Find Academic Supervisors

James MaynardView profile

Professor

• Analytic Number Theory
• Prime Numbers
• Sieve Methods
• +1 more

James Maynard is a Professor of Number Theory at the University of Oxford , holding a Title IV Professorship equivalent to a UK chair or US full professor. He has held prestigious positions including Membership at the Institute for Advanced Study (Princeton, 2017), Research Membership at MSRI (Berkeley, 2017), and a Clay Research Fellowship (2015-2018). His research focuses on analytic number theory , particularly prime numbers and sieve methods , with groundbreaking work on prime gaps and Diophantine approximation. EDUCATION DPhil in Mathematics (2009-2013), Balliol College, Oxford Part III Mathematics (2008-2009), Queens’ College, Cambridge BA Mathematics (2005-2008), Queens’ College, Cambridge Maynard’s research explores the structure of prime numbers, including prime distribution , digital properties of primes , and norm form representations . His work has revolutionized understanding of bounded prime gaps and extremal prime spacing using advanced sieve techniques and probabilistic methods. Maynard’s publications (15 most recent) span analytic number theory , prime distribution , and Diophantine approximation . Key subfields include Bounded Gaps Between Primes , Digital Restrictions in Primes , Probabilistic Methods in Number Theory , and Algorithmic Sieve Optimization . Scientific Awards Fields Medal (2022) Cole Prize in Number Theory (2020) ERC Starting Grant (€1.5m, 2020-2025) Compositio Prize (2019) Wolfson Merit Award (2017) EMS Prize (2016) Erdős $10,000 Problem Prize (2016) Clay Research Fellowship (2015-2018) Whitehead Prize (2015) Ramanujan Prize (2014) Maynard has advised no explicitly named students but collaborates extensively in number theory. His grants include the ERC Starting Grant (2020-2025) and Wolfson Merit Award (2018-2023) . He has contributed to collaborative projects like the Polymath group and served as a Summer Consultant at GCHQ/Heilbronn Institute (2008-2012).

Ying ChenView profile

Associate Professor

• Financial Statistics
• Machine Learning
• Quantitative Finance
• +7 more

Assoc Prof Ying Chen is an Associate Professor at the National University of Singapore , affiliated with the Department of Mathematics, Asian Institute of Digital Finance (as Academic Director of PhD Program in Digital FinTech 2022–2024), Risk Management Institute (2019–2023), Department of Statistics and Data Science (2019–2023), and Department of Economics (2018–2023). She also contributes to NUS Graduate School for Integrative Sciences and Engineering since 2016. Research Interests include: AI forecasting and quantum computing for finance Nonstationary time series and functional data analysis Energy data analytics and precision medicine Network autoregression and spatial-temporal modeling Explainable AI and citation metrics Portfolio liquidation and market-making algorithms Article Trends demonstrate expertise in: Adaptive forecasting for gas flows and electricity prices Blockchain network influence detection Quantum computing applications in finance Functional autoregression with mixed predictors Credit rating fairness and explainability High-resolution implied volatility modeling Scientific Awards include: ISI Elected Member (2016–) International Statistical Institute Council (2023–2027) IASC Scientific Secretary (2017–2019, 2023–2025) Advisory roles for EU FIN-TECH and xAIM projects

Marcella LusardiView profile

Assistant Professor

• Catalysis
• Materials Science
• Sustainable Energy
• +4 more

Marcella Lusardi is an Assistant Professor in the Department of Chemical and Biological Engineering and the Princeton Materials Institute at Princeton University, leading interdisciplinary research at the intersection of materials synthesis, catalysis, and sustainability. Her educational background includes: Ph.D. in Materials Science and Engineering from MIT (2018) B.S. in Chemical Engineering from Columbia University (2012) Dr. Lusardi's research focuses on designing advanced catalytic materials for environmental challenges, with core expertise in surface science, light-matter interactions, and complex materials processing. Her group develops natural and engineered materials for energy and sustainability applications, emphasizing CO 2 capture/reduction, pollution abatement, and photocatalysis through molecular-level catalyst design. The MatCat Lab integrates experimental techniques like NMR spectroscopy with computational guidance to create scalable solutions for closed carbon cycles and greener chemical processes. Analysis of her 15 most recent publications (2019-2025) reveals a dominant focus on zeolite-based catalysis for CO 2 conversion and carbonylation reactions, with growing emphasis on supramolecular assemblies and water-tolerant acid catalysts. Her work consistently bridges fundamental material properties with practical sustainability applications, showing progression toward integrated systems for direct air capture and light-mediated reactions. The MatCat Lab employs a highly interdisciplinary approach centered on defect engineering in silica matrices and molecular recognition for supramolecular networks. Current projects target tailored reaction environments for CO 2 reduction and microplastic oxidation, utilizing advanced synthesis methods and structural elucidation to develop practical catalytic technologies for a sustainable future.

