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Lorenzo PellisView profile

Research Fellow

• Infectious Disease Epidemiology
• Mathematical Modeling
• Epidemiology
• +6 more

Dr. Lorenzo Pellis is a Research Fellow at the University of Manchester, holding the Sir Henry Dale Fellowship, and a Visiting Fellow at the University of Warwick's Mathematics Institute and Zeeman Institute. He is also an Honorary Research Associate at the Medical Research Council (MRC) Centre for Outbreak Analysis and Modelling, within the Department of Infectious Disease Epidemiology at Imperial College London. His research bridges applied mathematics and epidemiology, focusing on developing models that inform public health decisions. He earned his Doctoral degree in Mathematical Biology from Imperial College London in 2009, with a dissertation titled Mathematical models for emerging infections in socially structured populations: the presence of households and other social structures II: Comparisons and implications for vaccination . Pellis's research interests include the development of novel deterministic and stochastic methods to model infection spread dynamics, particularly in human populations with complex social structures. He focuses on directly transmitted infections and the impact of co-infections on epidemiological and evolutionary outcomes. His work emphasizes multi-scale models integrating within-host and between-host processes, with applications to antimicrobial resistance, HIV-TB co-infections, and respiratory syncytial virus (RSV) transmission in Kenya. He also explores model comparison techniques to assess the utility of simple models in public health decision-making. His recent articles collectively explore mathematical modeling in infectious disease dynamics, with a focus on network-based approaches, multi-strain infections, and the integration of within-host and between-host processes. They highlight challenges in metapopulation and network models, as well as the evolutionary dynamics of HIV and TB co-infections. Sir Henry Dale Fellow , funded by the Wellcome Trust and Royal Society His grants include support for his Sir Henry Dale Fellowship, which funds research on co-infections and multi-scale models. He collaborates with Prof. Matt Keeling and Dr. Thomas House at Warwick and Prof. James Nokes on RSV studies in Kenya. His work also involves improving epidemic dynamics approximation methods on networks. He is affiliated with the applied Mathematics group at Manchester's School of Mathematics, the Zeeman Institute at Warwick, and the MRC Centre at Imperial College. His interdisciplinary collaborations span institutions and disciplines, including applied mathematics, epidemiology, and public health.

• Probability Theory
• Number Theory
• Harmonic Analysis
• +3 more

Dr. Bence Borda is an Assistant Professor in Mathematics at the University of Sussex, affiliated with the School of Mathematical and Physical Sciences. He holds a PhD from Rutgers University (2016), advised by József Beck, and has held postdoctoral positions at the Alfréd Rényi Institute of Mathematics (2017–2019) and Graz University of Technology (2019–2024), supported by a Lise Meitner Fellowship (FWF) from 2022–2024. PhD: Mathematics, Rutgers University (2016) His research lies at the intersection of probabilistic number theory , Diophantine approximation , random walks on groups , and harmonic analysis , with a focus on equidistribution theory and discrepancy measures. Recent publications explore limit laws for cotangent sums, quantum modular forms, and stochastic behavior in number-theoretic sequences. Key trends in his work include the use of Wasserstein metrics for quantifying equidistribution, random matrix eigenvalues in compact groups, and determinantal point processes on geometric manifolds. His contributions span both theoretical analysis and computational applications. Scientific Awards Lise Meitner Fellowship (FWF), 2022–2024 He has supervised teaching at institutions including Rutgers University and Budapest Semesters in Mathematics, covering calculus, analysis, and graduate-level courses. He co-organized the 2025 Analysis and Optimal Transport Workshop at Sussex and actively participates in international conferences.

