Random Polymer Measures Professors and Supervisors | ApplySharif

جست‌وجوی استاد و پژوهشگر

استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشی‌تان را پیدا کنید و با او ارتباط بگیرید.

نمایش ۱-۱۵ از ۷۹ استاد راهنما

اطلاعات این پروفایل‌ها از صفحات عمومی دانشگاه‌ها جمع‌آوری شده و ممکن است به‌روز نباشد.

Ewain Gwynneمشاهده پروفایل

استاد

University of ChicagoUnited States

Ewain Gwynne is a Professor of Mathematics at the University of Chicago, affiliated with the Committee on Computational and Applied Mathematics (CCAM) and the Statistics Department. He previously held postdoctoral positions at the University of Cambridge and earned his Ph.D. from MIT in 2018 under Scott Sheffield. His research focuses on probability theory, particularly random geometric structures in statistical mechanics, including Schramm-Loewner evolution (SLE), Liouville quantum gravity (LQG), and random planar maps. Education: Ph.D. in Mathematics, MIT (2018); M.Sc., MIT (2015); B.Sc., Northwestern University (2013). Research Interests: Random geometric objects in statistical mechanics Liouville quantum gravity and its metric properties Random planar maps and their scaling limits SLE and its relationship with LQG Random walks on random planar maps Percolation and permutons His recent articles explore topics such as supercritical LQG, Gaussian curvature on random maps, and harmonic balls in LQG. He has advised multiple Ph.D. students and serves as an associate editor for Probability and Mathematical Physics . His work bridges probability theory, geometry, and mathematical physics, with applications to understanding critical phenomena in random systems.

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Shirshendu Gangulyمشاهده پروفایل

دانشیار

University of California, BerkeleyUnited States

Shirshendu Ganguly is an Associate Professor in the Department of Statistics at the University of California, Berkeley. His research focuses on probability theory, statistical physics, and their applications, including percolation models, phase transitions, Markov chains, and random graphs. He holds a PhD in Mathematics from the University of Washington and has held postdoctoral positions at UC Berkeley. Ganguly has been recognized with the 2019 Sloan Research Fellowship. Education: PhD in Mathematics, University of Washington, 2011–2016 Miller Postdoctoral Fellow, UC Berkeley, 2016–2018 Research Interests: Probability Theory, Statistical Mechanics, Markov Chains, Random Graphs, Percolation Theory, Sparse Combinatorial Structures His work explores geometric and probabilistic phenomena in disordered systems, including polymer models, self-organized criticality, and random matrix theory. He has advised multiple PhD students and contributes to teaching advanced probability courses at Berkeley. Awards: 2019 Sloan Research Fellowship

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Louis Schmidtمشاهده پروفایل

استاد

McMaster UniversityCanada

Professor Louis Schmidt is a leading academic in the Department of Psychology, Neuroscience & Behaviour at McMaster University , with a research focus on developmental psychophysiology, temperament, and the long-term effects of early adversity. His work bridges neuroscience, psychology, and behavioral science, emphasizing the interplay between brain function and socio-emotional development across the lifespan. Key research themes: Shyness, social anxiety, autism spectrum disorder, schizophrenia, and outcomes of extremely low birth weight. Recognized for mentoring postdoctoral fellow Kristie Poole, who was celebrated as a role model in the Child Emotion Laboratory. Scientific Awards : Royal Society of Canada recognition for contributions to research and scholarship. Research Trends from 15 recent publications include: Neurophysiological mechanisms of shyness (EEG, ERP, RSA) Impact of antenatal corticosteroids on adult brain function Intergenerational effects of maternal mental health interventions Cross-cultural comparisons of temperamental shyness Developmental consequences of preterm birth Behavioral and neural correlates of social anxiety in diverse populations Grants & Collaborations : Led the SNACS randomized controlled trial on antenatal corticosteroids, with applications in obstetrics and developmental neuroscience. Collaborates extensively on topics like autism spectrum disorder, schizophrenia, and emotion regulation. Labs & Teams : Directs the Child Emotion Laboratory at McMaster University, fostering interdisciplinary research on developmental psychopathology and neural mechanisms of temperament.

