جست‌وجوی استاد و پژوهشگر

Wiebke Diestelkampمشاهده پروفایل

استاد

• Design of Experiments
• Combinatorics
• Probability and Statistics
• +۵ مورد دیگر

Wiebke Diestelkamp is a Professor in the Department of Mathematics at the University of Dayton, within the College of Arts and Sciences. She has been a full-time faculty member since 1998 and served as department chair from 2016 to 2024, demonstrating long-standing academic leadership. Her research focuses on Design of Experiments and Combinatorics , with significant contributions to orthogonal arrays, factorial designs, and applications in biomedical and behavioral sciences. She has collaborated extensively with researchers in biomechanics, music therapy, and medical device evaluation, bridging theoretical mathematics with practical health outcomes. The trend in her publications shows a strong interdisciplinary focus, particularly from 2011 onward, where her statistical expertise is applied to problems in gait analysis, fall risk, dementia care, and cardiovascular research. Her earlier work is more theoretical, centered on combinatorial structures and algebraic properties of arrays and polynomials. Dr. Diestelkamp earned her Ph.D. in Mathematics with a specialization in probability and statistics from the University of Wisconsin-Milwaukee in 1998, following an M.S. from the same institution in 1992. She began her academic journey in Germany, attending Georg-August Universität Göttingen and Universität Ulm. She has not been mentioned as receiving any scientific awards in the provided text. While no students are listed, her collaborative research suggests active mentorship and involvement in interdisciplinary projects. There is no mention of external grants, but her sustained publication record implies research funding support. She has not led any named labs or research centers, but her work appears to be conducted through departmental and cross-disciplinary collaborations at the University of Dayton.

• Computational Complexity
• SAT Solvers
• MaxSAT Algorithms
• +۳ مورد دیگر

M. Luisa Bonet Carbonell is a researcher in the Department of Computer Science at the Universitat Politècnica de Catalunya (UPC), affiliated with the Barcelona School of Informatics (FIB). Her work focuses on computational complexity, SAT and MaxSAT solvers, proof systems, and algorithmic optimization. She has extensive collaborations within the LOGPROG and ALBCOM research groups, contributing to projects like TASSAT3 and MULOG-2. Her research spans theoretical computer science, with emphases on proof complexity, polynomial calculus, and the analysis of industrial SAT instances. Notable contributions include studies on Sherali-Adams and Nullstellensatz proof systems, as well as the fractal dimension of SAT formulas. Over 90 publications include articles in Artificial Intelligence , Journal of Computer and System Sciences , and conferences like SAT and IJCAI. Her work bridges theoretical foundations with practical applications, such as improving MaxSAT algorithms and analyzing community structures in problem instances.

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 .

• Algebra
• Commutative Algebra
• Coding Theory
• +۴ مورد دیگر

Emanuela De Negri is a Full Professor at the University of Genoa's Department of Mathematics (DIMA), serving on both the Academic Senate and Department Board. Her teaching responsibilities span undergraduate and graduate programs including Computer Science (Algebra), Mathematics (Linear Algebra and Analytic Geometry, Coding Theory), and Biomedical Engineering (Geometry). Her research centers on Commutative Algebra and Algebraic Geometry, with emphasis on structural properties of ideals and varieties. Key areas include initial ideals, radical ideals, semiregular sequences, and secant varieties, often exploring combinatorial and computational aspects with applications in coding theory and cryptography. Recent work reveals consistent focus on multigraded structures and characteristic-free methods. Publications from 2020-2022 demonstrate collaborative research patterns, particularly with Conca and Gorla, addressing foundational questions in ideal theory and tensor decompositions. The work shows strong interdisciplinary connections between abstract algebra and information theory, notably in encryption and error-correcting codes.

