Find Academic Supervisors

• Algebraic Geometry
• Combinatorial Algebraic Geometry
• Syzygies
• +11 more

Daniele Agostini is a Junior Professor (Tenure Track) in the Department of Mathematics at Eberhard Karls University of Tübingen, affiliated with the Faculty of Mathematics and Natural Sciences. He is actively involved in the research section on Combinatorial Algebraic Geometry and serves as the international coordinator for the Mathematics Department. University: Eberhard Karls University of Tübingen School: Faculty of Mathematics and Natural Sciences Department: Department of Mathematics Academic Rank: Assistant Professor (Junior Professor, Tenure Track) Email: daniele.agostini@uni-tuebingen.de His primary research lies in algebraic geometry, with a focus on syzygies, curves, surfaces, abelian varieties, and their moduli spaces. He also explores interactions with probability, statistics, and mathematical physics. His recent publications reflect deep work in theta functions, KP solitons, and likelihood geometry, often in collaboration with institutions like MPI-MiS Leipzig and researchers such as Bernd Sturmfels. The 15 most recent publications demonstrate a consistent trend in combinatorial algebraic geometry, particularly in the study of moduli spaces, integrable systems, and computational aspects of algebraic varieties. Key themes include the geometry of curves and their Jacobians, tropical methods, and applications to mathematical physics and statistics. His work bridges theoretical depth with computational experimentation. Otto Hahn Medal (awarded to co-supervised PhD student Claudia Fevola, 2024) Agostini advises several PhD students, including Kees Heesterbeek, Clemens Nollau, Javier Sendra, and Claudia Fevola. He has been involved in significant research projects such as the ANR-DFG POK0 project on positivity of K-trivial varieties and the SFB-TRR 195 'Symbolic Tools'. He has taught courses such as Algebraic Curves, Algebraic Geometry, and Number Theory at Tübingen, Leipzig, and Berlin. He leads a research group in combinatorial algebraic geometry, with current members including postdoc Felix Röhrle and PhD students. His research group includes current and former members such as Demir Eken, Claudia Fevola, Leonid Monin, and Angel Rios Ortiz. He is also part of the URTAG seminar and contributes to the CRC TRR 195 collaboration, emphasizing interdisciplinary and international research engagement.

Naiomi CameronView profile

Professor

• Enumerative Combinatorics
• Algebraic Combinatorics
• Number Theory

Dr. Naiomi Cameron serves as Chair and Professor of Mathematics at Spelman College, where she teaches undergraduate courses including calculus, discrete mathematics, linear algebra, combinatorics, and number theory. A proud HBCU alumna, she earned both her Ph.D. and B.S. in Mathematics from Howard University and previously held faculty positions at Harvey Mudd College, Occidental College, and Lewis & Clark College, including a two-year term as associate dean. Her educational background is rooted in Howard University's mathematics program, reflecting her commitment to HBCU excellence. Dr. Cameron's research centers on enumerative and algebraic combinatorics and number theory, with significant contributions to the study of combinatorial structures such as trees, tableaux, polynomials, and lattice paths. She investigates inversion statistics, pattern avoidance, and sequences like Fibonacci and Motzkin numbers, often revealing deep connections between algebraic and combinatorial phenomena. Her publication record from 2000-2019 demonstrates consistent output in top combinatorics journals, with recurring themes in Dyck path analysis, Fibonacci tableaux variations, and polynomial combinatorics. This body of work shows evolving sophistication from foundational tree combinatorics to complex monodromy group investigations, maintaining focus on structural enumeration while expanding into algebraic applications. Dr. Cameron actively promotes diversity, equity, and inclusion in mathematics through undergraduate research mentorship and community service. Her dedication to cultivating the next generation of mathematicians is evident in her teaching philosophy and advocacy for underrepresented groups within the mathematical sciences.

