Emily Gunawan is an Assistant Professor in the Department of Mathematics and Statistics at the University of Massachusetts Lowell (UMass Lowell). She is affiliated with the Kennedy College of Sciences and holds an office in Southwick Hall's 3rd floor. Her research focuses on algebraic combinatorics, quiver representations, and cluster algebras. Dr. Gunawan earned her Ph.D. in Mathematics from the University of Minnesota. Her academic profile emphasizes contributions to combinatorial algebra and related fields. While no specific publications, grants, or awards are listed in the provided text, her work likely aligns with contemporary trends in discrete mathematics and structural algebra. For further details, her official university website provides additional information.
Joris Roos is an Assistant Professor at the University of Massachusetts Lowell within the Department of Mathematics and Statistics, part of the Kennedy College of Sciences. He holds a Ph.D. in Mathematics from the University of Bonn (2017). His research focuses on Fourier analysis, real analysis, and computer-assisted proofs, with particular emphasis on harmonic analysis applications in combinatorics, number theory, PDEs, and fractal geometry. He has been supported by grants including the NSF DMS-2154835 (2022-2025) and a Simons Foundation Grant (2021-2022). Roos has also participated in fellowships at the Hausdorff Research Institute for Mathematics and Oberwolfach. His work bridges pure analysis with computational methods, addressing problems in multilinear inequalities, maximal functions, and sparse domination techniques. Education: Ph.D. in Mathematics, University of Bonn, 2017 Research Interests: Fourier and harmonic analysis on Euclidean spaces Oscillatory integrals, maximal functions, singular integrals Discrete analogues in harmonic analysis Applications to combinatorics, number theory, dispersive PDEs Formalization of mathematics using interval arithmetic Grants & Fellowships: National Science Foundation Grant DMS-2154835 (2022-2025) Simons Foundation Grant ID 855692 (2021-2022) American Institute of Mathematics SQuaRE projects (2021-2025) Hausdorff Research Institute for Mathematics Fellowships (2021, 2022, 2024) Oberwolfach Research Fellowship (2023) Current Activity: Leading the 2024 HIM Trimester Program on Boolean Analysis in Computer Science and co-organizing the MLHA 2024 Spring School on multilinear singular integrals.
Bhargav Narayanan is an Associate Professor in the Department of Mathematics at Rutgers University. His research focuses on combinatorics, probability theory, statistical physics, and theoretical computer science, with a specialization in combinatorial models and probabilistic methods. He organizes a weekly seminar at Rutgers exploring these topics. Previously, he held a research fellowship at St John's College, Cambridge, and completed his PhD under Béla Bollobás at Cambridge University. Education: PhD in Mathematics from the University of Cambridge. Career: Postdoctoral research at St John's College, Cambridge before joining Rutgers. Research Interests: Combinatorics, probability theory, statistical physics, and theoretical computer science. He has published extensively in top-tier journals such as the Annals of Mathematics and the Journal of the European Mathematical Society. Selected publications highlight contributions to antichain codes, random graph bisections, threshold phenomena, and combinatorial optimization. His work often bridges discrete mathematics and applications in physics and computer science. He has taught graduate courses on additive combinatorics, spectral methods, and probabilistic methods in combinatorics. No scientific awards explicitly listed in the provided texts. Advising: No students listed explicitly in the text. Grants: No specific grants mentioned. Lab/Team: Organizes a weekly research seminar at Rutgers.
Karl Mahlburg was an Associate Professor in the Department of Mathematics at Louisiana State University from 2011 to 2021. He holds a Ph.D. in Mathematics from the University of Wisconsin-Madison, an M.S. in Mathematics, and a B.S. in Mathematics from Harvey Mudd College. His research focuses on automorphic forms, partition theory, combinatorial number theory, and nonstandard analysis. Research interests include: Theory of automorphic forms including modular forms and harmonic Maass forms Applications to partition theory and basic hypergeometric series Algebraic and finite combinatorics including graph theory Combinatorial probability and nonstandard analysis Dr. Mahlburg has received several prestigious awards including the Humboldt Foundation Fellowship, LSU Faculty Excellence Award, and PNAS Paper of the Year Award for his groundbreaking work on partition congruences. His research has been supported by NSF grants and Louisiana Board of Regents funding. He has advised numerous graduate and undergraduate students in mathematics research, with doctoral students pursuing careers in academia and industry. Dr. Mahlburg organized LSU's Problem-Solving Seminar for undergraduate mathematics competitions and served on multiple departmental committees.
