جست‌وجوی استاد و پژوهشگر

• Machine Learning
• Computer Vision
• Biomedical Data Science
• +۳ مورد دیگر

René Vidal is the Rachleff & Penn Integrates Knowledge (PIK) University Professor of Electrical and Systems Engineering & Radiology at the University of Pennsylvania and Director of the Center for Innovation in Data Engineering and Science (IDEAS). He holds secondary appointments in Computer and Information Science and Statistics and Data Science. His research focuses on the foundations of deep learning, trustworthy AI, and their applications in computer vision and biomedical data science. Education: B.S. (Electrical Engineering, valedictorian) from Pontificia Universidad Católica de Chile (1997), M.S. and Ph.D. (Electrical Engineering and Computer Sciences) from UC Berkeley (2000 and 2003). Prior roles include Professor at Johns Hopkins University (2004–2022) and leadership roles in institutions like MINDS and THEORINET. Research spans machine learning (mathematics of deep learning, manifold learning), computer vision (activity recognition, medical imaging), biomedical data science (cardiac MRI analysis, autism diagnosis), and dynamical systems. Awards include IEEE Fellow (2014), IAPR Fellow (2016), ACM Fellow, and the IEEE Edward J. McCluskey Technical Achievement Award (2021). Current lab members include 15+ graduate students and postdocs working on topics like adversarial robustness, optimization theory, and biomedical applications. His work is supported by grants from the Department of Defense and collaborations with organizations like Amazon and NORCE. Labs/Teams: Director of IDEAS Center, MINDS, and THEORINET. Active in editorial roles for journals like TPAMI and CVIU, and program chair for ICCV 2015 and CVPR 2014.

• Capital Structure
• Debt Financing
• Corporate Finance
• +۴ مورد دیگر

Sami Attaoui is a Full Professor of Finance and Head of the Finance Department at NEOMA Business School. He also serves as the Academic Director of the Global Executive MBA program. Holding a PhD in Management and Finance from the University of Paris Panthéon-Sorbonne, his research focuses on capital structure decisions, green financing, and financial asset valuation. His work bridges theoretical finance with practical corporate finance challenges, emphasizing the interplay between corporate debt structures and environmental economic factors. Key research areas include capital structure optimization, mergers & acquisitions financing, and green bond mechanisms. He has published extensively in top-tier journals such as Financial Management , Journal of Corporate Finance , and Journal of Economic Dynamics and Control . His recent studies explore the fundamentals of Sharpe ratios in commodity markets and the impact of ambiguity aversion on corporate leverage. Dr. Attaoui is an active member of professional organizations, including the Association Française de Finance and the American Finance Association. His academic contributions span theoretical models of debt prioritization, optimal payment methods in acquisitions, and the valuation of performance-sensitive debt instruments. While no specific awards are highlighted, his work has been presented at major international conferences such as the Eastern Finance Association Annual Meeting and the FMA European Conference. His teaching and research integrate real-world financial markets, emphasizing practical applications of financial theories. Current projects continue to explore the intersection of environmental finance, corporate governance, and innovative debt structures. Labs/Teams: Not explicitly mentioned in the provided materials.

Stéphane Mallatمشاهده پروفایل

استاد

• Signal Processing
• Wavelet Theory
• Machine Learning
• +۴ مورد دیگر

Stéphane Mallat is a Professor at the Collège de France, holding the Chair of Data Sciences. He is also affiliated with the École normale supérieure in Paris, where his address is located. His research focuses on signal processing, wavelet theory, and their applications in machine learning and data sciences. Mallat pioneered wavelet transforms for signal decomposition and has contributed to scattering transforms for invariant feature extraction in deep learning. His work bridges applied mathematics, harmonic analysis, and computational methods, with impactful applications in image processing, audio analysis, and quantum chemistry. Publicly listed articles span from foundational wavelet theory (1989) to recent advances in scattering networks (2020). His research trends emphasize geometric signal representations, sparse approximations, and interdisciplinary applications across physics and engineering. His CV and publications are available through institutional links, though specific awards or grants are not explicitly detailed in the provided texts. He collaborates extensively with researchers in mathematics and computer science, advancing theoretical frameworks with practical implementations.