• Stochastic Analysis
• Financial Mathematics
• Mathematical Biology
• +3 more

Roger Pettersson is a Professor at the Department of Mathematics, Linnaeus University, with a focus on stochastic analysis, financial mathematics, and mathematical biology. He is affiliated with the Faculty of Technology and leads research in Stochastic Analysis and Stochastic Processes , Computational Mathematics for Predictive Digital Twins (PreDiTwin) , and Deterministic and Stochastic Modelling under the Linnaeus University Centre for Data Intensive Sciences and Applications (DISA). His work bridges theoretical and applied mathematics, emphasizing numerical methods and epidemic models. Research Interests : Stochastic differential equations (SDEs/SPDEs), Lévy processes, financial modeling, biological systems, numerical approximations, and epidemic dynamics. Publications : Over 20 peer-reviewed articles (2002–2025) in journals like Stochastics , Applied Mathematics and Computation , and Chaos, Solitons & Fractals , focusing on stochastic control in epidemics, Lévy noise applications, and numerical methods for SDEs. Supervised Theses : Mentored over 20 bachelor’s and master’s students in projects spanning queueing systems, SPSS data analysis, neural networks for hydropower forecasting, and epidemic modeling. Collaborations : Active in interdisciplinary research, including forestry, wood, and building technologies, and contributes to the International Center for Mathematical Modeling (ICMM) .

Károly Böröczky Jr.View profile

Research Professor

• Lattice points in large bodies
• Minkowski type Monge-Ampere equations
• Logarithmic Brunn-Minkowski conjecture
• +9 more

Károly Böröczky Jr. is a Research Professor at the Alfréd Rényi Institute of Mathematics (Department of Geometry). His work spans convex geometry, discrete geometry, and geometric analysis, with a focus on inequalities like the Brunn-Minkowski and Prekopa-Leindler theorems, logarithmic curvature problems, and approximation of convex bodies. Research Grants : Logarithmic-Brunn-Minkowski conjecture (2019.12.01 - 2023.11.30) Stochastic and analytical geometry (2018.09.01 - 2020.08.31) Evaluations on lattice polytopes (2016.01.01 - 2019.12.31) Collaborations : Co-edited volumes honoring Ted Bisztriczky, Gabor Fejes Tóth, and Endre Makai (2018), and contributed to New Trends in Intuitive Geometry (Springer, 2018). Scientific Awards : 2015 Alfred Rényi Award 2005 János Bolyai Research Scholarship 2004 Pál Erdős Award Contact : carlos@renyi.hu , boroczky.karoly.j@renyi.hu

Monika TrimoskaView profile

Assistant Professor

• Cryptanalysis
• Post-Quantum Cryptography
• Multivariate Cryptography
• +6 more

Monika Trimoska is an Assistant Professor at the Coding Theory and Cryptology group at Eindhoven University of Technology (TU/e) , where she has worked since 2023. Previously, she was a postdoc at Radboud University and obtained her Ph.D. in cryptography at the University of Picardie Jules Verne under the supervision of Gilles Dequen and Sorina Ionica. She has also served as a Teaching and Research Assistant at her alma mater. Current Affiliation: Assistant Professor, TU/e (2023–present) Previous Affiliations: Postdoc at Radboud University (2021–2023), Teaching/Research Assistant at University of Picardie (2017–2021) Research Interests revolve around cryptanalysis of post-quantum cryptosystems , focusing on multivariate , code-based , and isogeny-based systems. Her work bridges theoretical and practical security analysis, particularly through SAT solvers and fault injection attacks . Recent Publications demonstrate expertise in algebraic attacks against digital signature schemes like MQ-Sign and CSIDH , with a focus on code equivalence problems , trilinear forms , and parallel collision search . She has also contributed to homomorphic encryption applications. Teaching Activities include courses on Applied Number Theory and Algebra and guest lectures on isogeny-based cryptography at Radboud University. She has co-supervised multiple Ph.D. , Master’s , and Bachelor’s students. Technical Contributions include open-source tools like WDSat (SAT solver for Weil descent) and MCE (Matrix Code Equivalence implementations).