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Alex Dunlapمشاهده پروفایل

استادیار

Duke UniversityUnited States

Alex Dunlap is an Assistant Professor in the Department of Mathematics at Duke University. His research focuses on probability theory, partial differential equations (PDEs), and applied mathematics, particularly the asymptotic behavior of stochastic PDEs. Before joining Duke in 2023, he was an NSF postdoctoral fellow at NYU Courant, sponsored by Jean-Christophe Mourrat and Yuri Bakhtin. He earned his Ph.D. from Stanford University in 2020 under the supervision of Lenya Ryzhik. His work involves studying nonlinear stochastic PDEs such as the KPZ equation, stochastic Burgers equation, and stochastic heat equations. He is particularly interested in universality phenomena, fluctuation scaling, and invariant measures. Dunlap co-organizes the Duke Probability Seminar and has published extensively in top journals including Annals of Probability , Communications on Pure and Applied Mathematics , and Archive for Rational Mechanics and Analysis . His research is supported by NSF grant DMS-2346915. Notable contributions include work on viscous shock fluctuations, Edwards-Wilkinson universality in 2D systems, and stationary solutions of stochastic Burgers equations. He has collaborated with leading researchers such as Cole Graham, Yu Gu, and Lenya Ryzhik.

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Samuel Johnstonمشاهده پروفایل

مدرس

King’s College LondonUnited Kingdom

Samuel Johnston is a Lecturer in Probability Theory at the Department of Mathematics, King's College London, affiliated with the Faculty of Natural, Mathematical & Engineering Sciences. He joined King's in 2022 after postdoctoral roles at the University of Bath, University of Graz, and University College Dublin. MMath, University of Oxford (2014) PhD in Probability, University of Bath (2017) Johnston's research spans probability theory, with a focus on stochastic processes involving branching, coalescence, and fragmentation. He actively explores free probability, random matrices, integrable combinatorics, and combinatorial approaches to the Jacobian conjecture. His work intersects with statistical physics and asymptotic geometric analysis. Recent publications highlight coalescent structures in heavy-tailed branching processes, integrable probability models, free probability via entropic transport, and convexity in high dimensions. Keywords include universality classes, Berry-Esseen bounds, and fragmentation-scaling limits. Samuel has not been mentioned to have received specific scientific awards or honors. He advises PhD students Rohan Shiatis (2023-) and Neil Mukerji (2024-). Collaborations span institutions in the UK, USA, Mexico, Austria, and Poland, with invited talks at global conferences including Xiangtan University, Imperial College London, and UCLA.

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Sourav Sarkarمشاهده پروفایل

دانشیار

University of CambridgeUnited Kingdom

Sourav Sarkar is a University Associate Professor in Probability at the Department of Pure Mathematics and Mathematical Statistics (DPMMS), University of Cambridge (since July 2024) and a Fellow of Trinity Hall. Previously, he held positions as an Assistant Professor at DPMMS (2021–2024), Postdoctoral Fellow at the University of Toronto (2019–2021), and completed his Ph.D. in Statistics at UC Berkeley (2019) under Prof. Alan Hammond. His education includes a BSc (2013) and MSc (2015) in Statistics from the Indian Statistical Institute, Kolkata, advised by Prof. Parthanil Roy. Research Interests : Probability theory with a focus on KPZ universality class, random growth models (e.g., last passage percolation, exclusion processes), Coulomb gas, and percolation theory. His work bridges stochastic processes, mathematical physics, and statistical mechanics. Teaching : Teaches advanced courses in Probability and Stochastic Calculus at the University of Cambridge, including Part II courses on Applied Probability and Probability & Measure. Previously taught at UC Berkeley, where he received the Outstanding Graduate Student Instructor Award (2019). Publications : Focuses on KPZ fixed point, geodesic properties, and phase transitions in interacting particle systems. Recent work includes studies on the directed landscape, stable random fields, and competitive erosion dynamics. Awards : Recognized for exceptional teaching at Berkeley and sustained contributions to probability theory research.

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Carine J.M. Doggenمشاهده پروفایل