• Elementary Particle Physics
• Astroparticle Physics
• Nuclear Physics
• +۲ مورد دیگر

Lola Smaragda is a Professor at the Department of Theoretical and Mathematical Physics, Astronomy and Astrophysics within the School of Sciences at the University of Patras. She has served as faculty since 2004, advancing to full Professor in 2009, and maintains active Visiting Professor roles across global institutions. Education: 1979-1985: Middle/High School at Barvakeio Model School 1985-1989: Physics Degree with Honors, University of Athens 1989-1993: PhD in Physics, University of Oxford (Thesis: Cosmological Implications of Unification Theories) Research Focus: Her work bridges Elementary Particle Physics and Cosmology , specializing in neutrino physics using data from Super-Kamiokande and SNO experiments, supersymmetric extensions of the Standard Model, and searches for new particles at CERN facilities. Her cosmological research tackles dark matter, inflationary models, and baryogenesis through theoretical frameworks. Publication Impact: With 94 publications and 5,700+ SPIRES citations (h-index 35), her highly influential work spans collider phenomenology (HERA, LHC), neutrino mass mechanisms, and future facility physics (ILC, Neutrino Factories), demonstrating consistent leadership in high-energy theory from 1997-2009. Awards: Marie Curie Excellence Grant (EXT) for establishing Elementary Particle Physics research group (2005-2009) Mentorship & Grants: She has supervised three doctoral students while securing major European network roles: UNIVERSENET Representative (2006-2010) for particle-cosmology research and HEPTOOLS Representative (2006-2010) for LHC computational physics. Collaborations: Her CERN and Heidelberg University background fuels ongoing partnerships with LHC experimental teams and international consortia developing next-generation colliders and neutrino facilities.

Papaioannou Georgiosمشاهده پروفایل

استادیار

• Real-time Computer Graphics
• Virtual Reality
• Photorealistic Imaging
• +۳ مورد دیگر

Georgios Papaioannou Georgios Papaioannou is an Assistant Professor at the Department of Informatics, Athens University of Economics and Business (AUEB). He holds a BSc and PhD in Informatics/Computer Science from the National and Kapodistrian University of Athens. His research focuses on real-time computer graphics, virtual reality, photorealistic rendering, and 3D pattern recognition with applications in cultural heritage digitization and interactive environments. Education BSc in Informatics, National and Kapodistrian University of Athens PhD in Computer Science, National and Kapodistrian University of Athens Research Interests His work spans real-time rendering techniques, virtual reality systems, 3D object reconstruction, and cultural heritage preservation. Notable projects include the PRESIOUS EU project for predictive digitization of cultural objects and the Virtual Archaeologist system for fractured artifact reassembly. Key Contributions Dr. Papaioannou has authored influential papers on global illumination algorithms, volume-based ambient occlusion, and real-time graphics optimization. His work integrates computer vision and machine learning to solve challenges in interactive visualization and archaeological reconstruction. Professional Activities A member of Eurographics, ACM, and SIGGRAPH, he actively reviews for top computer graphics conferences. His lab focuses on advancing real-time rendering technologies for immersive applications, including VR systems for cultural heritage education and historical reenactment.

Gary Dargushمشاهده پروفایل

استاد

• Computational Mechanics
• Applied Mechanics
• Size-Dependent Mechanics
• +۷ مورد دیگر

Professor Gary Dargush is a faculty member in the Department of Mechanical and Aerospace Engineering at the University at Buffalo, part of the School of Engineering and Applied Sciences. His research focuses on computational and applied mechanics, emphasizing size-dependent mechanics, boundary element methods, finite element methods, thermomechanics, and structural dynamics. He holds a PhD in Civil Engineering from the University at Buffalo (1987). His research interests include advanced computational techniques for multi-physics problems, such as fluid-structure interaction, thermal effects, and micro-scale phenomena. He has contributed to the development of boundary element methods for complex systems and has explored applications in earthquake engineering, biomedical devices (e.g., intracranial aneurysm modeling), and material science. Awards and Honors State University of New York Chancellor’s Award for Excellence in Teaching (2014) University at Buffalo President’s Circle support for Active Learning in Dynamics (2014) Research & Grants Professor Dargush’s work spans theoretical and applied mechanics, with a focus on developing numerical methods for size-dependent and multi-physics systems. His research often involves collaborations across disciplines, including materials science, biomedical engineering, and geomechanics. He has advised numerous graduate students and has secured funding for projects related to computational mechanics and active learning initiatives in engineering education. Labs & Teams His research is supported by advanced computational facilities at the University at Buffalo, where he leads projects in computational mechanics and structural dynamics. He is actively involved in interdisciplinary teams addressing challenges in smart materials, energy systems, and biomedical devices.

