentals. Research Infrastructure: Based at the Institute of Biomedical Engineering (Nuffield Orthopaedic Centre), she collaborates extensively with the Oxford Gait Laboratory. Her biomechanics research group utilizes motion capture systems and multi-segment modeling to translate engineering principles into clinical rehabilitation protocols.

Eduardo Mercado IIIمشاهده پروفایل

استاد

• Bioacoustics
• Cognitive Psychology
• Marine Ecology
• +۵ مورد دیگر

Eduardo Mercado III is a Professor in the Department of Psychology at the University at Buffalo, College of Arts and Sciences. His research focuses on bioacoustics, cognitive psychology, and marine ecology, particularly the vocal behavior of humpback whales and its implications for understanding human impact on marine ecosystems. He is also known for his work in perceptual learning, autism spectrum disorder, and comparative cognition. Scientific Awards Guggenheim Fellowship Harvard Radcliffe Institute Fellowship Research Trends His recent publications emphasize bioacoustic analysis of humpback whale songs, including their spectral entropy, cyclical variations, and adaptive adjustments to anthropogenic noise. Additional work explores perceptual learning mechanisms in autism, neural network modeling for acoustic classification, and cognitive processes in canines and rodents. Projects Mercado’s “Singers as Sentinels” project combines acoustic analysis of humpback whale songs with public awareness initiatives about ocean noise pollution. The project will produce a book, Why Whales Sing and Dolphins Don’t , and a web-based interface for public engagement.

Arie E. Kaufmanمشاهده پروفایل

استاد

• Computer Graphics
• Visualization
• Virtual Reality
• +۴ مورد دیگر

Arie E. Kaufman is a Distinguished Professor in the Department of Computer Science at Stony Brook University, serving as Chief Scientist of the Center of Excellence in Wireless and Information Technology (CEWIT) and Director of the Center of Visual Computing (CVC). He additionally holds a Distinguished Professorship in Radiology, with a 40+ year career at Stony Brook since joining in 1985 and chairing the CS department from 1999-2009. His seminal research spans computer graphics, visualization, and virtual reality with biomedical applications, pioneering breakthroughs including 3D Virtual Colonoscopy (FDA-approved colon cancer screening), Cube hardware architectures (commercialized as VolumePro), the Reality Deck (1.5 billion-pixel immersive display), and foundational work in volume visualization. His interests focus on real-time rendering, medical imaging, and immersive analytics, with recent work integrating machine learning for healthcare and environmental risk visualization. Recent publications demonstrate continued leadership in high-resolution immersive displays (Silo), XR analytics with LLMs, storm surge visualization, and neural reconstruction techniques. His work bridges theoretical innovation with practical applications, particularly in pancreatic cancer prognosis and disaster preparedness. Major honors include: IEEE Visualization Career Award (2005) Fellow of the National Academy of Inventors (2017) ACM Fellow (2009) IEEE Fellow (1998) Long Island Technology Hall of Fame (2013) European Academy of Sciences membership (2002) As PI on 100+ research grants, Kaufman's work has generated 300+ refereed papers, 40+ patents, and extensive media coverage (New York Times, Science, Wall Street Journal). He leads the Center of Visual Computing with focus on translational research, including VolVis software (5,000+ installations) and Reality Deck deployments for big data analytics. His lab develops cutting-edge visualization infrastructure for medical diagnostics and environmental modeling, with current projects advancing immersive storm surge analytics, neural structure extraction, and VR-based risk communication systems. Future work emphasizes AI-enhanced visualization for precision medicine and climate resilience planning.

Pere-Pau Vázquezمشاهده پروفایل

استادیار

• Information Visualization
• Scientific Visualization
• Medical Data Visualization
• +۶ مورد دیگر

Pere-Pau Vázquez is an Assistant Professor in AI for Visual Computing at the Computer Vision Lab, TU Wien, Austria . Previously, he held academic positions at the ViRVIG Group and Facultat d'Informàtica de Barcelona (UPC) , where he taught courses in Programming, Computer Graphics, and Visualization for over 20 years. His research focuses on Information Visualization, Scientific Visualization, Medical Data Visualization, Molecular Visualization, and AI applications to Visual Computing . Current Teaching : Data Visualization, Fast Realistic Rendering, Information Visualization, Medical Images, Scientific Visualization, Virtual Reality, and 3D Medical Visualization. Former PhD Students : Elena Molina, Alexandra Cortez, Jesús Díaz, Pedro Hermosilla, Eva Monclús. His scientific awards include the Best PhD Thesis Award (UPC, 2003), Best Student Paper Award (SPIE, 2012), and Best Paper Award (International Conference on Computer Graphics Theory and Applications, 2013). Recent publications explore AI integration in biomedical visualization, molecular data analysis, and interactive techniques for volume rendering. He serves on the EuroGraphics Executive Board as Secretary and is active in steering committees for EuroVis and Visual Computing for Biology and Medicine . His work bridges Computer Graphics, Artificial Intelligence, and Human-Computer Interaction , with applications in medical and molecular data analysis.