جستجوی استاد راهنمای دانشگاهی

Dimitri Shlyakhtenkoمشاهده پروفایل

استاد

• Free Probability Theory
• Von Neumann Algebras
• C*-Algebras
• +۶ مورد دیگر

Dimitri Shlyakhtenko is a Professor at the University of California, Los Angeles (UCLA) Department of Mathematics, with a distinguished career in free probability, operator algebras, and von Neumann algebras. He has held leadership roles as Department Chair (2012-2015) and Director of the Institute for Pure and Applied Mathematics (2017-). Ph.D. in Mathematics (1997) from UC Berkeley under Dan-Virgil Voiculescu . B.S. with high distinction from the University of Nevada, Reno (1993). His research spans free probability , von Neumann algebras , C*-algebras , L2-invariants , and Poisson geometry . He has pioneered connections between free probability and random matrix theory, subfactor classifications, and non-commutative transport equations. Recent work includes inequalities for free entropy dimension and duality in non-commutative optimal transport. His 15 most recent publications focus on free entropy dimension, crossed products, non-commutative transport, and classification of von Neumann algebras. Topics include non-microstates free entropy , free group factors , quasi-regular inclusions , and type B free probability , with applications to quantum information and ergodic theory. Scientific Awards : Sloan Foundation Fellowship (2001), NSF Fellowships (1994, 1998), Clay Mathematics Institute award (2002), and Bourbaki Seminar recognition (2004). Organized major conferences at Fields Institute, Oberwolfach, IPAM, and UC Berkeley on quantitative linear algebra, free probability, and von Neumann algebras. He has mentored 12 Ph.D. students, including David Jekel and Max Zhou , with research in free analysis and operator-valued distributions. His work also involves collaborations with leading mathematicians like Alain Connes and Sorin Popa .

Rongrong Wangمشاهده پروفایل

دانشیار

• Applied and Computational Harmonic Analysis
• Machine Learning
• Neural network training and generalization
• +۶ مورد دیگر

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

Adviye Ergulمشاهده پروفایل

استاد

• Vascular complications of diabetes and hypertension
• Acute ischemic stroke
• Alzheimer's Disease Related Deteriorias
• +۵ مورد دیگر

Adviye Ergul is a Professor at the Medical University of South Carolina in the Department of Pathology and Laboratory Medicine. She holds secondary appointments at Augusta University and the Charlie Norwood VA Medical Center. Her research focuses on vascular complications of diabetes and hypertension, acute ischemic stroke, and Alzheimer's disease-related dementias, with specific emphasis on endothelial cell biology and vascular pathology. Education : MD from Cerrahpasa Medical School (Istanbul, Turkey, 1987), PhD in Biochemistry & Molecular Biology from University of Miami School of Medicine (1995), postdoctoral training in Vascular Biology at University of Georgia. Her work explores mechanisms of endothelin system dysfunction , microvascular senescence , and inflammatory pathways in diabetic and hypertensive conditions. Recent studies investigate novel therapies like angiotensin receptor agonists and iron chelation for post-stroke cognitive impairment. She has published extensively on diabetes-stroke interactions , endothelin signaling , and sex differences in vascular disease. Key research trends include neurovascular unit remodeling , microemboli-mediated dementia , and mitochondrial quality control in brain injury. Her laboratory developed diabetic stroke models to test interventions like linagliptin and bosentan . Awards : NIH Individual Research Service Award, American Heart Association Scientist Development Award, Veterans Administration Research Career Scientist, Regents’ Professorship, Phi Kappa Phi Honor Society.

Mehrdad Naderiمشاهده پروفایل

مدرس

• Classification
• Cluster Analysis
• Finite Mixture Models
• +۵ مورد دیگر

Mehrdad Naderi is a Lecturer in Statistics at the Department of Mathematics, Physics, and Electrical Engineering , Northumbria University . His academic journey includes a PhD in Mathematical Statistics from Shahid Bahonar University of Kerman (2017) and postdoctoral research at National Chung Hsing University (Taiwan), Ferdowsi University of Mashhad (Iran), and University of Pretoria (South Africa). Education: PhD in Mathematical Statistics, Shahid Bahonar University of Kerman (2017) His research focuses on applied statistical inference with emphasis on classification , cluster analysis , factor analysis , finite mixture models , and EM algorithm for robust estimation. He has contributed to multivariate and matrix-variate analysis, particularly in handling outliers and asymmetrical data structures. Recent work includes three-way data clustering using matrix-variate normal distributions and robust Bayesian inference for censored mixture models. His publications demonstrate expertise in distribution theory, statistical computation, and applications to financial data, environmental modeling, and astrophysics. Current collaborations span multiple institutions, focusing on heavy-tailed distributions and computational methods for complex data structures.