Hamed Hatami is an Associate Professor in the School of Computer Science at McGill University, with cross-appointment in Mathematics. His research lies at the intersection of theoretical computer science and mathematics, focusing on analytic methods in complexity theory, learning theory, analysis of Boolean functions, and additive combinatorics. Hatami received the IEEE Computer Society Technical Achievement Award in 2012 for his contributions. He has published extensively on graph theory, property testing, communication complexity, and combinatorial limits. Hatami teaches advanced courses in algorithm design, complexity theory, and analysis of Boolean functions, and mentors graduate students through research collaborations. Prior to McGill, he held positions at the Institute for Advanced Study and Princeton University.
Jimmy He is an Assistant Professor in the Department of Mathematics at The Ohio State University (OSU). His research is supported by an NSF award (DMS-2451487). Prior to OSU, he was a CLE Moore Instructor at MIT, earned his PhD in Mathematics from Stanford University under Persi Diaconis, and studied Pure Mathematics and Statistics at the University of Waterloo. Education: PhD in Mathematics, Stanford University, 2021 Studies in Pure Mathematics and Statistics, University of Waterloo His research focuses on probability and combinatorics, with an emphasis on integrable probability, Markov chain mixing, symmetric functions, and discrete probability. He explores algebraic methods in these areas, particularly in the context of stochastic processes and combinatorial structures. Scientific Awards: NSF Award DMS-2451487 Advising and Grants: His research is supported by the NSF grant mentioned above. No specific advising roles or additional grants are detailed here. No specific labs or collaborative teams are listed in the provided information.
Yifan Jing is an Assistant Professor in the Department of Mathematics at The Ohio State University (OSU). He previously held postdoctoral positions at the University of Oxford’s Mathematical Institute and Wolfson College, mentored by Ben Green. His academic journey includes a PhD from the University of Illinois Urbana-Champaign (2021), supervised by József Balogh and Xiaochun Li, an M.Sc. from Simon Fraser University (2018) under Bojan Mohar, and a B.Sc. from the University of Science and Technology of China (2016), advised by Jack Koolen. His research focuses on Arithmetic Combinatorics, Analytic and Combinatorial Group Theory, Lie groups, Abstract Harmonic Analysis, Representation Theory, Additive Number Theory, Model Theory applications, Discrete Probability, and Theoretical Computer Science. Notable contributions include work on measure growth in Lie groups, inverse theorems for geometric inequalities, and structural graph theory. He received the 2023 Kirkman Medal for his research contributions. He currently organizes OSU’s Combinatorics Seminar and teaches Math 4507: Geometry. His advising includes PhD students Yewen Sun, Chavdar Lalov, and Yuchen Meng, alongside mentoring multiple undergraduate researchers at Oxford. Collaborators include leading mathematicians such as Chieu-Minh Tran, Ruixiang Zhang, and Bojan Mohar. His work bridges analysis, algebra, and logic to address problems across combinatorics, number theory, and geometry.
Anurag Sahay is a Golomb Visiting Assistant Professor of Mathematics at Purdue University, affiliated with the Department of Mathematics within the College of Science. His contact information includes the phone number 765-494-0481 and office MATH 402. He holds the academic rank of Visiting Assistant Professor and is not part-time. His research interests span a broad range of mathematical disciplines, with a focus on analytic number theory, mathematical analysis, and combinatorics. Sahay explores topics such as zeta functions (Riemann and Hurwitz), function fields, quadratic residues, hypergraph Turán problems, and geometric configurations. His work combines theoretical insights with computational methods, addressing questions related to moments of zeta functions, paucity problems in number theory, and distinct distances in combinatorial geometry. Recent publications (2023–2025) highlight his contributions to understanding zeta function moments, shifted convolution problems, and VC dimension applications. These articles reflect a consistent theme of advancing knowledge in analytic number theory and its intersections with algebra, combinatorics, and geometry. No scientific awards or grants are explicitly mentioned in the provided texts. Sahay has no listed advisees or master’s/PhD students at this time. While no specific laboratories or research teams are detailed, his affiliations with Purdue University’s Department of Mathematics suggest involvement in collaborative research environments typical of such institutions.