Ben GreenView profile

Professor

• Additive Combinatorics
• Analytic Number Theory
• Harmonic Analysis
• +3 more

Ben Green is the Waynflete Professor of Pure Mathematics at the University of Oxford and a Fellow of Magdalen College. His work spans additive combinatorics, analytic number theory, harmonic analysis, ergodic theory, discrete geometry, and group theory, with a focus on interdisciplinary approaches. Research Interests: Additive combinatorics and its applications to primes Analytic number theory (prime distribution, L-functions) Harmonic analysis (Fourier methods, spectral theory) Ergodic theory and its combinatorial applications Discrete geometry (ordinary lines, convex structures) Group theory (approximate groups, expansion) Article Trends: His recent work emphasizes multiplicative functions, Ramsey-type problems in number theory, expansion in finite groups, and extremal set theory. Themes include prime gaps, arithmetic progressions, and interactions between analysis and algebra. Scientific Awards: Clay Research Award (2004) Ostrowski Prize (2005) Whitehead Prize (2005) Leverhulme Prize (2007) European Mathematical Society Prize (2008) Royal Society Fellow (2010) Sylvester Medal (2014) Senior Whitehead Prize (2019) Advising: Ben has supervised numerous D.Phil students across additive combinatorics, analytic number theory, and related fields. Past students hold postdoctoral and academic positions globally.

Ye ZhishengView profile

Associate Professor

• Inventory Control
• Reliability Engineering
• Emergency Response Systems
• +4 more

Ye Zhisheng is the Dean’s Chair and Associate Professor in the Department of Industrial Systems Engineering & Management at the National University of Singapore (NUS). His research focuses on reliability engineering, inventory control, emergency response systems, and statistical modeling. He holds a PhD in Industrial and Systems Engineering from NUS, along with a BEng in Material Science and Engineering and a BEco in Economics from Tsinghua University. His work emphasizes practical applications in mission-critical systems, predictive maintenance, and data-driven decision-making. Current research initiatives include optimal maintenance policies for manufacturing systems, degradation analysis of bearings, and federated learning approaches for battery lifecycle prediction. He has pioneered methods for integrating physics-informed neural networks into prognostics and health management (PHM) systems. Key technical contributions span advanced statistical methodologies like sieve estimation for survival data, phase-type distributions modeling, and condition-based maintenance optimization. His interdisciplinary approach bridges operations research, mechanical engineering, and computer science to address complex reliability challenges. Recent projects include resilient consensus-based power grid management and contamination source identification frameworks. Notable collaborations involve developing intelligent cross-domain fault diagnosis systems using transformer networks and advancing the Internet of Federated Things (IoFT) for distributed data analytics. His work has been applied in aerospace, telecommunication infrastructure, and medical emergency response systems.

Emmanuel KowalskiView profile

Professor

• Automorphic forms
• L-functions
• Analytic Number Theory
• +5 more

Emmanuel Kowalski is a Professor of Mathematics at ETH Zurich , where he has been since 2008. Previously, he held professorships at Université Bordeaux I (2000–2007) and was a Veblen Research Instructor at Princeton University and the Institute for Advanced Study (1998–2000). His research focuses on analytic number theory, automorphic forms, and algebraic geometry. Education: École Normale Supérieure de Lyon (1989–1992); PhD in Mathematics from Rutgers University (1998). Research Interests include automorphic forms, L-functions, sieve methods, exponential sums, and probabilistic number theory. His work often bridges number theory with algebraic geometry and harmonic analysis. He has authored over 70 research papers and 6 books, including the influential Analytic Number Theory (2004) with Henryk Iwaniec. Scientific Awards and Invitations include the von Neumann Visiting Fellowship at IAS Princeton (2009), membership in the Board of the Institut des Hautes Études Scientifiques (2016–present), and four invitations to lecture at the prestigious Bourbaki Seminar. He has also delivered key lectures at the Riemann International School of Mathematics and conferences honoring major mathematicians. Grants and Leadership He has organized numerous conferences and research programs, including the 2019 Arithmetic, geometry and modular forms conference at FIM and the 2022 goMath program on Women in Mathematics. He co-leads projects funded by the Swiss National Science Foundation (SNF), such as Trace functions and arithmetic Fourier transforms .

