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Madhu SudanView profile

Professor

• Theories of Computation and Communication
• Coding Theory
• Property Testing
• +5 more

Madhu Sudan is the Gordon McKay Professor of Computer Science at Harvard University's John A. Paulson School of Engineering and Applied Sciences (SEAS), where he also serves as Director of Graduate Studies. He holds a B.Tech. from IIT Delhi (1987) and a Ph.D. from UC Berkeley (1992). Prior to Harvard, he was at MIT (1997–2015), IBM Research (1992–1997), and Microsoft Research (2009–2015). His research focuses on the theories of computation and communication, with notable contributions to probabilistically checkable proofs (PCP theorem), list-decoding algorithms for error-correcting codes, and sublinear-time algorithms. Education: B.Tech., Indian Institute of Technology Delhi, 1987 Ph.D., University of California, Berkeley, 1992 Research Interests: Communication and computing under errors Coding theory and its applications Property testing and sublinear algorithms Algebraic methods in computation Awards and Honors: Nevanlinna Prize (2002) IEEE Hamming Medal (2016) Member, National Academy of Sciences (2017) Infosys Prize in Mathematical Sciences (2018) Fellow of ACM, IEEE, and AMS Teaching and Service: Current courses: Algebra and Computation , Coding Theory Directed Graduate Studies in Computer Science at Harvard Editorial roles: Foundations and Trends in Theoretical Computer Science , Theory of Computing Research Groups: Member of Harvard's Theory of Computation group, collaborating on projects in coding theory, complexity theory, and distributed computing.

Stefan SteinerbergerView profile

Professor

• Analysis
• Applied Mathematics
• Combinatorics
• +5 more

Stefan Steinerberger is a Professor in the Department of Mathematics at the University of Washington, Seattle. He holds a PhD from the University of Bonn (2013) and specializes in Analysis, with research interests spanning Partial Differential Equations, Spectral Theory, Harmonic Analysis, and applications to Data Science and Mathematical Physics. His work often bridges theoretical and applied mathematics, addressing problems in geometry, combinatorics, and numerical methods. Education: PhD in Mathematics, University of Bonn, 2013 Research Interests: Steinerberger’s research focuses on Analysis, with emphasis on PDEs, Spectral Theory, and Harmonic Analysis. He explores interdisciplinary connections, such as applying analytic techniques to graph theory, optimization, and data science. Specific themes include eigenvalue estimates, dynamical systems, and the interplay between geometry and combinatorial structures. Awards & Recognition: While specific awards are not listed, his extensive publication record and affiliations with prestigious journals indicate significant contributions to the field. His work frequently appears in top-tier journals like Advances in Mathematics , Journal of Functional Analysis , and SIAM Journal on Discrete Mathematics . Teaching & Outreach: He teaches courses in the Department of Mathematics and is involved in outreach initiatives such as the Washington Experimental Mathematics Lab (WXML) and the UW Math Circle. His courses and research often emphasize problem-solving and real-world applications. Labs/Teams: Active in collaborations across mathematical disciplines, including work with researchers in combinatorics, probability, and numerical analysis. He maintains a personal website with resources on his research, teaching, and open problems.

William Yun ChenView profile

Assistant Professor

• Algebra
• Algebraic Geometry
• Number Theory
• +6 more

William Yun Chen is an Assistant Professor in the Department of Mathematics at the University of Illinois at Urbana-Champaign (UIUC). He holds additional campus affiliations within the College of Liberal Arts & Sciences. Prior to UIUC, he was an NSF Postdoctoral Fellow at Columbia University and McGill University, and a Member at the Institute for Advanced Study (IAS). He earned his PhD in 2016 from Penn State under Winnie Li's supervision, specializing in arithmetic geometry. His research focuses on the interplay between group theory, algebraic geometry, and number theory, particularly through monodromy actions of étale fundamental groups. His work includes moduli interpretations of noncongruence modular curves, integrality properties of noncongruence modular forms, and studies of tamely ramified covers of the projective line. Recent contributions address Nielsen equivalence classes of finite groups and Bourgain-Gamburd-Sarnak conjectures on Markoff triples. He also explores arithmetic monodromy actions and exceptional sequences in braid groups. Chen’s publications appear in prestigious journals like Annals of Mathematics, Algebra and Number Theory, and Mathematische Annalen. He actively supervises research seminars, including a 2024 reading seminar on Katz-Mazur’s Arithmetic moduli of elliptic curves . His teaching spans courses like Applied Linear Algebra, Number Theory, and Calculus at UIUC, Rutgers, Columbia, and Penn State. Chen maintains a code repository for computing moduli stacks of elliptic curves with nonabelian level structures, generating data on finite groups and their geometric properties. His photography, showcased on his personal site, complements his academic pursuits.