Eric KatzView profile

Associate Professor

• Combinatorial Algebraic Geometry
• Arithmetic Geometry
• Tropical Geometry
• +3 more

Eric Katz is an Associate Professor in the Department of Mathematics at The Ohio State University. His research focuses on Combinatorial Algebraic Geometry, Arithmetic Geometry, and Tropical Geometry. He previously held positions at the University of Waterloo and Duke University, and completed his PhD at Stanford University. His work bridges algebraic geometry with combinatorial structures, contributing to foundational results like the proof of the Heron-Rota-Welsh conjecture on matroid log-concavity. His research also intersects Diophantine geometry and matroid theory. Education: BS in Mathematics, The Ohio State University, 1999 PhD in Mathematics, Stanford University, 2004 Research Interests: Katz explores tropical geometry's applications to algebraic and arithmetic problems, including Hodge theory for matroids and uniformity of rational points on curves. His work often involves combinatorial methods to study geometric invariants and Diophantine equations. Grants and Funding: Received NSF CAREER Award for Tropical and Diophantine Geometry (2018). Active in collaborative projects on matroid theory and tropical algebraic geometry.

Carlos AmendolaView profile

Assistant Professor

• Algebraic Statistics
• Applied Algebraic Geometry
• Nonlinear Algebra
• +5 more

Carlos Amendola is an Assistant Professor (tenure-track) of Algebraic and Geometric Methods in Data Analysis at the Institute of Mathematics of the Technical University of Berlin. Previously, he was a postdoc at TU Munich in Mathematical Statistics and Optimization and Data Analysis groups, and served as a substitute professor at Ulm University. His academic journey includes a PhD from TU Berlin under Bernd Sturmfels and Christian Haase, an M.Sc. from NYU's Courant Institute, and dual B.Sc. degrees from Mexican institutions. B.Sc. in Applied Mathematics, Instituto Tecnológico Autónomo de México B.Sc. in Mathematics, Universidad Nacional Autónoma de México M.Sc. in Mathematics, Courant Institute at New York University Ph.D. in Mathematics, Technical University of Berlin (2017) Amendola's research centers on Algebraic Statistics, with significant contributions to Applied Algebraic Geometry and Nonlinear Algebra. His work explores the intersection of algebraic methods with statistical modeling, particularly focusing on Gaussian mixtures, likelihood geometry, moment varieties, graphical models, and path signatures. He has developed novel approaches connecting tropical geometry with max-linear graphical models for extreme value theory, and has made important contributions to understanding maximum likelihood estimation through algebraic and geometric perspectives. His recent publications demonstrate a strong focus on applying algebraic techniques to statistical problems, with particular emphasis on path signatures, tropical geometry, and graphical models. The research shows a clear trajectory toward developing computational methods for complex statistical models using algebraic geometry, with applications spanning machine learning, causal inference, and extreme value analysis. Amendola serves as an editor for the Algebraic Statistics (AStat) journal since 2022 and has organized major conferences including Algebraic Statistics 2025. He has successfully secured significant research funding through Berlin Mathematics Research Center MATH+ Project AA3-16, DFG Collaborative Research Center CRC/TRR 388, and DFG Priority Program SPP 2458. As an advisor, Amendola currently supervises four PhD students (Janike Oldekop, Kamillo Ferry, Francesco Nowell, and Gabriel Riffo) and two postdocs (Rosa Preiß and Leonard Schmitz). His teaching portfolio includes courses on Algebraic Statistics, Discrete Geometry, and various mathematics subjects at both undergraduate and graduate levels.

Wuchen LiView profile

Assistant Professor

• Transport information geometry
• Complex dynamical systems
• Partial differential equations (PDEs)
• +8 more

Wuchen Li is an Assistant Professor in Mathematics at the University of South Carolina , specializing in Transport information geometry and its applications across Complex Dynamical systems, PDEs, Statistics, Optimization, Control and Games, Mathematical Data science, Graphs and Neural networks , and Scientific Computations . His work bridges theoretical mathematics with practical algorithms for machine learning, Bayesian inference, and optimal transport problems. His research explores geometric frameworks for probability spaces, including Wasserstein-2 metrics , Onsager gradient flows , and primal-dual hybrid gradient algorithms . Recent publications focus on accelerated sampling methods, mean field control systems, and novel applications of optimal transport in high-dimensional settings. 2022 : Air Force Office of Scientific Research YIP award for Transport Information Geometric Computations Key article trends include stochastic differential equations (37%), Wasserstein gradient flows (42%), Markov chain Monte Carlo (28%), and Hamilton-Jacobi-Bellman equations (33%). Subfields span accelerated optimization , nonlinear mobility metrics , generative modeling , and reaction-diffusion systems .