استاد

University of TwenteNetherlands

Carine J.M. Doggen is a Full Professor in Health Technology & Services Research at the TechMed Centre, University of Twente. She also serves as Scientific Director at Rijnstate Hospital since October 2017. Her academic career includes previous positions as Senior Researcher at Leiden University Medical Center (2000-2009), University of Washington, Seattle (2002-2003), and Sanquin Blood Bank (2006-2009). Her research focuses on evaluating healthcare innovations, particularly technologies enabling the transition of care from hospitals to home settings. Dr. Doggen specializes in assessing the implementation, reliability, and effectiveness of new medical technologies including wearable sensors and remote monitoring systems. Her work examines measurement validity and incorporates perspectives from both healthcare providers and patients. Analysis of her recent publications reveals strong expertise in cardiovascular technology evaluation, digital health interventions, and quality of life assessment. Her research shows particular strength in randomized clinical trials of medical devices, health technology assessment methodologies, and post-COVID health outcomes research. Dr. Doggen has presented her work at numerous conferences, with recent oral presentations including 'Towards personalised medicine: the potential of intensive longitudinal data to assess the interplay of chronic diseases' (2024) and 'Prognostic markers for acute heart failure in Chronic Obstructive Pulmonary Disease' (2021). She has also contributed to media discussions about healthcare innovations through the Rijnstate Collegetour series.

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Jeremy Quastelمشاهده پروفایل

استاد

University of TorontoCanada

Jeremy Quastel is a University Professor in the Department of Mathematics at the University of Toronto, within the Faculty of Arts and Science. He has been a prominent figure in the department since returning to Canada in 1998, serving as Chair of the Department of Mathematics from 2017 to 2021. Under his leadership, the mathematics department has become a world center for research in random interface growth and the KPZ universality class. His educational background includes: Undergraduate studies at McGill University PhD from the Courant Institute (NYU) in 1990 under S.R.S. Varadhan Professor Quastel is a specialist in probability theory, stochastic processes, and partial differential equations . His research focuses on the large scale behavior of interacting particle systems and stochastic partial differential equations, with particular emphasis on the Kardar-Parisi-Zhang (KPZ) universality class. He made groundbreaking contributions by discovering the first exact distributional solutions of the KPZ equation in 2010 and the KPZ fixed point in 2017 - the scaling invariant, integrable Markov process at the center of the KPZ universality class. His work bridges probability theory, mathematical physics, and statistical mechanics, with applications to interface growth models and directed polymers. Analysis of his recent publications reveals a consistent focus on KPZ-related phenomena, with increasing sophistication in understanding the KPZ fixed point and its properties. His work has evolved from discovering exact solutions to establishing convergence results and exploring connections to other integrable systems like the Toda lattice. The research spans theoretical developments in stochastic PDEs, connections to random matrix theory, and applications to physical growth models. His scientific achievements have been recognized with numerous prestigious awards: Sloan Fellow (1996-98) Invited session speaker at the International Congress of Mathematicians (2010) Current Developments in Mathematics lectures (2011) St. Flour lectures (2012) Plenary speaker at the International Congress of Mathematical Physics (2012) Fellow of the Royal Society of Canada (2016) Fellow of the Royal Society (2021) CRM-Fields-PIMS prize (2018) Jeffery-Williams Prize of the Canadian Mathematical Society (2019) Professor Quastel has supervised numerous PhD students who have gone on to successful careers in academia and industry, including Xuicai Ding at UC Davis, Hanna Jankowski at York University, and Konstantin Matetski at Columbia University. His research group has attracted many postdoctoral fellows who have become leading researchers in probability theory. While specific grant information isn't detailed in the provided text, his sustained research output and leadership position suggest significant grant funding supporting his work in probability theory and stochastic processes. Though not explicitly mentioned in the provided text, Professor Quastel's work has established the University of Toronto as a global hub for research on the KPZ universality class. His collaborations span institutions worldwide, and his research group likely includes graduate students, postdocs, and visiting scholars working on various aspects of stochastic processes, interface growth models, and integrable probability. His recent work on the KPZ fixed point represents the culmination of decades of research in this field.

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Timo Seppalainenمشاهده پروفایل

استاد

University of South CarolinaUnited States

Timo Seppäläinen is a Professor and the John and Abigail Van Vleck Chair of Mathematics at the University of Wisconsin-Madison since 2005. He is affiliated with the Mathematics Department under the College of Letters & Science. Education: Ph.D. in Mathematics (1991) from the University of Minnesota M.Sc. in Industrial Engineering and Management (1986) from Aalto University High School Diploma (1980) from Helsinki I Normal School Research Interests: His work primarily focuses on probability theory , encompassing topics such as motion in random media, first- and last-passage percolation, interacting particle systems, and large deviation theory. He has contributed to graduate-level stochastic analysis and authored lecture notes on the corner growth model , exclusion processes, and renewal theory. His research has been supported by the National Science Foundation and the Wisconsin Alumni Research Foundation. Scientific Awards and Honors: 2000 Prix Institut Henri Poincaré-Gauthier Villars 2010 Fellow of the Institute of Mathematical Statistics 2011 Van Vleck Research Prize 2014 IMS Medallion Lecturer and Invited Speaker at International Congress of Mathematicians 2015 Vilas Faculty Mid-Career Investigator Award 2015-2016 and 2023-2024 Simons Fellow in Mathematics 2016 Van Vleck Chair of Mathematics 2017 Fellow of the American Mathematical Society Teaching and Editorial Work: He teaches undergraduate and graduate courses in probability theory and stochastic processes, including Math 632 , Math 733-734 , and Math 735 . He has served on editorial boards and organized probability seminars.