LianTao WangView profile

Professor

• Theoretical Particle Physics
• Higgs Physics
• Dark Matter
• +1 more

LianTao Wang is Professor in the Department of Physics, Enrico Fermi Institute, and Kavli Institute for Cosmological Physics at the University of Chicago. His theoretical research focuses on particle physics phenomenology beyond the Standard Model. Professor Wang investigates fundamental puzzles including electroweak symmetry breaking, dark matter identity, and cosmological asymmetries. His work connects theoretical frameworks with experimental searches at facilities like the Large Hadron Collider. Current studies examine Higgs boson properties, axion dark matter detection strategies, and primordial gravitational wave signatures from the early universe.

• Quantum Computing
• Topological Quantum Computation
• Tensor Networks
• +3 more

Andreas Bauer is a Research Fellow at the Department of Mechanical Engineering , Massachusetts Institute of Technology , focusing on quantum computing and topological phases of matter. His work bridges theoretical physics and computational methods, with an emphasis on fault-tolerant systems and tensor networks. Research Focus: Topological quantum computation, quantum error correction, tensor networks, and condensed matter physics. Email: andib@mit.edu

Alexander BargView profile

Professor

• Coding Theory
• Cryptography
• Combinatorics
• +5 more

Dr. Alexander Barg is a Professor of Electrical and Computer Engineering (ECE) at the University of Maryland, College Park, with affiliate appointments in Computer Science, Mathematics, and the Institute for Systems Research. He holds a Ph.D. from the Russian Academy of Sciences (1987). His research focuses on coding theory, quantum codes, information theory, and distributed storage systems. He has advised numerous graduate students and postdocs, contributing to advancements in error-correcting codes and quantum computing. His work spans theoretical foundations and applications, including smoothing of codes, quantum code design, and recoverable storage systems. He has authored over 200 publications and serves on editorial boards of leading journals like IEEE Transactions on Information Theory and Foundations and Trends® in Communications and Information Theory . He teaches graduate and undergraduate courses on information theory, coding, and probability. Research highlights include contributions to classical and quantum coding bounds, LDPC codes, and polar codes. His grants and awards reflect sustained NSF support for projects on discrepancy theory, energy optimization, and distributed storage.

Jiahui ChenView profile

Assistant Professor

• Topological Data Analysis
• Machine Learning
• Computational Biophysics
• +4 more

Jiahui Chen is an Assistant Professor in the Department of Mathematical Sciences at the University of Arkansas, Fayetteville. He holds a PhD in Computational and Applied Mathematics from Southern Methodist University (2019). Prior to his current position, he was a Visiting Assistant Professor at Michigan State University under Prof. Guo-Wei Wei's group. His research focuses on topological and geometrical data analysis, machine learning algorithms, and their applications in biomolecular modeling. Key areas include protein-protein interaction analysis, mutation impact prediction, and fast numerical methods like the Poisson-Boltzmann equation, Treecode, and Fast Multipole Method. He has contributed to studies on SARS-CoV-2 variants, vaccine-breakthrough mutations, and antibody resistance using topological methods and deep learning. His work combines numerical algorithms with parallel computing, emphasizing GPU acceleration and algorithm optimization. Chen has collaborated on projects involving persistent homology, Hodge Laplacians, and algebraic topology for biomolecular analysis. He maintains an active GitHub profile with repositories like persistent_homology_visualizer and TABI_solver , showcasing his computational tools.

• Commutative Algebra
• Algebraic Number Theory

Jared Kettinger is a Lecturer in the Department of Mathematical and Statistical Sciences within the College of Science at Clemson University, serving as Graduate Teacher of Record and Graduate Student Seminar Coordinator. He teaches undergraduate courses including Business Calculus and Calculus of One Variable sequences. His educational background includes: B.S. in Mathematics from Grove City College (2021) B.A. in Economics from Grove City College (2021) M.S. in Mathematical Sciences from Clemson University (2024) His research centers on Commutative Algebra—studying ring structures, ideals, and modules fundamental to algebraic geometry—and Algebraic Number Theory, which explores number fields with applications in cryptography and coding theory. These fields represent core algebraic disciplines requiring advanced abstract reasoning. No scientific awards were documented in the available information. Mr. Kettinger has not advised any graduate students per the provided records, and no research grants are referenced. His current responsibilities appear focused on teaching coordination and course instruction within the department's undergraduate programs. There are no mentions of laboratory affiliations, research teams, or collaborative projects in the source material.

