جستجوی استاد راهنمای دانشگاهی

• Probability Theory
• Discrete Probability
• Markov Chains
• +۶ مورد دیگر

Daniel Jerison is an Assistant Professor in the Department of Mathematics and Statistics at the University of San Francisco, where he supports undergraduate programs in mathematics and data science. He holds a PhD in Mathematics from Stanford University (2016) and a BA in Mathematics from Harvard University (2007). His educational background includes: PhD in Mathematics, Stanford University, 2016 BA in Mathematics, Harvard University, 2007 Professor Jerison specializes in discrete probability theory, with research focusing on circle packing and discrete complex analysis, abelian sandpile and rotor-router models, and Markov chain convergence and mixing times. His work bridges theoretical mathematics with applications in statistical physics and computer science. His research demonstrates a consistent trajectory toward understanding the properties of random objects and stochastic processes, particularly in discrete settings where traditional continuous methods face challenges. His scholarly contributions include publications in prestigious journals such as Advances in Mathematics, Communications in Mathematical Physics, and Transactions of the American Mathematical Society, reflecting his significant contributions to the field of probability theory. Professor Jerison has been actively involved in teaching a wide range of mathematics courses including probability theory, stochastic processes, complex analysis, and linear algebra. He has also contributed to mathematics education through involvement with PROMYS and SUMaC, summer programs for high school students, where he directed research labs and served on admission committees. His academic journey includes postdoctoral positions at Cornell University working with Lionel Levine and at Tel Aviv University under Asaf Nachmias, establishing him within a strong network of researchers in probability theory and discrete mathematics.

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 .

• Theoretical Computer Science
• Algorithms
• Computational Complexity
• +۴ مورد دیگر

Nutan Limaye is a Professor at the Department of Theoretical Computer Science , IT University of Copenhagen , specializing in Algorithms , Computational Complexity , and Algebraic Circuits . She actively contributes to research on polynomial complexity, quantum computation, and lower bound techniques. Key Research Areas : Algebraic Circuit Complexity, Polynomial Computation, Graph Isomorphism, Boolean Satisfiability Current Projects : FLows : Formula complexity and lower bounds (2024-2026) DIREC: OnlineAlgo : Digital research initiatives (2022-2025) BARC2 : Basic Algorithms Research Copenhagen (2024-2029) Scientific Recognition includes the FOCS Best Paper Award (2022) . Her work frequently appears in top conferences like CCC , FSTTCS , and SIGACT News , with recent collaborations in Denmark and international institutions. She contributes to public understanding through media appearances on topics like basic computer science research and BARC's initiatives .

• programming and building microprocessor devices
• application programming (Delphi, C++)
• Web programming (.NET, C#, MVC, AJAX)
• +۲ مورد دیگر

Sergey Oleksandrovych Sgadov is a Senior Lecturer in the Department of Computer Systems and Networks at Zaporizhzhia Polytechnic National University. With academic activity at the university since 1998, he has established himself as a dedicated educator and researcher in computer science and microprocessor technologies. His institutional affiliation places him within the Faculty of Computer Sciences and Technologies, where he contributes to both teaching and research initiatives. Education: Graduated from Zaporizhia National University in 1993 with honors, specializing in "Solid-state electronics and microelectronics" and receiving the qualification of "specialist". Dr. Sgadov's research spans multiple domains of computer science and engineering. His primary interests include microprocessor programming, application development using Delphi and C++, web programming with .NET technologies, and computer modeling of physical processes. He has made significant contributions to graph theory, particularly in topological graph drawing algorithms and their applications in printed circuit board design. His work bridges theoretical computer science with practical engineering applications, focusing on creating efficient algorithms for complex computational problems. Analysis of his publication record reveals a strong focus on graph theory applications in electronic design automation, microprocessor systems development, and educational tools for computer engineering. His research has evolved from fundamental theoretical work on graph algorithms to practical implementations in microcontroller programming and educational technology. The consistent thread throughout his work is the application of computational methods to solve complex engineering problems, particularly in circuit design and microprocessor systems. Dr. Sgadov teaches courses in microcontroller programming and programming of microcontroller systems, bringing his research expertise directly into the classroom. His teaching methodology likely incorporates practical, hands-on experience with modern microprocessor technologies, reflecting his research interests in ARM Cortex processors and microcontroller applications.

Ariane Carranceمشاهده پروفایل

پژوهشگر

• Combinatorics
• Probability Theory
• Discrete Metric Spaces
• +۵ مورد دیگر

Ariane Carrance is a postdoctoral researcher at the Department of Mathematics, Faculty of Mathematics, University of Vienna, where she works with Professor Nathanaël Berestycki. Her research program bridges combinatorics, probability theory, and theoretical physics with applications to quantum gravity. PhD in Mathematics, Institut Camille Jordan, supervised by Grégory Miermont and Fabien Vignes-Tourneret Postdoctoral position at Laboratoire de Mathématiques d'Orsay with Nicolas Curien and Jean-François Le Gall Hadamard lecturer at Centre de Mathématiques Appliquées de l'École polytechnique Dr. Carrance specializes in the combinatorial and probabilistic aspects of discrete metric spaces. Her work in dimension 2 focuses on specific families of maps, while in higher dimensions she investigates "colored trisps" and associated tensor models. She has made significant contributions to the understanding of random discrete structures and their continuum limits, with implications for quantum gravity theories. Her research combines deep theoretical insights with computational approaches, including development of mathematical software. Dr. Carrance's publication record demonstrates a consistent progression from foundational work on planar maps and triangulations toward more complex higher-dimensional structures. Her recent work shows increasing sophistication in handling the interplay between combinatorial structures and probabilistic phenomena, with particular attention to asymptotic behaviors and scaling limits. The mathematical tools she employs span from classical combinatorics to advanced probability theory and computational mathematics. Dr. Carrance has collaborated with leading researchers in probability theory including Nicolas Curien, Jean-François Le Gall, and Nathanaël Berestycki. She co-developed the SageMath package dynpuiseux for Puiseux series expansions, demonstrating her commitment to computational approaches in pure mathematics. Her research is supported through postdoctoral fellowships and academic positions at prestigious institutions across Europe. As a member of the probability research group at the University of Vienna, Dr. Carrance contributes to a vibrant mathematical community focused on stochastic processes, random geometry, and their applications. Her work connects with broader efforts to understand the mathematical foundations of quantum gravity through discrete approaches.