Find Academic Supervisors

• Mathematics of Data Science
• Stochastic Geometry
• Convex Geometry
• +6 more

Eliza O'Reilly is an Assistant Professor in the Department of Applied Mathematics & Statistics at Johns Hopkins University. Her research focuses on the intersections of stochastic geometry , convex geometry , high-dimensional probability , and statistical learning theory . Her work explores: Nonconvex and convex regularizers in inverse problems Random tessellations and their machine learning applications Spectrahedral regression for convex function approximation Determinantal point processes for modeling repulsive interactions High-dimensional random convex sets and their asymptotic geometry Her research is supported by the National Science Foundation . Recent publications investigate gradient-based dimension reduction, oblique decision trees, and geometric properties of regularizers. She has received her PhD from the University of Texas at Austin and was a postdoctoral scholar at Caltech.

Shaun FallatView profile

Professor

• Combinatorial Matrix Theory
• Algebraic Graph Theory
• Matrix Positivity
• +3 more

Shaun Fallat is a Professor in the Mathematics and Statistics Department at the University of Regina, within the Faculty of Science. He holds a Ph.D. in Applied Mathematics from the College of William and Mary (1999) and degrees from the University of Victoria (BSc and MSc). His research focuses on combinatorial matrix theory, algebraic graph theory, matrix positivity, and total positivity, with over 90 publications and a co-authored book on totally nonnegative matrices. He has supervised numerous graduate and undergraduate students, postdoctoral fellows, and visiting scholars, fostering a collaborative research environment. Fallat has delivered lectures globally and organized conferences, including the Western Canada Linear Algebra Meeting. His awards include the U. Regina Alumni Association Teaching Award, Olga Taussky-Todd Lecturer (2014), and Inaugural Hans Schneider Lecturer (2015). He serves as an Associate Editor for Linear Algebra and its Applications and the Canadian Journal of Mathematics . His research spans topics such as zero forcing parameters, spectral graph theory, and matrix inequalities. Recent work includes studies on hypertrees, graph complements, and applications of combinatorial matrix analysis. Fallat is actively involved in mentoring and promoting mathematics education at all levels, including outreach to K-12 students.

• Combinatorial group theory
• Geometric semigroup theory
• Algorithmic problems in algebra
• +6 more

Robert D. Gray is a Professor of Mathematics at the School of Mathematics, University of East Anglia. His research focuses on combinatorial and geometric group and semigroup theory, algorithmic problems in algebra, decidability, homological finiteness properties, and group actions on graphs and topological spaces. EPSRC Research Fellow Editorial Board: International Journal of Algebra and Computation Available for PhD supervision in semigroup and inverse monoid theory His recent work explores: Topological finiteness properties of monoids Undecidability in one-relator inverse monoids Algorithmic properties of inverse monoids Maximal subgroups in special inverse monoids Key article trends include: Geometric and algorithmic aspects of inverse monoids Homological properties of semigroups Connections between group theory and semigroup theory Applications to graph theory and automata Scientific Awards: EPSRC Fellowship EP/V032003/1 EPSRC grant EP/N033353/1 EPSRC Postdoctoral Fellowship EP/E043194/1 Contact: Room S1.29, School of Mathematics, University of East Anglia, Norwich NR4 7TJ. Email: Robert.D.Gray@uea.ac.uk . Phone: +44 1603 591443.

Yizao WangView profile

Professor

• Probability Theory
• Stochastic Processes
• Extreme Value Theory
• +4 more

Yizao Wang is a Professor in the Department of Mathematical Sciences at the University of Cincinnati. He holds a Ph.D. from the University of Michigan (2012) and specializes in Probability Theory, Stochastic Processes, and their applications, with a focus on extreme value theory, long-range dependence, and random fields. His research includes studies on asymmetric exclusion processes, fractional Brownian motion, and self-similar processes. Education : Ph.D. in Mathematics, University of Michigan, 2012. Research Interests : Probability theory, stochastic processes, extreme value theory, long-range dependence, random fields, limit theorems, and applications in finance and statistics. His work frequently explores the interplay between combinatorial structures and stochastic models, such as random partitions and operator-scaling processes. Grants : He has led and co-led multiple grants, including: DoD Army Research Laboratory: Advances in Extreme Value Theory with Long-Range Dependence ($84,229, 2020–2023) National Security Agency: From Random Partitions to Self-Similar Processes ($40,000, 2016–2018) National Science Foundation: Cincinnati Symposium on Probability Theory and Applications ($20,000, 2018–2019) Students and Advising : Mentored numerous graduate and undergraduate students in capstone projects and independent studies, focusing on topics like random walks, branching processes, and stochastic differential equations. Notable advisees include Connor McClellan, Yiyang Yu, and Weiqing Yu (recipient of the Charles Phelps Taft Senior Thesis Fellowship). Labs/Teams : Active in collaborative research groups within the department, contributing to interdisciplinary projects in stochastic modeling and mathematical finance. Teaches advanced courses in probability, stochastic processes, and financial mathematics.