• Heterogeneous Catalysis
• Catalytic Materials Synthesis
• Zeolite and Molecular Sieve Research
• +3 more

Rajamani Gounder is the R. Norris and Eleanor Shreve Professor of Chemical Engineering at Purdue University's Davidson School of Chemical Engineering. He leads the Gounder Research Group, focusing on heterogeneous catalysis, zeolite synthesis, and catalytic materials for energy and environmental applications. His work includes developing structure-function relationships in zeolites for reactions like NOx reduction, hydrocarbon conversion, and biomass processing. Education: B.S., University of Wisconsin (2006); Ph.D., UC Berkeley (2011); Postdoctoral Fellow, Caltech (2011-2013). Research Interests: The group studies catalyst design for renewable energy, petroleum processing, and pollution control. Key areas include zeolite-based catalysts for NOx abatement, propene oligomerization, and methane oxidation. They emphasize synthesizing materials with controlled active site environments to optimize reactivity and selectivity. Publications: Recent studies explore copper ion mobility in Cu-CHA zeolites, propene oligomerization in MFI voids, and NH3 oxidation kinetics. These highlight advancements in catalytic mechanisms and material design. Awards: Recognitions include the Royal Society of Chemistry Fellowship (2023), ISCRE Rutherford Aris Award (2023), and multiple teaching awards (e.g., R. Norris Shreve Award). His work has been funded by DOE, NSF, and industry partnerships. Advising & Grants: Supervises a team of ~30 students (PhD, master's, undergrad) and collaborates with the Purdue Catalysis Center. His research is supported by grants from agencies like DOE and NSF. Labs/Teams: The Gounder Group operates in Forney Hall, part of Purdue's chemical engineering facilities. They engage with CISTAR (Catalysis Center for Energy Innovation) and other interdisciplinary networks.

Daniel WilhelmView profile

Professor

• Econometrics
• Statistics
• Nonparametric Methods
• +4 more

Daniel Wilhelm is a Professor of Statistics and Econometrics at LMU Munich, with a courtesy appointment in the Department of Economics. His research focuses on econometric theory, nonparametric methods, measurement error modeling, and statistical inference. He leads the Statistics and Econometrics Group at LMU and holds affiliations with the Centre for Microdata Methods and Practice (CeMMAP), Institute for Fiscal Studies (IFS), and the Centre for Research and Analysis of Migration (CReAM). Wilhelm’s work includes groundbreaking contributions to NPIV estimation, robust statistical testing, and the development of R and Stata packages for rank inference and econometric analysis. His recent publications address topics like rank-based inference, measurement error detection, and high-dimensional independence testing. He organizes academic events such as the Munich Econometrics Seminar and the LMU-Todai Econometrics Workshop. His research emphasizes methodological rigor and practical applications, with a focus on improving statistical techniques for social science and policy analysis.

Keith ConradView profile

Associate Professor

• Number Theory
• Algebraic Number Theory
• Analytic Number Theory
• +3 more

Keith Conrad is an Associate Professor in the Department of Mathematics at the University of Connecticut (UConn), part of the College of Liberal Arts and Sciences. His research focuses on Number Theory, particularly in areas such as algebraic and analytic number theory, prime numbers, arithmetic geometry, and modular forms. He has published extensively on topics like congruent numbers, prime specialization, and the Möbius function. His work integrates classical number theory with modern algebraic techniques, contributing to foundational understanding in the field. Conrad is actively involved in academic outreach, organizing and teaching at programs like the Ross Mathematics Program and PROMYS. He has delivered lectures on advanced topics such as L-functions, the Riemann Hypothesis, and the ABC conjecture. His expository papers and teaching materials emphasize clarity and accessibility, bridging gaps between complex mathematical concepts and broader audiences. Conrad's academic contributions include significant publications in journals like *Mathematics Magazine* and *Journal für die reine und angewandte Mathematik*, as well as expository works on modular forms, prime patterns, and historical aspects of representation theory. He maintains a comprehensive website with resources for students and researchers, including detailed lecture notes, problem sets, and links to mathematical tools and software.