Timothy Beckerمشاهده پروفایل

استادیار

• Genomics
• Deep Learning
• Generative Modeling
• +۸ مورد دیگر

Timothy Becker serves as the John D. MacArthur Assistant Professor of Computer Science at Connecticut College, where he joined in 2023. His research focuses on transforming complex datasets into functional instruments through advanced computational techniques. His academic background includes: B.M. in Music Production from The Hartt School of Music B.S. in Computer Science from the University of Hartford Ph.D. in Computer Science and Engineering from the University of Connecticut Becker specializes in genomics applications but maintains active interdisciplinary collaborations in ecology and transportation. His core methodology integrates deep learning, generative modeling, and data visualization to develop open-source software tools. He emphasizes practical implementations for real-world data analysis and creates interactive tutorials to foster persistent student learning. His publication record from 2018-2025 reveals consistent contributions to bioinformatics and environmental data science, particularly in structural variation analysis and river connectivity modeling. Key trends include developing neural network frameworks for genomic data integration and creating visualization methods for multi-omic datasets. Becker actively seeks undergraduate research collaborators, encouraging students with domain-specific data or research questions to initiate projects. His interdisciplinary approach connects computer science with life sciences and environmental studies through numerous cross-institutional partnerships.

• Particle Physics
• High Energy Physics
• Charmonium Physics
• +۲ مورد دیگر

Zhang W. is a researcher at GSI Helmholtzzentrum für Schwerionenforschung GmbH in Darmstadt, Germany, actively contributing to the field of experimental particle physics through the BESIII experiment at the Beijing Electron Positron Collider. As evidenced by numerous publications from 2024-2025, they specialize in charmonium physics and heavy quark decays, working as part of large international collaborations in the field. Their research focuses on precision measurements in the charm sector, including detailed studies of charmonium states, D meson decays, and searches for exotic hadronic structures. Recent work includes investigations of rare decays, lepton flavor universality tests, and spectroscopy of charmonium and light hadron systems. The diversity of topics covered in their publications indicates broad expertise across multiple aspects of heavy flavor physics. Analysis of their recent publications shows a strong emphasis on precision measurements that test the Standard Model of particle physics and search for potential new physics effects. Their work contributes to our understanding of quantum chromodynamics in the non-perturbative regime and helps map out the spectrum of hadronic states containing charm quarks. Zhang W. collaborates extensively with researchers from institutions worldwide, as reflected in the large author lists typical of modern particle physics publications. While specific details about their academic rank or departmental affiliation are not provided in the available information, their active publication record suggests they hold a significant research position within the particle physics community.

Christoph Fraenzمشاهده پروفایل

پژوهشگر

• Neuroimaging
• Cognitive Psychology
• Individual Differences
• +۴ مورد دیگر

Dr. Christoph Fraenz is a researcher at the Leibniz Research Centre for Working Environment and Human Factors (IFADO) in Dortmund, Germany, where he works within the Psychology and Neurosciences department in the Neuroimaging and interindividual differences research group under Prof. Dr. Michael Nitsche. His research focuses on the neural basis of interindividual differences in cognitive functions and personality, utilizing a multimodal approach combining psychometrics, fMRI, DTI and EEG methodologies. Dr. Fraenz's work primarily investigates how variations in brain structure and function relate to individual differences in intelligence, personality traits, and cognitive abilities across the human population. Dr. Fraenz completed his academic training with a Bachelor's degree in Psychology from Westfälische Wilhelms University of Münster (2009-2012), followed by a Master's degree in Psychology from Ruhr University Bochum (2012-2015). He earned his PhD from the Department of Biopsychology at Ruhr University Bochum (2015-2019) and subsequently worked as a Research Associate there (2019-2020) before joining IFADO. His publication record demonstrates a strong focus on understanding the relationship between brain structure/function and cognitive abilities, with recent work particularly examining white matter microstructure, neurite density imaging, functional connectivity patterns, and genetic correlates of brain organization. His research often employs polygenic scoring approaches to understand how genetic factors contribute to individual differences in cognition. Dr. Fraenz has published extensively in high-impact neuroscience journals including Cerebral Cortex, Nature Communications, NeuroImage, and Human Brain Mapping, with numerous collaborative publications featuring researchers like Erhan Genç, Caroline Schlüter, and Sebastian Ocklenburg.