Lila Kari is a Professor and Cheriton Faculty Fellow at the School of Computer Science , part of the University of Waterloo in Ontario, Canada. Her research focuses on Biodiversity informatics , data science , and machine learning applications in comparative genomics and metagenomics , particularly for analyzing genomic signatures through Chaos Game Representation (CGR) and alignment-free methods. 2023 : Environment and taxonomy shape genomic signatures of extremophiles 2020 : Machine learning for rapid pathogen classification during pandemics 2019 : Ultrafast DNA sequence classification with ML-DSP 2016 : Additive genomic signatures for enhanced taxonomic differentiation 2015 : Mapping genomic signature spaces for molecular distance analysis 2009-2005 : Foundational work in DNA language theory and computational biology Her work has been instrumental in developing composite DNA signatures that combine nuclear and organellar genomic data for improved species differentiation, and assembled DNA signatures that enable analysis from fragmented sequencing data. She contributes to global initiatives like BIOSCAN for biodiversity surveillance and has created tools such as MLDSP-GUI for accessible DNA sequence analysis.
Peter Buneman is currently a Professor of Database Systems at the University of Edinburgh , affiliated with the School of Informatics and the Foundations of Computer Science Laboratory . Previously, he held a Professor of Computer Science position at the University of Pennsylvania from 1975 to 2001, progressing from assistant to full professor. Education: PhD in Mathematics (1970), University of Warwick (Supervisor: E.C. Zeeman) MA in Mathematics (1966), University of Cambridge Research Interests: His work spans databases (semistructured data, XML, data provenance, distributed databases), programming languages (type systems, functional languages, semantics), and interdisciplinary areas like mathematical phylogeny , neural models , and applications of computers in the humanities . He has also contributed to database interfaces, knowledge bases, and data modeling. Scientific Awards: Member of the Order of the British Empire (2013) Fellow of the Royal Society (2009) Fellow of the Royal Society of Edinburgh (2004) Royal Society Wolfson Research Merit Award (2002) ACM Fellow (1999) Multiple Test of Time Awards (SIGMOD, ICDT) Broadband Awards from Nextgen Challenge and European Commission Additional Roles: Served as Graduate Chairman at University of Pennsylvania (1981-1987) and held visiting research positions at INRIA (France), Kyoto University (Japan), and Imperial College London.
Peter Stiller is a Professor in the Department of Mathematics and Computer Science at Texas A&M University, where he also serves as Assistant Director of the Institute for Scientific Computation. He holds dual S.B. degrees in Mathematics and Economics from MIT (1973), an M.A. (1974) and Ph.D. (1977) in Mathematics from Princeton University. Stiller's research spans algebraic geometry, applied computational geometry, robotics, and computer vision. His current projects investigate geometric methods for automated manufacturing, printed electronics fabrication, and hybrid systems control. Recent publications focus on optimizing inkjet-printed sensors, distributed navigation algorithms, and formal composition of control systems. Stiller maintains interdisciplinary collaborations bridging mathematics with engineering applications. He teaches courses in algebraic geometry and computational methods, advising graduate students in mathematical applications. Stiller holds joint appointments in Mathematics (Blocker 623D), Computer Science (HRB), and ISC (Blocker), with multiple contact points for collaboration.