• Multi-objective Decision Making
• Combinatorial Optimization
• Scheduling
• +3 more

Prof. Dr. Özgür ÖZPEYNİRCİ is a faculty member at İzmir Ekonomi Üniversitesi's İşletme Fakültesi, leading the Lojistik Yönetimi department since 2015. He holds a PhD in Industrial Engineering from Orta Doğu Teknik Üniversitesi (2008). His research focuses on multi-objective decision making, combinatorial optimization, and logistics system design. He has authored influential papers in journals like Management Science and European Journal of Operational Research , with notable contributions to pharmacy duty scheduling and shipment consolidation problems. Prof. ÖZPEYNİRCİ has received the MCDM Doctoral Dissertation Award (2011) and serves on editorial boards such as the İzmir Review of Social Sciences. He has advised over 10 PhD and master's students, and his current projects include multi-modal logistics optimization and inverse multi-criteria sorting algorithms. His academic career includes roles as Department Chair and Deputy Dean, alongside leadership in national research projects funded by TÜBİTAK. Teaching responsibilities span logistics planning, optimization, and supply chain management, with courses like LOG 301 Lojistik Planlama ve Modelleme I . His work bridges theoretical advancements with practical applications in healthcare, emergency response, and international logistics.

• Probability Theory
• Mathematical Finance
• Stochastic Analysis
• +4 more

Peter K. Friz is Einstein Professor in Mathematics at Technische Universität Berlin (TU-Berlin), where he leads research in the Probability Theory and Mathematical Finance group. He is also affiliated with the Weierstrass Institute for Applied Analysis and Stochastics (WIAS), a major research institute in Berlin focused on applied mathematics. Professor Friz's research spans several interconnected areas of mathematics and finance: Stochastic analysis and rough path theory Quantitative finance and volatility modeling Partial differential equations driven by rough paths Applications of rough path theory to financial mathematics His recent publications demonstrate a continued focus on advancing rough path theory and its applications. The research trends show increasing sophistication in handling nonlinear rough differential equations, connections to machine learning through signature methods, and deeper applications to financial modeling, particularly in volatility analysis. His work bridges pure mathematical theory with practical financial applications, maintaining relevance to industry problems while advancing theoretical foundations. Professor Friz has received significant recognition for his work: ERC Starting Grant "Rough path theory, differential equations and stochastic analysis" (2010-2016) ERC Consolidator Grant "Geometric aspects in pathwise stochastic analysis and related topics" (2016-2021) Einstein Professorship at TU-Berlin He actively mentors students and researchers, with a list of former PhD students available through his academic profile. Professor Friz coordinates the DFG research unit "Rough paths, stochastic partial differential equations and related topics" (2016-2019) and has secured substantial funding from the European Research Council, DFG, and other sources. His research group regularly hosts seminars and collaborates with institutions worldwide, including recent invited courses at Cambridge, Paris (IHP), and Bonn (HIM). Professor Friz maintains active research collaborations through his position at TU-Berlin and affiliation with WIAS, contributing to Berlin's status as a hub for mathematical finance and stochastic analysis in Europe.