Tamara Gravaمشاهده پروفایل

دانشیار

• Integrable systems
• Nonlinear waves
• Random matrix theory
• +۵ مورد دیگر

Tamara Grava is an Associate Professor at the International School for Advanced Studies (SISSA) in Trieste, Italy, and a Professor at the University of Bristol, UK. Her research focuses on mathematical physics, particularly integrable systems, nonlinear waves, and random matrix theory. She maintains active collaborations between these two prestigious institutions, contributing significantly to both theoretical developments and interdisciplinary applications. Her educational background includes a PhD in Mathematical Physics from SISSA, completed on October 5, 1998, with a thesis titled "On the Cauchy problem for the Whitham equations" under the supervision of Boris Dubrovin. Professor Grava's research spans several interconnected areas in mathematical physics. She investigates integrable systems with random initial data, developing probabilistic Riemann-Hilbert methods to analyze soliton gases and their connections to statistical mechanics. Her work on dispersive nonlinear partial differential equations examines long-time and small-dispersion asymptotics, with particular attention to dispersive shock waves and rogue waves. She also makes significant contributions to random matrix theory, studying special functions, orthogonal polynomials, and their connections to Painlevé equations. Her research often bridges pure mathematics with applications in physics, revealing deep connections between seemingly disparate fields. Analysis of Professor Grava's recent publications (2021-2024) reveals a strong focus on the intersection of integrable systems, random matrix theory, and nonlinear wave phenomena. Her work increasingly explores soliton gases and their statistical properties, connecting microscopic soliton dynamics to macroscopic hydrodynamic descriptions. There's a clear progression toward more complex systems involving random initial conditions and the development of rigorous mathematical frameworks to handle these problems. Her research shows strong interdisciplinary connections between mathematical physics, statistical mechanics, and quantum field theory. Professor Grava actively supervises PhD students including Sacha Grover (Bristol), Dmitrii Rachenkov (SISSA), Xiao-Fan Zhang, Xiaodong Zhu, and Zechuan Zhang. Her editorial work includes service on the boards of Nonlinearity (since 2012), SIAM Journal of Mathematical Analysis (since 2022), Constructive Approximation (since 2023), and the Bulletin and Journal of the London Mathematical Society (starting 2025). She participates in numerous international conferences and workshops, with upcoming engagements in 2025 including events on enumerative combinatorics, integrable systems, and statistical physics at institutions including CIRM, Harvard University, and the MATRIX Institute.

François Pirotمشاهده پروفایل

دانشیار

• Graph Theory
• Combinatorics
• Probabilistic Method
• +۴ مورد دیگر

François Pirot is an Associate Professor (Maître de Conférences) at Université Paris-Saclay since September 1, 2021. He conducts research at the LISN laboratory within the GALaC team and teaches at the Faculty of Science of Orsay. PhD in Mathematics (Radboud University) and Computer Sciences (Université de Lorraine), 2019 Postdoctoral experience: ULB (2019), G-SCOP (2019-2020), Inria Sophia Antipolis (2020-2021) His research focuses on graph coloring problems in diverse contexts such as graph powers, locally sparse graphs, and distributed algorithms, utilizing probabilistic methods and connections to bio-informatics through circular codes. He has advanced bounds for h -conflict-free coloring, acyclic coloring, and dichromatic numbers in oriented graphs, with applications to minor-closed families and geometric group theory. Scientific contributions include: Asymptotically tight bounds for chromatic numbers in sparse graphs Efficient fractional coloring algorithms for K_t-minor-free graphs Structural analysis of comma-free and mixed circular codes in genetic alphabets Charles Delorme Prize for outstanding thesis in Graph Theory (2019) Collaborations span institutions like ULB, G-SCOP, Inria, and cross-disciplinary fields from computer science to mathematical biology.

Olga Holtzمشاهده پروفایل

استاد

• Numerical Analysis
• Matrix Theory
• Algebra and Combinatorics
• +۱ مورد دیگر

Olga Holtz is a Professor in the Department of Mathematics at the University of California-Berkeley, appointed in 2007. Her research spans applied mathematics, algebra, and computational complexity. Research Interests: Numerical analysis, matrix theory, algebra and combinatorics, computational complexity. Her recent publications focus on communication-efficient algorithms, matrix theory, and zonotopal algebra. Key trends include interdisciplinary work bridging theoretical mathematics with high-performance computing challenges. Contact: holtz@math.berkeley.edu . Personal website: http://www.cs.berkeley.edu/~oholtz/ .

• Theoretical Computer Science
• Algorithms
• Edge Estimation
• +۵ مورد دیگر

Holger Dell is a Lecturer in Theoretical Computer Science and Algorithms at the IT University of Copenhagen. His research focuses on computational complexity, graph theory, and algorithmic efficiency. Active in polynomial-time algorithms and oracle-based methods Contributions to edge estimation in hypergraphs and fairness in node embeddings Key collaborations with BARC (Basic Algorithms Research Copenhagen) project Research trends show expertise in causal modeling, finite field polynomial solving, and graph embedding techniques. Recent work emphasizes algorithmic fairness and abstract causal relationships. Participated in a major project funded by the Villum Foundation (2017-2024) as a collaborator.

• 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 .