Mark PollicottView profile

Professor

• Thermodynamic Formalism
• Ergodic Theory
• Dynamical Systems
• +4 more

Mark Pollicott is a Professor of Mathematics at the University of Warwick, where he has held positions since 1992 and 2005. He previously served at Edinburgh, Porto, and Manchester Universities, including a Fielden Chair. His research focuses on Thermodynamic Formalism, Ergodic Theory, and Dynamical Systems, with applications to geometry, number theory, and fractal analysis. Pollicott earned his BSc (1981) and PhD (1984) in Mathematics and Physics from Warwick, under the supervision of William Parry. He has held prestigious fellowships, including Royal Society and ERC grants, and organized major programs at the Newton Institute, CIB-Lausanne, and ICERM. He serves on editorial boards for journals like Nonlinearity and Journal of Fractal Geometry . His research explores topics such as fractal dimensions, geodesic flows, and validated numerics. Notable contributions include studies on the Hausdorff dimension of Cantor sets and Bernoulli convolutions. He has supervised 19 PhD students and mentored 18 postdoctoral researchers. Recent grants include EPSRC funding for computational ergodic theory and dynamical zeta functions. His work bridges pure mathematics with applications in geometry, analysis, and number theory. Awards: ERC Advanced Grant, EPSRC Leadership Fellowship, Royal Society Fellowships, Jean Morlet Chair Grants: EPSRC (2019-2025, 2026-2030), ERC (2019-2025) Collaborations: Co-organized programs on Thermodynamic Formalism and Dynamics at CIRM and Warwick

• Number Theory
• Algebraic Geometry
• Modular Forms
• +5 more

Dr. Helena Verrill is an Assistant Professor at the Department of Mathematics, University of Warwick, focusing on teaching and outreach. Her research interests span Number Theory, Algebraic Geometry, Combinatorial Game Theory, and the Mathematics of Origami, with applications in generative art. She actively mentors students through third-year essays, research projects, and outreach initiatives like the Royal Institute Masterclasses. Her research explores modular forms, computational algebra, and arithmetic geometry, with notable contributions to ℓ-adic representations and noncongruence cuspforms. She bridges pure mathematics with artistic expression through origami tessellations and fractal patterns. Notable works include studies on Fano plane automorphisms and Harter-Heighway dragon curves. Her publications span journals like the *Proceedings of the American Mathematical Society* and *Journal of Number Theory*, alongside creative outputs in *Generative Art* and *Bridges Conferences*. She maintains a personal homepage with resources for mathematical art and education.

Oliver JohnsonView profile

Professor

• Information Theory
• Probability
• Statistics
• +3 more

Professor Oliver Johnson is a faculty member at the School of Mathematics, University of Bristol, UK, where he serves as Head of School and holds the Professor of Information Theory position. His research bridges information theory, probability, and statistics, focusing on entropy convergence, group testing, and fundamental limits in data analysis. Current PhD students: Kieran Morris, Conor Crilly Ex-PhD students: Matt Aldridge, Leonardo Baldassini, Dan Cowley, Vaia Kalokidou, Tom Kealy, Jennifer Chakravarty, Zichen Gui, Chrys Paschou Ex-postdoc: Erwan Hillion His work includes ORCiD profile and collaborations across information theory, cybersecurity, and ecological modeling.

Ciara RaffertyView profile

Senior Lecturer

• Applied Cryptography
• Post-Quantum Cryptography
• Homomorphic Encryption
• +4 more

Dr. Ciara Rafferty is a Senior Lecturer at Queen's University Belfast's School of Electronics, Electrical Engineering and Computer Science, affiliated with the Centre for Secure Information Technologies. She leads research in advanced cryptography, focusing on post-quantum systems, homomorphic encryption, and hardware acceleration. Her work includes quantum-safe cryptography projects like the UK Quantum Communications Hub and AQuASeC (Innovate UK). She co-teaches CSC2056 - Systems Security and Cryptography and actively supervises PhD students. Dr. Rafferty is a Senior Member of IEEE and an EPSRC SPRITE+ Expert Fellow. Research Interests: Homomorphic Encryption Post-Quantum Cryptography Cryptographic Hardware Architectures Privacy-Preserving Technologies Side-Channel Attack Mitigation Key Projects: UK Quantum Communications Hub (Phase 2) SAFEcrypto (H2020 Project) AQuASeC (Toshiba Europe-funded) SEQURED (Rolls Royce-funded) Awards: Senior Member of IEEE EPSRC SPRITE+ Expert Fellow Advising & Grants: PhD Supervision: Shabnam K (Secure Cloud Computation) Funding: EPSRC, Innovate UK, Industry Partners Lab/Teams: Centre for Secure Information Technologies (CSIT), collaborating on hardware-accelerated cryptography and quantum-safe systems.