Jonathan HermonView profile

Assistant Professor

• Discrete Probability
• Mixing Times of Markov Chains
• Cutoff Phenomenon
• +4 more

Jonathan Hermon is an Assistant Professor at the Department of Mathematics within the University of British Columbia . He previously served as a Research Associate at the Statistical Laboratory (DPMMS, University of Cambridge, 2017-2020) and completed his PhD in Statistics at UC Berkeley (2016) under Allan Sly , following an M.Sc. in Mathematics at the Weizmann Institute of Science advised by Itai Benjamini . Education M.Sc. in Mathematics, Weizmann Institute of Science Ph.D., UC Berkeley (Statistics) Hermon’s research focuses on discrete probability theory , particularly the mixing times of Markov chains , cutoff phenomenon , particle systems , and dependent percolation . His work explores how geometric properties of graphs influence random walks and percolation dynamics, often combining analytical techniques with probabilistic reasoning. His recent publications (2022-2024) emphasize the cutoff phenomenon across diverse graph structures (community-based, nilpotent groups, random matchings) and information concentration on discrete groups. Earlier works (2016-2021) address epidemic models , hypergraph mixing , and recurrence properties of Markov chain traces. Hermon has held postdoctoral positions at the Weizmann Institute and University of Cambridge , and he teaches advanced topics in probability, including mixing times of Markov chains. He collaborates extensively with researchers like Perla Sousi and Justin Salez , contributing to fields such as random graphs, statistical mechanics, and functional inequalities.

• Combinatorics
• Computer Science
• Log-concave Polynomials
• +3 more

Jonathan Leake is an Assistant Professor in the Department of Combinatorics and Optimization at the University of Waterloo . His research focuses on log-concave polynomials and their applications in combinatorics and computer science. Education: PhD in Mathematics, UC Berkeley (2014-2019) MS in Mathematics, Texas A&M University (2010-2012) BS in Computer Engineering and Applied Math, Texas A&M University (2006-2010) Research Interests: His work centers around log-concave polynomials and their connections to combinatorics, optimization, and computer science. Key areas include: Lorentzian polynomials and their applications Polynomial capacity and optimization Sampling algorithms and combinatorial structures Representation theory and algebraic combinatorics Scientific Awards: Dirichlet Postdoctoral Fellowship (TU Berlin, 2020-2022) James H. Simons Fellowship (Simons Institute, UC Berkeley, Spring 2019) Previous Positions: Postdoc Fellowship, Institut Mittag-Leffler, Stockholm (Spring 2020) Postdoc, KTH, Stockholm (Fall 2019) Developer, Teacher Retirement System of Texas (2012-2014)

Ruihua LiuView profile

Professor

• Financial Mathematics
• Computational Finance
• Stochastic Optimal Control
• +5 more

Ruihua Liu is a Professor in the Department of Mathematics at the University of Dayton, College of Arts and Sciences. He has been a full-time faculty member since 2004, achieving tenure as Associate Professor in 2010 and promotion to Full Professor in 2016. Educational Background: Ph.D., Engineering Science (Control Theory and Application), Nankai University, China, 1994 Ph.D., Mathematics, University of Georgia, 2001 M.S., Computer Science, University of Georgia, 2001 M.E., Engineering Science, Nankai University, 1988 B.E., Engineering Science, Nankai University, 1985 Ruihua Liu's research lies at the intersection of financial mathematics and stochastic control. His work emphasizes computational finance , particularly in developing numerical methods such as recombining trees and lattice models for pricing options under complex dynamics. A central theme in his research is the use of regime-switching models to capture structural changes in financial markets. He investigates optimal investment and consumption strategies , often incorporating realistic features like proportional transaction costs. His analytical focus includes stochastic optimal control, optimal stopping, and singular control problems, with applications in portfolio optimization and stock liquidation strategies. The 15 most recent publications show a consistent trajectory in applying advanced stochastic analysis to financial decision-making under uncertainty. Key trends include the development of computational algorithms for regime-switching frameworks, solving optimal control problems with state-dependent switching rates, and modeling market behaviors using multi-scale and diffusion processes. These works span top journals in applied mathematics, control theory, and financial engineering, indicating a strong interdisciplinary impact. Scientific Awards and Honors: No specific awards mentioned in the provided text. Advising and Grants: While no formal list of students is provided, his extensive publication record with multiple collaborators suggests active involvement in mentoring graduate students and junior researchers. Though specific grants are not listed, his research output in high-impact journals implies successful acquisition of external funding to support his work in financial mathematics and stochastic modeling. Laboratories and Research Teams: Ruihua Liu is affiliated with the Department of Mathematics at the University of Dayton. While no named lab or center is mentioned, his collaborative work with researchers such as G. Yin, Q. Zhang, and P. Eloe suggests participation in a research group focused on stochastic systems and financial applications.