David Merollaمشاهده پروفایل

دانشیار

• Race and Racism
• Sociology of Education
• Social Psychology
• +۳ مورد دیگر

David Merolla is an Associate Professor and Department Chair of the Department of Sociology at Wayne State University. He holds a Ph.D. in Sociology from Kent State University (2010). His research focuses on race and racism, sociology of education, social psychology, and quantitative methods. Merolla examines issues such as structural racism, educational disparities, policing, and identity formation through interdisciplinary lenses. His work spans topics like immigration attitudes across racial groups, genetic ancestry testing’s impact on racial identity, and the role of racial prejudice in policy attitudes (e.g., marijuana legalization). He also investigates disparities in officer-involved shootings and the sociological impacts of the pandemic on pediatric health. Merolla teaches courses such as SOC1020 (Social Problems) and SOC7290 (Advanced Social Statistics), emphasizing methodological rigor and critical analysis. His publications appear in journals like Sociological Focus , Sociological Compass , and Sociology of Race and Ethnicity . His teaching and research reflect a commitment to addressing systemic inequalities and advancing evidence-based solutions.

Xinfeng Liuمشاهده پروفایل

استاد

• Computational Biology
• Mathematical Modeling of Cancer Stem Cells
• Signal Transduction
• +۴ مورد دیگر

Xinfeng Liu serves as Professor and Undergraduate Director in the Department of Mathematics at the University of South Carolina. His academic journey includes progression from Assistant Professor (2009-2013) to Associate Professor (2013-2017) and finally to full Professor (2018-present), following a Visiting Assistant Professor position at UC Irvine (2006-2009). His research spans Computational Biology with focus on cancer stem cell modeling and signal transduction mechanisms, alongside Numerical PDEs specializing in front tracking methods and integration factor techniques. Liu's work bridges mathematical theory with biological applications, particularly in morphogen gradient formation and MAPK cascade regulation. His computational approaches address complex phenomena like Rayleigh-Taylor instability in fluid dynamics. Liu's recent publications demonstrate strong trends in developing numerical methods for free boundary problems in biological systems, with significant contributions to cancer stem cell modeling. His work increasingly integrates stochastic elements and time-delay systems in therapeutic response modeling. NSF Mathematical Biology Division grant DMS1853365 (2019-2022) NSF Mathematical Biology Division grant DMS1308948 (2013-2017) NSF Mathematical Biology Division grant DMS1019544 (2010-2014) University of South Carolina ASPIRE I grant (2013-2014) South Carolina EPSCoR/IDeA GEAR program (2011-2013) Liu has mentored three doctoral students to completion, all securing competitive postdoctoral positions at Los Alamos National Lab, University of Waterloo, and University of North Texas. His teaching portfolio spans computational mathematics, differential equations, and advanced analysis courses since 2009, including honors sections and specialized topics like Modeling of Complex Biological Systems.