• Coding Theory
• Post-Quantum Cryptography
• Quantum Error Correction
• +2 more

Felice Manganiello is an Associate Professor and Associate Director for Mathematics and Statistics Education in Clemson University's College of Science, Department of Mathematical and Statistical Sciences. His research specializes in coding theory with applications to quantum computing, cryptography, and secure communications. His work bridges theoretical mathematics and practical implementations in information security and distributed systems. Research interests include the development of quantum-resistant cryptographic systems, error-correcting codes for quantum computing, and secure multiparty computation protocols. Recent publications focus on constructing specialized codes for quantum fault tolerance, developing zero-knowledge proof systems, creating efficient batch coding schemes for distributed storage, and designing secure computation methods for matrix operations. His work demonstrates consistent innovation in applying algebraic structures to solve contemporary challenges in information security and network communications.

Beth A NovickView profile

Lecturer

• Combinatorial Optimization
• Discrete Mathematics
• Graph Theory
• +7 more

Beth A Novick is a Principal Lecturer in the Department of Mathematical and Statistical Sciences at Clemson University, part of the College of Science. She holds a Ph.D. in Operations Research from Carnegie Mellon University (1990) and completed a postdoctoral fellowship at the University of Waterloo's Department of Combinatorics and Optimization (1990–91). Her primary research focuses on combinatorial optimization, discrete mathematics, graph theory, and related areas including median graphs, metric dimension, and reconfiguration graphs. She has been affiliated with Clemson University since 1992. Her research interests encompass integer programming, algebraic graph theory, matroids, and closure systems. Notable contributions include studies on reconfiguration graphs of shortest paths and geometric interpretations of threshold dimensions. She is a member of the American Mathematical Society and Women in Combinatorics. Teaching responsibilities include courses such as Linear Algebra and Graph Theory. No scientific awards or grants are explicitly listed in the provided information. Her work spans theoretical advancements in discrete mathematics and applications in graph-based optimization problems.

• Arithmetic Groups
• Geometric Group Theory
• p-adic Lie Groups
• +2 more

Benjamin Klopsch is Professor of Mathematics and Head of the Algebra and Number Theory group at Heinrich-Heine-Universität Düsseldorf. His research explores asymptotic and geometric group theory with applications to number theory. Research Areas: Algebraic properties of arithmetic groups, zeta functions of algebraic structures, combinatorial problems in coding theory, and representation growth of p-adic Lie groups. Leadership: Organizes the Advanced Seminar on Group Theory and co-directs the DFG-GRK 2240 graduate school. Serves as editor for Archiv der Mathematik and Journal of Group Theory. Teaching: Offers courses on representations of finite groups, local fields, and geometric group theory for undergraduate and graduate students.

• Applied Topology
• Sheaf Theory
• Category Theory
• +5 more

Justin M. Curry is a tenured Associate Professor in the Department of Mathematics and Statistics at the University at Albany SUNY. His research focuses on developing theoretical foundations for Topological Data Analysis (TDA) using sheaf theory and category theory. He completed his PhD at the University of Pennsylvania under Robert Ghrist and held a postdoc at Duke University. Recent activities include sabbaticals at the University of Oxford, VU Amsterdam, and the Max Planck Institute for Mathematics in the Sciences (MPI MiS). Education: PhD in Mathematics from University of Pennsylvania (2014) Visiting Associate at the Institute for Advanced Study (2009-2011) Research interests span applied topology with emphasis on algebraic and geometric models for space communications, topological deep learning, and inverse problems in TDA. Notable collaborations include NASA's TIMAEUS project (2020-2025) and contributions to the IEEE Aerospace Conference. His work bridges pure mathematics and engineering applications, particularly in distributed space networks and topological signal processing. Recent publications (2021–2024) explore decorated Reeb spaces, universal ℓ^p-metrics on merge trees, and topological attributed graphs for shape discrimination. He has delivered invited lectures at venues like the International Conference on Machine Learning (ICML) and the Max Planck Institute. Awards: NSF CRII Award (2020), NSF Grant for Enriched Topological Summaries (2019) Advising 5 PhD students and leading the NASA-funded TIMAEUS initiative ($650k), his lab integrates categorical methods with geometric deep learning frameworks. Current work includes algebraic models for space communication protocols and sheaf-theoretic approaches to shape space construction. Labs/Teams: Active member of the ATiA (Applied Topology and Inverse Problems) research group and collaborator with NASA's DTN (Disruption Tolerant Networking) working group.