• Algorithms
• Combinatorics
• Complexity Theory
• +۳ مورد دیگر

Sundar Vishwanathan is a Professor in the Department of Computer Science and Engineering at Indian Institute of Technology Bombay (IIT Bombay), where he has established himself as a leading researcher in theoretical computer science. His academic career spans over three decades with consistent contributions to algorithms, combinatorics, and complexity theory. His research interests form a cohesive body of work focused on theoretical foundations of computing: Algorithms (particularly approximation algorithms, online algorithms, and randomized algorithms) Combinatorics and extremal set theory Complexity theory and circuit lower bounds Graph theory and graph algorithms Combinatorial optimization problems Vishwanathan's publication record demonstrates remarkable consistency and depth, with publications spanning from 1990 to 2024. His recent work focuses on graph algorithms (particularly maximum matching problems), approximation algorithms for combinatorial optimization, and circuit complexity. He has developed innovative techniques using linear algebra, combinatorial methods, and probabilistic analysis to solve challenging theoretical problems. His approach often bridges theoretical insights with practical algorithmic considerations. His collaborative work spans multiple research groups, with frequent co-authorships with researchers such as Ashish Chiplunkar, Sumedh Tirodkar, and Sreyash Kenkre. His research has evolved from foundational work in online graph coloring in the 1990s to more specialized topics in combinatorics and recently to circuit lower bounds, showing both depth in core areas and adaptability to evolving research landscapes.

• Computational Engineering
• Model-Based Development
• Production Engineering
• +۳ مورد دیگر

Julia Kowalski serves as Professor and Chair of the Department of Methods of Model-Based Development in Computational Engineering at RWTH Aachen University's Faculty of Mechanical Engineering. She holds dual appointments on the Steering Committees for the university's Profile Areas in Production Engineering (ProdE) and Modeling & Simulation Sciences, operating from the Collective Building of Mechanical Engineering in Aachen, Germany. Her research integrates computational engineering with geohazard prediction and cryorobotics, developing advanced numerical methods for multiphysics problems including ice-penetration probes, landslide susceptibility mapping, and wind-energy systems. She pioneers machine learning applications that bridge physical models with engineering design while championing FAIR data principles across cryosphere and geohazard research domains. Current projects focus on model coupling techniques for environmental flows and space exploration technologies. Analysis of her 15 most recent publications reveals dominant trends in surrogate modeling for geotechnical stability, cryorobotic exploration systems, and FAIR data frameworks for environmental science. Her work consistently bridges machine learning with physical modeling across renewable energy, planetary science, and natural hazard mitigation through international collaborations like the TRIPLE project. Scientific awards are not documented in provided materials, though her leadership in DLR-funded space exploration initiatives and editorial roles in topical collections indicates significant recognition. As department chair, she oversees graduate advising and research direction within her computational engineering group, with active grant funding evidenced by German Space Agency collaborations and multi-institutional projects targeting geohazard prediction and cryosphere exploration. Her work demonstrates strong industry-academia-government partnerships. Kowalski leads the Methods of Model-Based Development research group, which operates as an integrated lab for numerical simulation, model coupling, and data-driven engineering solutions. Future work focuses on enhancing uncertainty quantification in geohazard models, advancing cryorobotic technologies for extraterrestrial environments, and developing robust frameworks for FAIR geoscientific data.

Dmitriy (Tim) Kuniskyمشاهده پروفایل

استادیار

• Probability
• Statistics
• Mathematical Data Science
• +۷ مورد دیگر

Dmitriy (Tim) Kunisky is an Assistant Professor in the Department of Applied Mathematics and Statistics at Johns Hopkins University's Whiting School of Engineering. He is also affiliated with the Data Science and AI Institute, the Department of Mathematics, and the Algorithms and Complexity Group at Johns Hopkins. Dr. Kunisky received his bachelor's degree in mathematics from Princeton University, worked as a software engineer for Google, earned his PhD in mathematics from the Courant Institute at NYU under the supervision of Afonso Bandeira and Gérard Ben Arous, and was a postdoctoral associate in computer science at Yale University before joining Johns Hopkins. His research broadly concerns how probability theory and mathematical statistics interact with computational complexity and the theory of algorithms. He investigates the mathematical phenomena that govern the power and limitations of algorithms processing massive and high-dimensional inputs, drawing on asymptotic statistics, convex geometry, random matrix theory, statistical physics, and representation theory. His work includes studying convex relaxation algorithms on combinatorial optimization problems, computational intractability in high-dimensional statistics, pseudorandomness, and experimental approaches to number theory and combinatorics. His recent publications demonstrate a consistent focus on the intersection of computational complexity, statistical inference, and random matrix theory. There's a clear trajectory from theoretical foundations to practical algorithmic applications, with particular emphasis on information-computation gaps, spectral methods, and the sum-of-squares hierarchy. His work often bridges theoretical computer science with statistical physics approaches. Dr. Kunisky actively advises graduate students at Johns Hopkins, including PhD candidates in Applied Mathematics and Statistics. He has taught courses on Random Matrix Theory in Data Science and Statistics, Probability Theory, Sum-of-Squares Optimization, and Modern Probability for Theoretical Computer Science, demonstrating his commitment to both research and education in mathematical data science.