• Numerical Analysis
• Uncertainty Quantification
• Inverse Problems
• +3 more

Oliver G. Ernst is a Professor of Numerical Analysis at Technische Universität Chemnitz . His research focuses on Numerical Analysis , Uncertainty Quantification , and Inverse Problems , with applications in Thermo-Hydro-Mechanical (THM) processes , Electromagnetics , and Stochastic Partial Differential Equations . He is associated with the Numerical Analysis group at TU Chemnitz. Key Research Areas : Efficient numerical methods for PDEs Krylov subspace techniques Stochastic finite element methods Multi-physics modeling Geoscientific applications Recent Publications (2025-2010): THM simulations under uncertainty Neural network PDE solvers Bayesian inversion frameworks Rational Krylov algorithms Deflated restarting strategies Collaborations : TU Bergakademie Freiberg University of Manchester Technical University of Munich University of Maryland University of Geneva Software Development : Contributor to OpenGeoSys platform Developer of FEMALY MATLAB library Academic Recognition : h-index 32, i10-index 66, with over 4423 citations since 2020.

Clinton ConleyView profile

Associate Professor

• Descriptive Set Theory
• Ergodic Theory
• Combinatorics
• +4 more

Clinton Conley is an Associate Professor and Director of Graduate Studies in the Department of Mathematical Sciences at Carnegie Mellon University, part of the Mellon College of Science. He holds a Ph.D. in Mathematics from UCLA and has held postdoctoral appointments at the Kurt Gödel Research Center (Vienna, Austria) and Cornell University. His research focuses on descriptive set theory, measurable group actions, and Borel graphs, exploring intersections with ergodic theory, combinatorics, and set theory. Key research areas include measurable chromatic numbers, Borel combinatorics, and hyperfinite equivalence relations. His work often bridges abstract set-theoretic principles with concrete problems in dynamics and graph theory. Notable awards include the Julius Ashkin Award. Education: Ph.D. in Mathematics, University of California, Los Angeles Postdoctoral Appointments: KGRC (Vienna), Cornell University Recent publications span topics like measurable regular subgraphs, quasi-invariant measures, and hyperfiniteness in Borel combinatorics. Teaching includes advanced courses on descriptive set theory, set theory, and mathematical paradoxes. Advising and grants sections remain unspecified in available data. No lab or team affiliations are noted.

Jignesh PatelView profile

Professor

• Systems
• Data-Intensive and Cloud Computing
• Databases
• +3 more

Jignesh Patel is a Professor in the Computer Science Department at Carnegie Mellon University, specializing in database systems and data-intensive computing. His research focuses on hardware-software synergy for high-performance databases and democratizing data analytics through no-code interfaces. He co-founded DataChat, a startup focused on intuitive data analytics platforms. He holds fellowships from AAAS, ACM, and IEEE, along with teaching awards. His work emphasizes building systems that leverage novel hardware and user-friendly interfaces. Research interests include scalable data platforms, LLM-based query interfaces, and optimizing database performance through hardware collaboration. Notable projects include the Quickstep data platform and the Ava conversational interface. Awards: Fellow of AAAS, ACM, IEEE; Multiple Teaching Awards Labs/Teams: CRISP (Intelligent Storage and Processing), DataChat startup

• Mathematical Physics
• Partial Differential Equations
• Probability Theory
• +5 more

Joona Oikarinen is a Postdoctoral Researcher at Aalto University's Department of Mathematics and Systems Analysis within the School of Science. His research focuses on interdisciplinary areas including Mathematical Physics, Quantum Field Theory, and Probability Theory. He contributes to groups studying Nonlinear Partial Differential Equations (NPDE), Conformal Field Theory, and Differential Geometry. Key research interests span Liouville Quantum Field Theory, Gaussian Multiplicative Chaos, and the interplay between stochastic processes and geometric structures. His work often bridges theoretical frameworks with applications in critical phenomena and statistical mechanics. Joona is affiliated with research clusters exploring stress-energy tensors in conformal field theories and the mathematical foundations of two-dimensional quantum systems. His research also intersects numerical analysis and systems analysis, reflecting his department’s multidisciplinary approach.