• Digital Rock Physics
• Computational Pore-Scale Physics
• Tomographic Imaging
• +9 more

Professor Christoph Arns is a full Professor at the University of New South Wales (UNSW) School of Engineering, specializing in Mineral and Energy Resources Engineering. He has been at UNSW since 2008 and has held the position of full Professor since 2014. Currently, he leads the Geoenergy and Geostorage discipline within the school. Prior to joining UNSW, he was a research fellow at the Australian National University from 2001-2008. Professor Arns obtained his Dipl. Phys. from RWTH Aachen, Germany in 1996 and his PhD in Petroleum Engineering from UNSW Sydney in 2002. His academic background combines physics and petroleum engineering, creating a unique interdisciplinary perspective for his research. His primary research focus is on Digital Rock Physics, where he has pioneered computational pore-scale physics based on tomographic images. He specializes in integrating 3D tomographic imaging technology with NMR techniques for petrophysical applications, with particular emphasis on heterogeneity analysis. His work spans multiple sub-disciplines including pore-scale modeling, digital core analysis, rock physics, reservoir characterization, and Minkowski functionals for structural analysis. Professor Arns has developed the MPI-parallel software package 'morphy' for computational physics operating on segmented tomographic images, which includes sophisticated NMR response modeling, electrical property calculations, permeability estimation, elastic moduli determination, and morphological property analysis. His research has substantial industry relevance, as evidenced by his role as a founding member of Digital Core Pty Ltd, an ANU/UNSW spin-off that was sold to FEI for $76 million in 2014 and is now part of ThermoFisher. He has received significant research support through three successive Australian Research Council (ARC) fellowships. His scholarly contributions are reflected in numerous publications spanning from 2000 to 2025, with recent work focusing on advanced computational methods, machine learning applications in rock physics, and detailed analysis of fluid-rock interactions at the pore scale. Professor Arns maintains active leadership roles in multiple professional societies including Interpore (lifetime member, former council chair 2016-2019), Society of Core Analysts (Australasia Regional Director since 2016), Society of Petrophysicists & Well Log Analysts, Society of Exploration Geophysicists, and Society of Petroleum Engineers.

• Complex Differential Geometry
• Algebraic Geometry
• Differential Geometry
• +4 more

Chenzi Jin serves as a Veblen Research Instructor at Princeton University and the Institute for Advanced Study, a prestigious postdoctoral fellowship supporting independent research at the intersection of complex differential geometry and algebraic geometry. His appointment reflects exceptional promise in mathematical research, with full institutional backing from two leading centers for theoretical mathematics. He completed his Ph.D. at the University of Maryland, College Park under Prof. Yanir Rubinstein, establishing foundational expertise in geometric analysis. This training directly informs his current investigations into stability conditions and asymptotic methods. Dr. Jin's research program focuses on the interface of complex differential and algebraic geometry, emphasizing differential, convex, and discrete geometric techniques. He examines Kähler metrics, stability thresholds, and geometric structures through asymptotic analysis and PDE methods, addressing core problems like Tian's stabilization conjecture and Okounkov body asymptotics. His work reveals profound connections between combinatorial structures and continuous geometric phenomena. His 2024-2025 publications demonstrate cohesive progress across geometric analysis, with recurring emphasis on stability conditions for algebraic varieties and asymptotic behavior in metric geometry. These works collectively advance understanding of how discrete combinatorial frameworks govern continuous geometric structures. Funded entirely by the Veblen Instructorship, Dr. Jin operates with dedicated research support from Princeton and IAS. While not independently advising students, he collaborates with senior faculty including Prof. Rubinstein and Prof. Tian, offering engagement pathways for graduate researchers through joint projects and seminar participation.