• Nonlinear Partial Differential Equations
• Numerical Analysis
• Applied Computational Mathematics
• +3 more

Tori Fisher is a doctoral student and Graduate Research Assistant in the School of Mathematical and Statistical Sciences at Clemson University. She holds a B.S. in Mathematical Sciences from Clemson (2023) and focuses on applied and computational mathematics with emphases on nonlinear PDE analysis, numerical methods, and coding theory. Education: B.S., Mathematical Sciences, Clemson University, 2023 Her research interests include nonlinear partial differential equations , nonlinear solvers , Anderson Acceleration , and CSS-T code construction from Reed Muller codes . She has presented work at NCUWM 2023 and the AMS Southeast Sectional 2023 conferences. Notable achievements include the Samuel M. Martin Outstanding Senior Award (2023) and the Michael Case Award for promising PhD research (2024). She is expected to graduate in May 2028.

Dan A. SimoviciView profile

Professor

• Data Mining
• Machine Learning
• Information Theory
• +5 more

Dan A. Simovici is a Professor of Computer Science at the University of Massachusetts Boston, where he has served since 1985 and currently directs the Computer Science Graduate Program. He also holds an Honorary Professorship at the University of Iasi (Romania) and has held visiting positions at the University of Science and Technology Lille and Tohoku University. A Senior Member of IEEE and active in ACM and AAAI, his research integrates information theory, data mining, formal logic, and algebra. Education Ph.D. in Mathematics, University of Bucharest (1974) M.S. in Mathematics, University of Iasi (1970) M.S. in Electrical Engineering, Polytechnical Institute of Iasi (1965) Research Interests Dr. Simovici’s work centers on information-theoretic and linear-algebraic techniques in data mining , semantic database models, and the algebraic foundations of multiple-valued logic. His recent focus includes clustering validation via entropy measures, ultrametric structures in dissimilarity spaces, and the mathematical underpinnings of machine-learning algorithms. These themes are unified by a rigorous mathematical approach that bridges theory and practical data-analysis challenges. Books & Recent Publications Over the past decade, he has authored or co-authored major reference texts including Clustering – Theoretical and Practical Aspects (2021), Mathematical Analysis for Machine Learning and Data Mining (2018), and the 1004-page Linear Algebra Tools for Data Mining (2nd ed., 2023). His 2024 volumes Logical Foundations of Computer Science (2 vols.) and Introduction to the Theory of Formal Languages consolidate decades of scholarship. Scientific Awards & Honors Best Paper Award, AFIA (2000) Senior Member, IEEE Vice Chair, IEEE Computer Society Technical Committee for Multiple-Valued Logic Managing Editor, Journal of Multiple-Valued Logic and Soft Computing Editorial roles: International Journal of Parallel, Emergent and Distributed Systems and International Journal of Software and Information Technologies PhD Advising & Graduate Program Leadership Since 1984, Dr. Simovici has directed the Computer Science Graduate Program at UMass Boston, mentoring 12 PhD graduates (2002–2021) whose work spans data-mining algorithms, clustering, and machine-learning theory. He regularly organizes and chairs premier conferences such as ISMVL (International Symposium on Multiple-Valued Logic) and serves on program committees for KDD, PKDD, and DAWAK. Laboratories & Teams While no specific laboratory name is provided, Dr. Simovici’s graduate program leadership and extensive editorial and conference responsibilities effectively coordinate a distributed research group focused on theoretical computer science and data mining, collaborating with institutions in the U.S., Europe, and Asia.

Catalin ZaraView profile

Professor

• Differential Geometry
• Equivariant Cohomology
• K-Theory
• +3 more

Catalin Zara is a Professor in the Department of Mathematics at the University of Massachusetts Boston (UMass Boston), serving as Interim Associate Dean of the College of Science and Mathematics (CSM). He holds a Ph.D. in Mathematics from the Massachusetts Institute of Technology (MIT). His research focuses on differential geometry, equivariant cohomology and K-theory, combinatorial structures, and applications of distance metrics in finite spaces. He has published extensively in top-tier journals such as Advances in Mathematics and Journal of Combinatorics . Dr. Zara's work bridges pure and applied mathematics, with notable contributions to GKM theory, polynomial assignments, and combinatorial optimization. His recent projects include studies on balance weighing problems, windfarm geometry impacts, and Thue-Morse sequences. Teaching evaluations highlight his engaging style, challenging yet supportive approach, and ability to foster deep conceptual understanding across courses like Calculus, Linear Algebra, and advanced topics in combinatorics. He maintains an active research program with interdisciplinary applications, including collaborations in environmental science (bird mortality modeling) and computer science (medoid-based clustering). His office is located in Wheatley Hall and he is regularly involved in academic service roles such as department leadership and curriculum development.