James CranchView profile

Lecturer

• Homotopy theory
• Category theory
• Theoretical Computer Science
• +3 more

Dr James Cranch is a Teaching Fellow in the School of Mathematical and Physical Sciences at the University of Sheffield, holding critical roles as Chair of Schools Liaison, Disability Liaison Officer, Outreach Officer, and Tutor for Men Students. Based in G39c, Hicks Building, he actively contributes to academic administration and student support services. His research centers on homotopy theory and category theory, with significant interdisciplinary extensions into theoretical computer science. Key focus areas include concurrency theory, monoidal category applications, and homotopy type theory, demonstrating consistent exploration of algebraic structures in computational contexts since 2010. Recent publications (2020-2024) reveal a concentrated effort on convolution frameworks for concurrency, interacting monoidal systems in computing, and cohomological studies of partition algebras. These works, published in venues like Mathematical Structures in Computer Science, highlight his bridging of abstract mathematics with practical computing challenges through collaborations with Struth, Doherty, and others.

James EastView profile

Associate Professor

• Algebraic Semigroup Theory
• Combinatorial Semigroup Theory
• Transformation Semigroups
• +7 more

James East is an Associate Professor at the Western Sydney University , affiliated with the School of Computer, Data and Mathematical Sciences and the Centre for Research in Mathematics and Data Science. He served as an ARC Future Fellow from 2020 to 2023. PhD in Mathematics (2006) from the University of Sydney Postdoctoral fellowships at La Trobe University (2006-2007) and University of Sydney (2008-2010) His research focuses on algebraic and combinatorial semigroup theory , particularly transformation semigroups, diagram monoids, braid groups, and congruences. Trends in his recent work include studies of free projection/Idempotent-generated semigroups, twisted monoid products, tensor/category presentations, and lattice path structures. He serves on the editorial boards of the Journal of the Australian Mathematical Society and Communications in Algebra . Scientific awards : ARC Future Fellow (2020-2023) Current students/postdocs : Chad Clark (PhD student) Matthias Fresacher (PhD student) Azeef Muhammed Parayil Ajmal (Postdoctoral Fellow) He co-founded the Association of Australian Mathematics Students and actively promotes visual mathematics through tools like the Semigroups package for GAP .

Nic FreemanView profile

Lecturer

• Probability
• Stochastic Processes
• Random Geometry
• +3 more

Dr Nic Freeman is a Lecturer in Applied Probability and Programme Leader for Financial Mathematics at the School of Mathematical and Physical Sciences, University of Sheffield. He holds an academic position within the Department of Mathematics and is a member of the Probability research group. His research focuses on probability theory, stochastic processes, random geometry, fractals, and applications to population genetics and financial mathematics. Dr Freeman teaches courses such as MAS350 Measure and Probability, MAS352 Stochastic Processes and Finance, MAS451 Measure and Probability, and MAS452 Stochastic Processes and Finance. His work integrates theoretical probability with practical applications, including the study of preferential attachment models, coalescent processes, and spatial stochastic systems. He is affiliated with the Hicks Building, located in Room I20. Research interests span topics such as tightness criteria for random processes, Brownian web/net structures, and cluster dynamics in network models. His recent publications explore foundational aspects of stochastic processes and their convergence properties, contributing to both pure and applied probability theory. Dr Freeman collaborates within interdisciplinary teams and maintains an active research profile in mathematical probability.

Zongchen ChenView profile

Assistant Professor

• Randomized algorithms
• Discrete probability
• Machine learning
• +5 more

Zongchen Chen is an Assistant Professor in the School of Computer Science at the Georgia Institute of Technology . He holds a PhD in Algorithms, Combinatorics and Optimization from Georgia Tech (2021) and a BS in Mathematics & Applied Mathematics from Shanghai Jiao Tong University (2016). Previously, he was an Assistant Professor at University at Buffalo and a postdoctoral instructor at MIT. His research spans randomized algorithms , discrete probability , and machine learning , with current focus on: Markov chain Monte Carlo (MCMC) methods Approximate counting and sampling algorithms Learning/testing of high-dimensional distributions Phase transitions in combinatorial structures His publication profile shows strong emphasis on: Mixing time analysis of Markov chains (13/15 papers) Combinatorial problems including k-SAT, graph colorings, and spin systems Theoretical computer science venues (STOC/FOCS/SODA/RANDOM) Awards & Honors 2021 Outstanding Doctoral Dissertation Award, College of Computing, Georgia Tech Teaching Spring 2025: CS 3510 Design and Analysis of Algorithms Fall 2024: CS 8803 Counting and Sampling Spring 2024: CSE 632 Analysis of Algorithms II (University at Buffalo) Office: KACB 2134 | Email: chenzongchen@gatech.edu

Sunmee KimView profile

Assistant Professor

• Quantitative Psychology
• Behavioral Data Science
• Longitudinal Data Analysis
• +6 more