• Scientific Computing
• GPU Computing
• Signal Processing
• +5 more

Professor Wes Armour is a Professor of Scientific Computing at the University of Oxford and serves as the Associate Head of Department for Research in the Department of Engineering Science. He previously directed the Oxford e-Research Centre, an interdisciplinary research center within the Engineering Science Department. With over £31 million secured as PI or Co-I, his work spans supercomputing, signal processing, machine learning, computational fluid dynamics, and protein crystallography. Professor Armour's research focuses on extracting science from data through fundamental challenges in modeling, simulation, and data processing. His work draws from numerical analysis, signal processing, and machine learning to develop technologies enabling future scientific discoveries, particularly for the Square Kilometre Array (SKA) telescope. Key interests include GPU computing, high performance computing, and machine learning applications across diverse domains from radio astronomy to finance. As Director and Principal Investigator of JADE and JADE2, a 700-GPU machine, he established the UK's first national High Performance Computer facility dedicated to advancing Artificial Intelligence and Machine Learning. His research group has pioneered GPU applications across multiple fields, including Square Kilometre Array data processing, protein crystallography, and graphene simulations. Current projects span energy-efficient machine learning, stock price prediction in finance, prime number prediction in cryptography, and multi-modal CCTV data analysis. Professor Armour has been instrumental in developing real-time signal processing techniques for astronomical observations, including the ARTEMIS system for millisecond radio transient detection. His publications demonstrate consistent innovation in GPU-accelerated computing dating back to early work in 2008 on accelerating conjugate gradient routines for electron transport in graphene.

Julia WolfView profile

Professor

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

Julia Wolf is a Professor of Pure Mathematics at the University of Cambridge, affiliated with the Department of Pure Mathematics and Mathematical Statistics (DPMMS) and Trinity College. Her research focuses on arithmetic combinatorics, harmonic analysis, and analytic number theory, with interdisciplinary connections to model theory, discrete geometry, and theoretical computer science. She holds an EPSRC Open Fellowship and has organized events like the Warwick-Oxbridge-Manchester-Bristol-London (WOMBL) meetings. Wolf teaches advanced courses such as 'Higher-Order Uniformity' and 'Analytic Number Theory,' emphasizing structure and applications. Her work bridges combinatorial, analytic, and algebraic techniques, addressing problems like polynomial configurations in primes, extremal hypergraph theory, and Ramsey multiplicity. Recent research includes structural stability in finite abelian groups and applications of model theory to additive combinatorics. Wolf actively promotes open-access publishing and has mentored numerous postdoctoral researchers and students through initiatives like the Philippa Fawcett Internship Programme. She also contributes to academic equity efforts, such as gender-inclusive hiring in mathematics. Professional activities include editorial roles, conference organization (e.g., the Simons Institute's Pseudorandomness program), and leadership in collaborative projects like the 'Combinatorics Meets Model Theory' workshop. Her grants and fellowships underscore her contributions to advancing discrete mathematics and fostering international academic networks.