Xiang LimingView profile

Associate Professor

• Survival Analysis
• Longitudinal/Clustered Data Analysis
• Mixture Modelling
• +3 more

Assoc Prof Xiang Liming is an Associate Professor in the Division of Mathematical Sciences at Nanyang Technological University (NTU), Singapore, serving as Assistant Chair (Students). She holds editorial roles at *Computational Statistics & Data Analysis* and *Statistics in Medicine*. With a PhD in Statistics (City University of Hong Kong, 2002), her research focuses on survival analysis, longitudinal data analysis, and biostatistical methods. Notable contributions include methodologies for semi-competing risks, interval-censored data, and mixture models. Her work bridges statistical theory with biomedical applications, addressing challenges in clinical trials and public health. Awards include the 2009 IIE Transactions Best Paper Award and the Outstanding Research Thesis Award (2002–2003, CityU). Education: PhD in Statistics, City University of Hong Kong (2002) Postdoctoral Research: Hong Kong University of Science and Technology (2002–2003) and CityU (2003–2006) Research Interests: Survival analysis methodologies, including frailty models, cure models, and quantile regression for censored data. She develops robust statistical approaches for clustered/longitudinal data, addressing missingness and overdispersion. Applications span biomedical research, epidemiology, and quality management. Grants & Collaborations: Her grants include work on robotic-assisted stroke rehabilitation (2021) and LNG cold energy utilization systems (2017–2019). She collaborates with clinical teams on trials involving upper limb neurorehabilitation technologies. Labs & Teams: Leads statistical method development for multi-center clinical trials, particularly in biostatistics and survival analysis frameworks. Active in NTU’s School of Physical & Mathematical Sciences research initiatives.

Christian JaegerView profile

Researcher

• Machine Learning
• Optimal Control
• Reinforcement Learning
• +3 more

Dr. Christian Jaeger is a Researcher at the Zurich University of Applied Sciences (ZHAW) School of Engineering, focusing on Machine Learning in Optimal Control for Industry. His work bridges engineering and computer science with applications in industrial automation and building systems. His research interests span Machine Learning , Optimal Control , Reinforcement Learning , Energy Management Systems , and Industrial Automation . Jaeger has led multiple research projects including a preliminary study on automated IBN heat pumps and a feasibility study on Reinforcement Learning Control for heating systems. His work demonstrates a clear trajectory from traditional manufacturing technology toward contemporary AI-driven control systems. Jaeger's publication record shows consistent output from 2005 to 2024, with recent focus on energy optimization in building control using reinforcement learning, 3D printing techniques, and model predictive control. His research demonstrates strong interdisciplinary connections between computer science, engineering, and practical industrial applications. His scientific contributions include publications in journals such as Applied Sciences and the Journal of the British Interplanetary Society, along with numerous conference proceedings from international events including EuroSun and the International Symposium on Nonlinear Theory and its Applications. At ZHAW, Jaeger has served as project leader for multiple completed research initiatives including adaptive energy management systems for buildings and automated heat pump systems. His work demonstrates strong industry connections with applications in building automation and industrial manufacturing processes.

J. Ilja SiepmannView profile

Professor

• Chemical Theory and Computation
• Chemical Physics
• Environmental and Green Chemistry
• +4 more

J. Ilja Siepmann is a Distinguished McKnight University Professor and Distinguished University Teaching Professor at the University of Minnesota's Department of Chemistry, with affiliations spanning Chemical Engineering, Materials Science, and Data Science. His research integrates molecular simulations, force field development, and machine learning to study adsorption phenomena, phase equilibria, polymer chemistry, and nanoporous materials. Education: Undergraduate: University of Freiburg, Germany (1983-1987) Graduate: University of Cambridge, UK (PhD, 1988-1991) Post-doctoral: IBM Zurich Research Lab, Koninklijke/Shell Lab, and University of Pennsylvania (1991-1994) Research interests focus on chemical theory, materials genomics, and environmental chemistry, with emphasis on energy-efficient separations, nanostructured materials, and sustainable chemical processes. Computational methods like Monte Carlo algorithms and machine learning underpin his investigations into fluid interfaces, nucleation, and catalytic systems. Recent publications emphasize adsorption thermodynamics, molecular simulations of complex fluids, data-driven materials discovery, and polymer self-assembly. Trends include integration of machine learning with molecular modeling, nanoporous materials for clean energy, and phase behavior of refrigerants. Awards: Distinguished McKnight University Professor Distinguished University Teaching Professor Advises graduate and undergraduate researchers in computational chemistry projects. Leads the Siepmann Group at Kolthoff Hall, part of the Chemical Theory Center and Nanoporous Materials Genome Center. Research funded through MURI and industry partnerships.