Terence Chi-Shen Taoمشاهده پروفایل

استاد

• Harmonic analysis
• Partial differential equations
• Algebraic combinatorics
• +۵ مورد دیگر

Terence Tao is an Australian-American mathematician and professor of mathematics at the University of California, Los Angeles (UCLA), where he holds the James and Carol Collins Chair in the College of Letters and Sciences. Widely regarded as one of the greatest living mathematicians, Tao has received numerous prestigious awards including the Fields Medal, the Breakthrough Prize in Mathematics, and the MacArthur Fellowship. Dr. Tao's educational background includes: Bachelor's and Master's degrees from Flinders University (1991) Ph.D. from Princeton University (1996) under Elias M. Stein Tao's research spans an extraordinary breadth of mathematical fields. He is particularly known for his work in harmonic analysis, partial differential equations, combinatorics, and analytic number theory. His research has included groundbreaking contributions to compressed sensing, the Green-Tao theorem on arithmetic progressions in prime numbers, and progress on the Navier-Stokes equations. Tao is renowned for his collaborative approach, having worked with over 60 co-authors throughout his career. Tao's publications demonstrate remarkable diversity across mathematical disciplines. His work shows strong trends in connecting seemingly disparate areas of mathematics, often bringing techniques from one field to solve problems in another. He has made significant contributions to both theoretical and applied mathematics, with applications ranging from signal processing to number theory. Among his numerous scientific achievements, Tao has received: Fields Medal (2006) Breakthrough Prize in Mathematics (2014) Royal Medal (2014) MacArthur Fellowship (2006) Crafoord Prize (2012) Princess of Asturias Award (2020) Tao has mentored numerous students throughout his career, with Monica Vișan among his doctoral students. He has secured significant research funding through prestigious awards including the Packard Fellowship, Sloan Fellowship, and Simons Investigator award. His collaborative research has been supported by multiple National Science Foundation grants. Tao maintains an active research group at UCLA and frequently collaborates with mathematicians worldwide. His blog and public lectures have made advanced mathematical concepts accessible to broader audiences, demonstrating his commitment to mathematical education and outreach.

Viresh Patelمشاهده پروفایل

مدرس

• Extremal combinatorics
• Probabilistic combinatorics
• Graph polynomials / partition functions
• +۵ مورد دیگر

Dr. Viresh Patel is a Lecturer in Optimisation at the School of Mathematical Sciences, Queen Mary University of London. His research focuses on extremal and probabilistic combinatorics, graph polynomials, phase transitions, and approximation algorithms. University: Queen Mary University of London School: School of Mathematical Sciences Email: viresh.patel@qmul.ac.uk Research Interests: Patel’s work bridges combinatorics, graph theory, and statistical physics. Key areas include Hamiltonian cycles in dense graphs, algorithmic approaches to graph polynomials, and complexity analysis of physical models. Publication Trends: Recent articles address structural graph theory (cycle/path decomposition), computational complexity (Potts/Ising models), and approximation algorithms using probabilistic and Taylor series methods. Collaborations: Regular co-authorship with researchers like Guus Regts, Allan Lo, and Matthew Jenssen indicates strong interdisciplinary engagement.

Jinho Baikمشاهده پروفایل

استاد

• Analysis
• Probability Theory
• Mathematical Physics
• +۷ مورد دیگر

Jinho Baik is a Professor of Mathematics at the University of Michigan, where he has been affiliated since 2002. His research spans analysis, probability theory, mathematical physics, and applied mathematics, with specific focus areas including random matrix theory, integrable systems, random permutations, and random growth models. He holds a Ph.D. from the Courant Institute of Mathematical Sciences (1999) and previously served as a Veblen Instructor/Assistant Professor at Princeton University (1999–2003). Education: B.S., KAIST, Korea (1995) Ph.D., Courant Institute of Mathematical Sciences, NYU (1999) Research Interests: Baik applies analytic tools to study probabilistic models, including eigenvalues of large random matrices, randomly growing interfaces, vicious random walkers, and longest increasing subsequences of random permutations. His work intersects with complex analysis, asymptotic analysis, functional analysis, potential theory, and combinatorics. Scientific Awards: Sloan Doctoral Dissertation Fellowship Kurt O. Friedrichs Prize for an Outstanding Dissertation in Mathematics (NYU) AMS Centennial Research Fellowship Sloan Research Fellowship CMFT 2005 Award for an Outstanding Young Researcher 2016 Simons Fellowship Professional Roles: Baik has served as Director of Graduate Admissions in the Department of Mathematics. He is an Associate Editor for unspecified journals and has presented at major international conferences, including the 2022 International Congress of Mathematicians (Probability section).