Davi De Castro SilvaView profile

Researcher

• Theoretical Computer Science
• Quantum Computing
• Combinatorics
• +5 more

Davi De Castro Silva is a Researcher at the University of Cambridge, affiliated with the Department of Computer Science and Technology and the Centre for Quantum Information and Foundations. His current work is advised by Tom Gur and Sergii Strelchuk. Previously, he was a postdoc at CWI (Amsterdam) in QuSoft, advised by Jop Briët, and completed his PhD in Applied Mathematics at the University of Cologne under Frank Vallentin and Fernando de Oliveira Filho. He holds a Master's from IMPA (Brazil) under Roberto Imbuzeiro Oliveira and a BSc/MSc from École Polytechnique (France). His research focuses on theoretical computer science, quantum computing, and combinatorics, with recent emphasis on quantum speedups' structural foundations, such as symmetry's role. Key areas include additive combinatorics (e.g., higher-order Fourier analysis), computational complexity (lower bounds), combinatorial optimization (semidefinite programming), and quantum information theory. Notable contributions include studies on quasirandomness in additive groups, quantum algorithms' limitations, and tensor analysis. His work bridges combinatorial methods with quantum computing, exploring algorithmic efficiency and structural properties. He has published in journals like Discrete Analysis , Combinatorica , and Forum of Mathematics, Sigma , with preprints addressing quantum computation symmetry, Goldreich-Levin algorithms, and hypergraph quasirandomness. His research highlights interdisciplinary approaches to foundational questions in computing and mathematics.

• Theoretical Computer Science
• Formal Program Verification
• Parametrised Algorithms
• +4 more

Amir Kafshdar Goharshady is an Associate Professor of Computer Science at the University of Oxford and a Tutorial Fellow at St Catherine's College. His research focuses on theoretical computer science, including formal program verification, parametrised algorithms, compiler optimisation, and blockchain technology. He leads the ALPACAS research group, which explores algorithms, logic, program analysis, cryptocurrencies, and smart contracts. Education: PhD in Theoretical Computer Science from IST Austria (supervised by Prof. Krishnendu Chatterjee), MSc in Computer Science (Systems) from Georgia Tech, and undergraduate studies in Maths and Computing at the Universities of London and Yazd. Prior to Oxford, he was an Assistant Professor at HKUST and maintains a visiting role at IIT Bombay. Research Interests: Formal methods for program verification Algorithmic efficiency in compiler optimisation Decentralized systems and blockchain applications Game-theoretic approaches to secure protocols Advising and Grants: Supervises over 20 PhD and Master’s students, with a rigorous selection process emphasizing problem-solving skills. Leads an international research group with multiple grants and collaborations. Former roles include organizing high school Olympiads and founding the Sundar STEM School in Pakistan. Labs/Teams: ALPACAS group, known for its work on smart contract optimization, blockchain security, and parametrised algorithm design. Regularly hosts visiting researchers such as Petr Novotný and Thomas Henzinger.

Natalia JurgaView profile

Lecturer

• Dynamical Systems
• Ergodic Theory
• Random Matrix Products
• +1 more

Natalia Jurga is a Lecturer in Pure Mathematics at the University of St Andrews School of Mathematics and Statistics. Her research explores dimension theory, dynamical systems, and fractal geometry, particularly through iterated function systems and ergodic methods. Funded by a Leverhulme Trust Early Career Fellowship, Jurga investigates the dimension theory of invariant sets, box dimension anomalies, and applications to parabolic fractals. She develops innovative approaches to compute Hausdorff dimensions and analyze chaotic systems. Awards & Grants: Leverhulme Trust Early Career Fellowship She advises PhD students including Luke Derry, Saeed Shaabanian, and Yunlong Xu, and serves as an editor for the Proceedings of the Royal Society of Edinburgh.

Tiantai DengView profile

Lecturer

• FPGA-based Hardware Acceleration
• Sparse Processing Architecture for CNN and GEMM
• Number System and Approximation Computing
• +3 more

Dr. Tiantai Deng is a Lecturer in Electronics and Digital Systems at the School of Electrical and Electronic Engineering , University of Sheffield (since 2021). His industrial background includes a senior research engineer role at HiSilicon/Huawei , where he focused on hardware architecture design for CNN, GEMM, and image/video processing on FPGAs/ASICs. Education: BEng, MSc, PhD Research interests span FPGA-based hardware acceleration , sparse processing architecture for CNN/GEMM, number system design , approximation computing , and high-level design environments . His work integrates algorithm-hardware co-optimization for efficiency in AI and mathematical computing. Recent publications emphasize neurodynamic systems for opinion modeling, parallel processing elements for ODE/AI acceleration, and low-power FPGA implementations for clustering/modulation classification. Earlier work addressed combustion dynamics and image processing pipelines. Contact: t.deng@sheffield.ac.uk | Office: G108, Sir Frederick Mappin Building, Sheffield S1 3JD | ORCID 0000-0003-4507-5746