Tim BrowningView profile

Professor

• Number Theory
• Analytic Number Theory
• Diophantine Geometry
• +4 more

Tim Browning is a Professor of Number Theory at the Institute of Science and Technology Austria (IST Austria). He leads the Browning Group, focusing on analytic number theory and its interfaces with algebraic geometry. His research addresses Diophantine equations, rational points on algebraic varieties, and the distribution of arithmetic objects. He organizes the Algebraic Geometry & Number Theory Seminar and the Women in Math Day. Previously, he held roles at the University of Bristol and University of Oxford. He has authored over 100 publications and received accolades including the Ferran Sunyer i Balaguer Prize and an ERC Starting Grant. His group includes PhD students and postdocs working on topics like rational points, sieve methods, and arithmetic statistics. Education: PhD in Mathematics, University of Oxford (2002) Postdoctoral Fellowships at University of Oxford and Université de Paris-Sud Research Interests: Analytic and arithmetic methods in number theory, Diophantine geometry, rational points on varieties, circle method, sieve theory, and arithmetic statistics. His work often combines geometric and analytic techniques, such as the circle method and algebraic geometry to solve problems like Manin's conjecture and the distribution of solutions to polynomial equations. Grants & Leadership: ERC Starting Grant (2012) Serves on editorial boards of journals like Compositio Mathematica and Commentarii Mathematici Helvetici Organizes international conferences and workshops Labs/Teams: Leads the Browning Group at IST Austria, which includes postdocs and PhD students working on number theory and algebraic geometry. Collaborates with researchers globally on topics like the arithmetic of Fano varieties and rational curves.

Lillian Beatrix PierceView profile

Professor

• Analytic Number Theory
• Harmonic Analysis
• Number Theory
• +1 more

Lillian Beatrix Pierce is a Professor of Mathematics at Duke University, affiliated with the Trinity College of Arts & Sciences. She holds a B.A. from Princeton University (2002), an M.Sc. from the University of Oxford (2004), and a Ph.D. from Princeton University (2009). Her research focuses on analytic number theory and harmonic analysis, exploring intersections between oscillating functions, Diophantine equations, and arithmetic structures. Pierce has been recognized with prestigious awards, including the 2023 Guggenheim Fellowship, the 2018 Sloan Research Fellowship, and the 2019 PECASE award. She leads research grants from the NSF and Simons Foundation, investigating topics like class groups, character sums, and oscillatory integrals. Her work bridges number theory and harmonic analysis, with contributions to sieve methods, maximal operators, and decoupling techniques. She serves on editorial boards for journals like the Journal of the AMS and Duke Mathematical Journal. Pierce also advocates for accessibility in mathematics, co-founding the journal Essential Number Theory to disseminate foundational research. Her academic journey includes roles as a von Neumann Fellow at the Institute for Advanced Study and a Rhodes Scholar. Notable publications include breakthroughs on the Vinogradov mean value theorem, ℓ-torsion in class groups, and polynomial Carleson operators. She actively mentors and collaborates in global research networks, fostering interdisciplinary approaches to mathematical challenges.

Asif ZamanView profile

Associate Professor

• Analytic Number Theory
• Probabilistic Number Theory
• Algebraic Number Theory
• +7 more

Asif Zaman is an Associate Professor in the Faculty of Arts and Science at the University of Toronto. His research focuses on Analytic Number Theory , Probabilistic Number Theory , and Arithmetic Statistics , with applications to Algebraic Structures , L-functions , and Modular Surfaces . He has contributed to problems involving the distribution of prime numbers, zeros of L-functions, and mass equidistribution. Research highlights include work on the Chebotarev Density Theorem , Random Multiplicative Functions , and Binary Quadratic Forms . His recent publications address advanced topics such as Artin L-functions , GL(n) Sieve Methods , and Multiplicative Chaos in number theory. Zaman has co-authored articles with prominent researchers like James Thorner and Robert J. Lemke Oliver, focusing on non-vanishing properties, explicit density estimates, and Siegel zeros. Zaman teaches mathematics courses at the University of Toronto, including MAT237 Multivariable Calculus with Proofs and MAT198 Cryptology . His teaching philosophy emphasizes active learning, collaboration, and analytical skill development, inspired by resources like Mathematical Mindsets and the American Mathematical Society blog series.