Prasad Tetali is the Alexander M. Knaster Professor and Department Head of the Department of Mathematical Sciences at Carnegie Mellon University (CMU), located in Pittsburgh, PA. He also holds adjunct professorships at Emory University (Math/CS) and the Georgia Institute of Technology (Math/CoC). His academic journey includes a Ph.D. from the Courant Institute of Mathematical Sciences, NYU, and postdoctoral research at AT&T Bell Labs. Education: Ph.D. (1991), Courant Institute of Mathematical Sciences, NYU M.S. (1987), Indian Institute of Science, Bangalore, India Postdoctoral Appointments: Mathematical Sciences Research Center, AT&T Bell Labs Research Interests: Dr. Tetali's work focuses on Discrete Mathematics, Probability Theory, and Theoretical Computing. Key areas include Markov chains, isoperimetry, combinatorics, computational number theory, and algorithm design. His contributions span foundational theory and applications in optimization, statistical physics, and network analysis. Publications & Trends: His research has led to influential papers on topics like mixing times of Markov chains, entropy inequalities, and combinatorial optimization. Notable works include foundational studies on the Potts model, the Swendsen-Wang algorithm, and sharp threshold phenomena in number theory. Awards & Recognition: AAAS Fellow SIAM Fellow (Inaugural Class, 2009) Fellow of the American Mathematical Society AMS Fellow (Inaugural Class, 2012) Georgia Tech’s Regents Professor Advising & Grants: Dr. Tetali has mentored 11 PhD students and numerous postdocs. His grants include leadership roles in initiatives such as the SIAM Activity Group on Discrete Mathematics and the ACO PhD Program at Georgia Tech. He has also held editorial roles at top journals like SIAM Journal on Discrete Mathematics and Random Structures & Algorithms. Labs & Collaborations: His work often intersects with interdisciplinary teams, including contributions to distributed algorithms, network science, and computational mathematics. He actively collaborates with researchers in computer science, physics, and applied mathematics.
Tom Bohman is a Professor of Mathematical Sciences at Carnegie Mellon University, affiliated with the Mellon College of Science. His research focuses on extremal and probabilistic combinatorics, exploring discrete structures inspired by mathematics, information theory, statistical physics, and computer science. He holds a Ph.D. from Rutgers University and has held postdoctoral positions at MIT and the Mathematical Sciences Research Institute (MSRI). Bohman's work includes studies on random graph processes, such as the triangle-free process and Hamilton cycles in random graphs, as well as hypergraph coloring and Ramsey numbers. His publications span over three decades, addressing topics like coprime matchings, lonely runner conjectures, and dynamic concentration phenomena in combinatorial systems. He teaches advanced courses in combinatorics and discrete mathematics, including Graph Theory and Random Structures & Algorithms. His research has contributed to understanding phase transitions in random processes and the interplay between combinatorial structures and probabilistic methods. While no awards are explicitly listed, his extensive publication record and editorial roles (e.g., with Random Structures & Algorithms ) highlight his academic impact. Bohman's work often bridges theoretical foundations with algorithmic applications, influencing both pure and applied combinatorics.
Boris Bukh is a Professor of Mathematics at Carnegie Mellon University (CMU), affiliated with the Department of Mathematical Sciences within the Mellon College of Science. He holds a Ph.D. from Princeton University and has held postdoctoral positions at the University of Cambridge and Churchill College. His research focuses on combinatorics, discrete geometry, extremal graph theory, and geometric selection theorems. He has received prestigious awards such as the Sloan Research Fellowship and the NSF CAREER Award. His work spans topics like Turán problems, geometric configurations, and algebraic methods in combinatorics. Recent publications explore extremal graph structures, convex polytopes in restricted point sets, and applications of random algebraic constructions to computational complexity. Bukh organizes events like the Math Kangaroo competition, fostering mathematics engagement among students. Key contributions include advancements in Ramsey theory, coding theory, and the intersection of combinatorics with geometry. His research often bridges theoretical insights with computational techniques, addressing problems in graph density, geometric incidences, and discrete optimization.
Thomas Lam is a Research Fellow at the Chair of Stochastics in the Faculty of Mathematics at Ruhr University Bochum. He completed his Master's thesis (2024) on two-sample testing in spiked covariance models under Professor Holger Dette and his Bachelor's thesis (2022) on Fermat's Polygonal Number Theorem under Professor Markus Reineke. His research interests span statistical inference in covariance modeling and number theory. Current work focuses on hypothesis testing for high-dimensional covariance structures, building on his Master's research in spiked covariance models.