Sunmee Kim is an Assistant Professor in the Department of Psychology at the University of Manitoba's Faculty of Arts. She obtained her BS in Statistics, BA in Psychology, and MS in Mathematical Statistics from Korea University, followed by a PhD in Quantitative Psychology & Modelling from McGill University (2020). Dr. Kim serves as a Research Affiliate at the Centre on Aging and Associate Chair of AKCSE-WiSE. PhD (Quantitative Psychology and Modeling), McGill University, 2020 MS (Mathematical Statistics), Korea University, 2012 BS (Statistics) & BA (Psychology), Korea University, 2010 Her research focuses on developing innovative statistical techniques for longitudinal data methods, knowledge-based dimension reduction, and multivariate prediction models. This includes extensions of Extended Redundancy Analysis (ERA) like GEE-ERA and ERA-Tree, as well as predictive model indices and applications in behavioral data science. Dr. Kim collaborates with domain experts in Health, Sociology, and Space Systems using large-scale datasets (CLSA, HRS) for intersectionality in health research, immigrant health studies, and methodological best practices. Her work is supported by NSERC and University of Manitoba funding programs. Scientific Awards 2024 - Early Achievement Award, AKCSE 2023 - WiSE Award, AKCSE 2023 - Invitation to 1st World Congress of Korean Scientists & Engineers 2022-2023 - Psychology Teaching Award Nominee 2022 - Invited International Scholar, Korea University BK21 Conference She mentors through the International Young Woman Scientist Camp and organizes WiSE sessions at AKCSE conferences, representing Canadian EDI practices internationally.

Patrick J.F. GroenenView profile

Professor

• Data Science
• Multidimensional Scaling
• Optimization Algorithms
• +5 more

Patrick J.F. Groenen is a full Professor of Statistics at the Erasmus School of Economics (ESE), Erasmus University Rotterdam , and currently serves as its Dean. His academic career spans leadership roles, including Director of the Econometric Institute (2014-2020) and President of the International Association for Statistical Computing (2015-2017). He has held visiting positions at Stanford University and contributed extensively to multidimensional scaling (MDS), data science , and statistical genetics . His research focuses on numerical algorithms for MDS, support vector machines , and optimization techniques applied to diverse fields. He is a founding editor of the open-access journal Journal of Data Science, Statistics, and Visualisation and has authored major textbooks including Modern Multidimensional Scaling and Applied Multidimensional Scaling and Unfolding . His work appears in top journals like Nature Genetics , Psychometrika , and Journal of Machine Learning Research . Recent publications highlight advancements in convex clustering , genomic prediction , and robust statistical methods . He has developed influential R packages such as GenSVM , SVMMaj , and smacof for multiclass classification and MDS software. His supervisory record includes 14 PhD students across economic psychology, genetics, and data science. Academic activities include editorial roles at Advances in Data Analysis and Classification and Psychometrika , alongside organizing international conferences like CARME 2007 on correspondence analysis. His contributions to nonlinear biplots and response style modeling have advanced visual data interpretation in social sciences.

Lydia Forssander-SongView profile

Professor

• Postcolonial Literatures
• Migrant Literatures
• South Asian Diasporic Fiction
• +3 more

Lydia Forssander-Song is a Professor of English at Trinity Western University (TWU), located in Langley, British Columbia. She has been teaching since 1998 and holds affiliations with ACCUTE, the Christianity and Literature Study Group, and the International Society for Religion, Literature, and Culture. Her research focuses on postcolonial literatures, particularly South Asian diasporic narratives and Islamic-influenced works. Education: B.A. English, First Class Honours (University of British Columbia, 1995) M.A. English (University of Toronto, 1997) Research Interests: Explores postcolonial identity construction through works by authors like Salman Rushdie, Michael Ondaatje, and Chimamanda Ngozi Adichie. Examines intersections of religion, migration, and cultural hybridity in global literatures. Recent work emphasizes ethical storytelling in pluralistic contexts. Publications: Over 20 articles and book chapters analyzing postcolonial authors, including critical studies of Rushdie’s migration themes and Ondaatje’s historical narratives. Regular contributor to Canadian Literature and Canadian Book Review Annual . Awards: Recipient of the University of British Columbia Scholarship and twice named to the Dean’s Honour List during her undergraduate studies. Teaching: Instructs foundational writing courses (WRTG 100, ENGL 102) and advanced seminars on postcolonial women’s novels (ENGL 290), Booker Prize winners (ENGL 400), and South Asian diasporic fiction (ENGL 607). Also edits literary works, including Karl Petersen’s children’s novels and memoirs. Conferences: Active presenter on themes like “Incarnational storytelling in Joy Kogawa’s Obasan” and “Postmodern faith in Yann Martel’s Life of Pi” at venues in Canada and Sweden. Served as panel chair for sessions on trauma and transcendence in 20th-century literature.