Milana Čolićمشاهده پروفایل

دانشیار

• Polyatomic Gas Dynamics
• Kinetic Theory of Gases
• Non-Equilibrium Thermodynamics
• +۳ مورد دیگر

Milana Čolić is an Associate Professor in the Department of Applied Analysis at the Faculty of Sciences, University of Novi Sad. Her research focuses on polyatomic gas dynamics, kinetic theory, non-equilibrium thermodynamics, and Boltzmann equation analysis. She holds a Ph.D. and maintains an active profile in mathematical physics and fluid mechanics modeling. Her work emphasizes the mathematical and computational modeling of complex gas systems, including polyatomic gas mixtures, rarefied gas behavior, and shock structure analysis. Key contributions include the development of multi-velocity/multi-temperature models and energy methods for Boltzmann equations. She has published extensively on topics such as kinetic closure hierarchies and dynamic pressure effects in non-equilibrium systems. Dr. Čolić collaborates with international researchers and contributes to both theoretical advancements and applied computational methods in fluid dynamics. Her research bridges applied mathematics with engineering applications, addressing real-world phenomena like phase-change processes (e.g., the espresso coffee problem) and gas mixture interactions. Her academic profile includes a personal website (http://personal.pmf.uns.ac.rs/milana.colic/) and active engagement with the PMF academic community. Research interests are consistently aligned with advancing kinetic theory and fluid mechanics through rigorous mathematical frameworks.

Sheila Cunninghamمشاهده پروفایل

استاد

• Social Cognition
• Developmental Psychology
• Educational Psychology
• +۴ مورد دیگر

Professor Sheila Cunningham is a leading academic in social cognition and developmental psychology at Abertay University, within the Department of Sociological and Psychological Sciences. She joined the university in 2011 after completing her PhD and post-doctoral research at the University of Aberdeen. Her research focuses on self-processing biases, particularly how self-referential cues influence learning and memory across the lifespan, and the impact of gender stereotypes on educational choices among adolescents. She has secured significant grants from prestigious organizations such as the ESRC, ERC, Leverhulme Trust, and Carnegie Trust. Her work bridges academic research with practical applications, including teacher training programs and policy engagement through initiatives like the Scottish Government’s Gender Equalities Taskforce. Professor Cunningham is a Senior Fellow of the Higher Education Academy and serves as an Associate Editor for the journal Memory . Key research themes include: self-reference effects in memory, gender stereotype development, and applying cognitive biases to improve educational outcomes. She leads Abertay’s MSc Research Methods in Psychology program from 2025 and has supervised students on modules like PSY216 and PSY314. Her outreach efforts include public lectures and workshops, such as the Leverhulme Public Lecture series and engagement with organizations like the YMCA. Recent studies explore topics like ADHD’s impact on self-processing, the role of pronouns in mathematical problem-solving, and social learning biases in adolescents. Grants include a 2023 Leverhulme Trust award (£227,860) and a 2020 ESRC grant (£484,575). Her work has been published in journals like Child Development , Cognitive Science , and Psychological Science .

Ellen Luptonمشاهده پروفایل

مدرس

• Graphic Design
• Typography
• Design Theory
• +۳ مورد دیگر

Ellen Lupton is an Instructor at The Cooper Union's School of Art, specializing in Graphic Design. She holds dual roles as Senior Curator of Contemporary Design at Cooper Hewitt, Smithsonian Design Museum, and Director of the Graphic Design MFA Program at Maryland Institute College of Art (MICA). Her work bridges academic teaching, museum curation, and design practice. She earned her BFA from The Cooper Union in 1985. Lupton’s research focuses on design processes, typography, and storytelling. Her influential books include Thinking with Type , Graphic Design: The New Basics , and Type on Screen , which explore foundational design principles and their contemporary applications. Her upcoming book Design Is Storytelling (2017) emphasizes narrative strategies in design. Her exhibitions include Beauty—Cooper Hewitt Design Triennial and How Posters Work , showcasing innovative approaches to design communication. Lupton’s contributions span academic publishing, museum exhibitions, and educational leadership in graphic design.

• Operations Research
• Decision Support Systems
• Optimization Algorithms
• +۵ مورد دیگر

Daniele Pretolani is an Associate Professor at the Department of Engineering Sciences and Methods, University of Modena and Reggio Emilia. He specializes in Operations Research (MATH-06/A) with a focus on decision support systems, multi-objective optimization, and directed hypergraph algorithms. Teaches Methods and Algorithms for Optimization in Digital and Creative Industry (Management Engineering) Teaches Models and Methods for Decision Support (Management Engineering) His research explores: Stochastic time-dependent network routing Multi-criteria decision analysis for supplier selection Hypergraph reductions for satisfiability problems Visual decision support tools for composite indexes Recent work includes developing a decision support system for global service providers (2024) that improved supplier selection by 25% over company practices, and foundational contributions to the SDEWES sustainability index (2018-2020). No specific awards or student advising details were mentioned in the provided texts.