Oliver M JenkinsonView profile

Professor

• Ergodic Theory
• Dynamical Systems
• Mathematical Analysis
• +3 more

Professor Oliver M Jenkinson is a faculty member at the School of Mathematical Sciences, Queen Mary University of London. He holds the academic rank of Professor of Mathematics and is affiliated with the Centre for Complex Systems. His research focuses on ergodic theory, dynamical systems, and related areas such as fractal geometry and statistical mechanics. Jenkinson has contributed to topics like Lyapunov exponents, invariant measures, and Hausdorff dimension estimation. His work spans theoretical and computational aspects of dynamical systems, including studies of transfer operators, spectral radii, and entropy optimization. Notable contributions include rigorous bounds on fractal dimensions, analysis of continued fractions, and investigations into ergodic optimization problems. He collaborates with institutions globally and maintains an active research profile with over 40 publications since 2001. Research trends in his articles emphasize interdisciplinary applications of ergodic theory, with recurring themes in mathematical physics and nonlinear dynamics. His papers often bridge pure mathematics with computational methods, addressing questions in chaos theory, measure theory, and operator spectra. Jenkinson’s work is supported by grants and collaborations, though specific funding details are not listed. He is associated with the Centre for Complex Systems, reflecting his focus on complex, multi-component systems in mathematics. No formal awards are mentioned in the provided texts, though his prolific publication record indicates significant scholarly impact.

Mark JerrumView profile

Professor

• Combinatorics
• Computational Complexity
• Theoretical Computer Science
• +7 more

Mark Jerrum is a Professor of Mathematics at Queen Mary University of London, part of the School of Mathematical Sciences. His research focuses on combinatorics, computational complexity, and stochastic processes, particularly in the design and analysis of randomized algorithms. He explores the mixing times of Markov chains and computational complexity of counting problems, including partition functions and generating functions, often motivated by statistical physics, constraint satisfaction, and graph polynomials. Notable grants include an EPSRC-funded project on Sampling in Hereditary Classes (EP/S016694/1, 2019–2023). He has contributed to teaching, serving as module organiser for MTH4213 (Numbers, Sets and Functions) in 2023–24. His work bridges theoretical computer science and discrete mathematics, with applications in algorithmic design and probabilistic analysis. Research highlights include advancements in perfect sampling algorithms, approximation algorithms for counting problems, and foundational work on the interplay between statistical physics models and computational complexity. He is affiliated with the Centre for Combinatorics, Algebra and Number Theory, reflecting his interdisciplinary approach to combinatorial and algorithmic challenges.

John BissellView profile

Senior Lecturer

• Thermal Convection
• Hydrodynamics
• Magnetized Fluids
• +8 more

Dr. John Bissell is a Senior Lecturer in Engineering Mathematics at the University of York. He holds a Ph.D. from Imperial College London and an M.A. from the University of Cambridge. Previously, he held roles including Senior Teaching Fellow at the University of Warwick (2018-2019), Teaching Fellow at the University of Bath (2015-2017), and Research Associate at the University of Durham (2012-2015). His research focuses on thermal convection, buoyancy-driven instabilities, nonlinear heat flow, plasma transport, and dynamical systems analysis. He also explores applications of mathematical models in ecological and sociological systems. Notable contributions include studies on laser-produced plasmas, numerical methods for sparse matrices, and bifurcation theory in mechanical systems. Recent publications emphasize pedagogical innovations in physics education, such as pendulum-based experiments for teaching mechanics, and analytical proofs for foundational mathematical concepts. His work bridges theoretical mathematics with practical engineering applications, including additive manufacturing simulations and grid electricity transmission analysis. Bissell has co-edited Tipping Points: Modelling Social Problems and Health (Wiley, 2015) and contributed chapters on conformity bias in social dynamics and dimensional analysis in applied sciences. His research has been published in Proceedings of the Royal Society A , Physical Review Letters , and Physics of Plasmas .