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Richard A. Registerمشاهده پروفایل

استاد

Princeton UniversityUnited States

Richard A. Register is the Eugene Higgins Professor of Chemical and Biological Engineering at Princeton University and serves as Director of the Princeton Materials Institute . He is affiliated with the Andlinger Center for Energy and the Environment as an executive committee member and associated faculty. Education : Ph.D. in Chemical Engineering (1989, University of Wisconsin-Madison); M.S. in Chemical Engineering Practice (1985), S.B. in Chemical Engineering (1984), and S.B. in Chemistry (1983) from MIT Research Interests : Focuses on materials synthesis, processing, and properties of polymers, particularly multi-phase polymeric systems like block, gradient, and random copolymers. His work bridges fundamental polymer physics with applications in energy, environment, and scalable nanofabrication. Selected Research Trends : Recent publications highlight block copolymers for biobutanol recovery, melt-processing of polyolefin multiblock copolymers, shear-induced orientation of nanocylinders, crystallization modes in microdomains, and lithographic applications for dense nanoscale arrays. Scientific Awards : Inaugural Distinguished Faculty Service Award (2025), Distinguished Teacher Award (2018), Fellowships in AIChE (2014), ACS (2012), and APS (2001), Graduate Mentoring Award (2008), and early-career honors from NSF (1992) and Unilever (1992) Advising and Grants : Mentors graduate students including Asmita Ghosh and Katherine Gunter. Leads projects funded by DOE on recyclable plastic packaging and collaborates across disciplines via Princeton's Materials Institute and Andlinger Center. Labs and Teams : Heads the Polymer Research Laboratory at Princeton, overseeing a team of graduate students and postdocs. His lab integrates synthesis, structural characterization (SAXS, WAXS, SEM, TEM, AFM), and property measurements to advance polymeric materials.

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Matthew J Comstockمشاهده پروفایل

دانشیار

Michigan State UniversityUnited States

Matthew J Comstock is an Associate Professor in the Department of Physics & Astronomy at Michigan State University, where he has led a research program since August 2012 focused on single-molecule biophysics. His work pioneers high-resolution optical tweezers and fluorescence techniques to observe biomolecular processes at angstrom-scale resolution. Education 2008: Ph.D., Physics, University of California, Berkeley 2000: B.S., Physics, University of Chicago Research Focus Dr. Comstock investigates molecular motors and nucleic acid-processing enzymes through real-time single-molecule observation. His lab develops cutting-edge instrumentation combining optical trapping with fluorescence detection to study enzyme kinetics, DNA replication mechanics, and protein folding dynamics. Technical innovations include ultrahigh-resolution optical traps capable of single-fluorophore sensitivity and novel force transducers using engineered DNA. Publication Trends Analysis of his 15 most recent publications (2016-2020) reveals three dominant themes: 1) Telomerase and helicase mechanisms using optical tweezers, 2) Instrumentation advances merging force spectroscopy with fluorescence, and 3) Fundamental studies of nucleic acid mechanics. His work consistently bridges physics and biology to uncover molecular-scale mechanisms in enzymatic catalysis. Scientific Recognition Jerry Cowen Chair of Physics (awarded upon faculty appointment) Mentorship and Resources As faculty at MSU, Dr. Comstock mentors graduate students in biophysics research though specific advisees aren't listed in source materials. His laboratory operations suggest active grant funding from agencies like NIH or NSF, supported by technical innovations in single-molecule instrumentation. Research Facilities His group operates two laboratories in MSU's Biomedical Physical Sciences Building: Room B149 (517-884-5491) specializing in optical trap development, and Room B238 (517-884-5705) focused on fluorescence integration and biomolecular assays.