Renée Stevensمشاهده پروفایل

دانشیار

• Graphic Design
• Motion Design
• Augmented Reality
• +۴ مورد دیگر

Renée Stevens serves as Associate Professor and Associate Chair of the Visual Communications Department at Syracuse University's S.I. Newhouse School of Public Communications. She oversees both undergraduate and graduate design programs while maintaining an active professional design practice. Her research interests focus on Graphic Design , Augmented Reality , and Immersive Design , with particular emphasis on how these technologies can help overcome learning disabilities and create more accessible learning environments. Her teaching portfolio includes graphic design theory and practice, motion design, and immersive design for augmented reality, as well as the undergraduate design capstone course that functions as a professional design studio. Stevens' publications have established her as a thought leader in design education, with her book Powered by Design receiving significant recognition including being named one of the 'Top 10 Graphic Design Books' by MasterBundles and 'One of the Best Graphic Design Books for Beginners' by BookAuthority. 2017 Educator to Watch by Graphic Design USA Awarded by Graphis, Print, GDUSA, AEJMC, Minted and Light Work Active member of AIGA Upstate New York (Assistant Director of Education) As creative and managing director of the annual 'Pixels and Print' design workshop, she provides students with real-world collaborative experiences focused on designing for social good. She has presented her work internationally at SXSW, AIGA conferences, and the Eastern European Conference on Social Media.

John Ravenمشاهده پروفایل

استاد

• Socio-Cybernetics
• Systems Thinking
• Intelligence Measurement
• +۳ مورد دیگر

Professor John Raven is a leading academic in socio-cybernetics and systems thinking, focusing on paradigm shifts in education, organizational management, and societal governance. His research critiques traditional intelligence metrics and advocates for holistic, systemic approaches to competence assessment and societal sustainability. Key areas include: Reform of hierarchical educational systems to foster creativity and innovation Development of socio-cybernetic frameworks to map invisible social forces Ethical use of intelligence assessments like Raven Progressive Matrices Advocacy for non-hierarchical societal management to address ecological crises Publications include 'Competence in Modern Society' and 'The New Wealth of Nations', emphasizing systemic change and collective intelligence.

Jesse H. Goldbergمشاهده پروفایل

استاد

• Systems Neuroscience
• Comparative Neuroscience
• Motor Learning
• +۶ مورد دیگر

Jesse H. Goldberg is a Professor and holds the Dr. David and Dorothy Joslovitz Merksamer Professorship in Biological Sciences at Cornell University, with dual appointments in the Department of Neurobiology and Behavior and Psychology within the College of Arts and Sciences. He leads the Goldberg Lab, which focuses on comparative systems neuroscience through the study of vocal communication in songbirds and parrots, as well as motor control in mice. Dr. Goldberg's research investigates how the brain implements learning through trying new things, evaluating outcomes, and modifying future performance. His work emphasizes comparative approaches to distinguish general neural principles from species-specific solutions to motor control problems. The lab combines electrophysiology, optogenetics, and machine learning-guided behavioral analysis to study neural mechanisms in cortex, basal ganglia, and cerebellum—brain regions implicated in disorders such as Parkinson's, dystonia, and ADHD. His research has revealed significant insights into dopamine signaling during vocal learning, demonstrating that songbirds receive dopaminergic feedback when hitting the right note and that these signals are dynamically gated by social context. Goldberg discovered an actor-critic circuit motif in songbird basal ganglia similar to those used in reinforcement learning algorithms, and identified how ventral pallidal regions generate predicted quality signals for song syllables. Dr. David and Dorothy Joslovitz Merksamer Professor in Biological Sciences Klarman Fellow (2022-23) Pew Investigator Dr. Goldberg's work has important implications for understanding how neural circuits implement learning across species, with potential applications for treating movement and neuropsychiatric disorders. His lab continues to investigate how neural mechanisms of learning and performance evaluation operate across different social contexts and species.