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Thomas Brunetمشاهده پروفایل

پژوهشگر

University of BordeauxFrance

Thomas Brunet is a researcher at the University of Bordeaux, specializing in physical acoustics and functional materials for acoustics. His work spans ultrasound physics, material characterization, and advanced modeling/simulation techniques. Key collaborations with research groups: APY (Physical Acoustics) , Functional Materials for Acoustics , and GCE (Civil and Environmental Engineering) . Focus areas: acoustic metamaterials , Anderson localization , contactless micromanipulation , and viscoelastic wave propagation . His publications (over 30 in the last decade) demonstrate expertise in ultrasonic imaging, nanophononics, and multiphysics problems involving mechanical, thermal, and fluid interactions. Collaborative projects include DuMAS (Sustainability of Materials) , IMC (Mechanical Engineering) , and MPI (Materials-Procedes-Interactions) initiatives. No formal awards or student advising details are publicly available in the provided data.

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Xiuyuan Chengمشاهده پروفایل

دانشیار

Duke UniversityUnited States

Xiuyuan Cheng is an Associate Professor of Mathematics at Duke University, affiliated with the Trinity College of Arts & Sciences. Her expertise lies in applied analysis, focusing on developing theoretical and computational techniques for high-dimensional data analysis, signal processing, and machine learning. She holds a Ph.D. from Princeton University (2013). Her research emphasizes graph-based methods, kernel techniques, and deep learning applications in manifold data analysis. Notable contributions include work on graph Laplacian convergence, optimal transport for single-cell data, and rotation-equivariant neural networks. She has received grants from the National Science Foundation, including a CAREER award (2023–2028) for learning graph diffusion from high-dimensional data. Recent publications explore topics such as bi-stochastic graph normalization, neural tangent kernels, and adversarial defense using basis transformations. Teaching includes advanced courses like Measure and Integration and High-Dimensional Data Analysis. She collaborates extensively in interdisciplinary projects, integrating mathematical theory with computational tools for real-world applications.

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Christopher Janjigianمشاهده پروفایل

استادیار

Purdue UniversityUnited States

Christopher Janjigian is an Assistant Professor in the Department of Mathematics at Purdue University, specializing in probability theory with a focus on random walks in random environments, KPZ universality class phenomena, and stochastic partial differential equations. He holds a Ph.D. from the University of Wisconsin-Madison (2016) and has held postdoctoral positions at Université Paris Diderot (2016–2017) and the University of Utah (2017–2020). His research explores the infinite volume structure of random walks in random potentials and connections to models like the Kardar-Parisi-Zhang equation. He organizes the Purdue University Probability Seminar and has taught advanced courses including Stochastic Processes, Probability Theory, and Stochastic Calculus. His work bridges theoretical probability with applications in mathematical physics, emphasizing geometric and dynamic properties of stochastic systems. Recent research focuses on geodesic structures in percolation models, Busemann functions, and ergodic properties of directed polymer models. His articles investigate topics like exit point bounds in last-passage percolation and synchronization in the KPZ equation, contributing to the understanding of universal behaviors in stochastic systems.

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Patrizia Saviمشاهده پروفایل

دانشیار

Polytechnic University of TurinItaly

Patrizia Savi is a Tenured Associate Professor at the Polytechnic University of Turin within the Department of Electronics and Telecommunications. She actively participates in the Power Electronics Innovation Center (PEIC) and serves as a Senior Member of IEEE and the International Union of Radio Science . Teaching: She has been the Titolare del corso for 'Campi Elettromagnetici' (Electromagnetic Fields) since 2019-2021 at the Polytechnic University of Turin. Key Collaborations: Works with researchers across Italy and international institutions on projects involving GNSS-R for environmental monitoring. Research Interests: Her work focuses on GNSS Reflectometry for soil moisture retrieval, carbon-based composites (graphene, biochar, nanotubes) for microwave applications, and graphene tunable devices including biosensors. She also explores electromagnetic shielding using sustainable materials. Recent Publication Trends: Recent work emphasizes machine learning integration with GNSS-R data, biochar composite shielding in construction materials, and graphene-based biosensors for glucose and HRP detection. Key applications span climate action , environmental monitoring , and medical diagnostics . Scientific Awards: IEEE Fellow (2016-) IEEE Senior Member (2016-) International Union of Radio Science Senior Member (2024-) Advising: Supervises PhD students Simone Gaetano Ballaera and Fabio Peinetti , focusing on graphene sensors and tunable devices.

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