Mathematical and Statistical Modelling (PhD)

Mathematical and statistical modelling is essential in a wide range of industries. New types of highly qualified specialists are needed to develop, analyze and apply modern quantitative approaches to a variety of issues of high complexity. Our interdisciplinary PhD program will help you become an independent researcher capable of succeeding in careers in research, industry, teaching, or government.

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Interdisciplinary approach with critical areas of application.

Projects tackle ongoing scientific questions.

Guided by professors with national and international reputations.

Program Details

Overview

Laurier’s PhD in Mathematical and Statistical Modelling is an interdisciplinary program with strength in complex systems modelling, financial mathematics and statistics. The program is lead by faculty with national and international reputations in a diverse set of cross-disciplinary research.

In this program you will:

  • Develop expertise in using the tools of mathematical and statistical modelling;
  • Contribute in creative and innovative ways to solving complex interdisciplinary problems;
  • Carry out independent research; and
  • Learn to communicate effectively with researchers in other disciplines.

Structure

This full-time program is to be completed in four years. Students engage in a specific area of research under the supervision of one or more faculty members.

Students start working on a research project in year one to become familiar with the area of research and develop a research proposal by year two. Typically, students complete two terms of coursework, followed by a comprehensive examination.

All students must attend an Interdisciplinary Seminar in Applied Modelling and participate in a Research Modelling Symposium.

Research

Students perform research on problems that come from diverse application domains. The unifying themes for mathematical and statistical modelling are the main research domains:

  • Financial Mathematics
  • Complex Systems Modelling
  • Statistics and Data Analysis

Students may work on research that spans more than one domain.

MS2Discovery Institute

The Interdisciplinary Research Institute for Mathematical and Statistical Modelling in Scientific Discovery, Innovation and Sustainability (MS2Discovery) connects researchers working in mathematical and statistical modelling in various disciplines – from natural sciences and technology, finance, business and economics, and social sciences.

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"Immerse yourself in all Laurier has to offer while completing your graduate education. Enjoy the journey – remember to have fun too!"

Paula C. Fletcher, associate dean, Faculty of Graduate and Postdoctoral Studies

Admissions

Take the first step in your graduate education and apply to one of our graduate programs. Follow our three-step admission process — we’ll walk you through how to apply and prepare for your first day as a graduate student.

  • Start: Fall (September) or Winter (January)
  • Format: Full-time or part-time
  • Application opens:
    • January intake: Nov. 16 (domestic applicants only)
    • September intake: March 31 (international applicants) or July 31 (domestic applicants)
  • Application deadline:
    • January intake: Nov. 15 (domestic applicants only)
    • September intake: Jan. 15 (first consideration), March 30 (international applicants) or July 30 (domestic applicants)

Your Next Steps

Questions? Contact Xu (Sunny) Wang, graduate academic coordinator, at mathgradprogram@wlu.ca or 548.889.3745.

Waterloo Campus

This program is available on Laurier's Waterloo campus.

Laurier Waterloo is where tradition, innovation and incredible school spirit collide.

The Waterloo campus spans one large city block, ensuring you’re close to your classes, favourite study spots, student services and favourite coffee shops. Laurier is a leading force in research among Canadian universities, and many of our research centres and institutes are housed in Waterloo.

We offer the guidance and support you need to thrive academically and personally throughout your degree.

Discover Laurier Waterloo for yourself: 

Tuition and Funding

Regardless of the type of graduate degree program you intend to pursue, financial planning is important. At Laurier, we want to provide you with as much information as possible about a variety of scholarship and funding opportunities and equip you with the skills to manage your finances effectively in the years to come.

Laurier welcomes international applicants to all of our doctoral programs. International students who have confirmed funding from a third-party, such as their employer or a scholarship program in their home country, will be considered for admission. Learn more about admission requirements for international applicants.

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Your Path to Post-Degree Success

ASPIRE is Laurier's professional skills development training program for graduate students.

The program helps you craft an individualized, extracurricular learning plan tailored to your professional journey and entry to the workplace.

Faculty

In most cases, a student in this program working on a specific application-oriented project will have two co-supervisors, one with expertise in mathematical and statistical sciences and the other with specialized expertise in the project-specific domain application involving modelling.

Devan Becker
Assistant Professor

  • Bayesian statistics
  • Spatial statistics
  • Unsupervised machine learning

Phelim Boyle
Professor

  • Hedge funds
  • Structured products
  • Investments
  • Ponzi schemes

Kathie Cameron
Professor

  • Graph algorithms
  • Polytime combinatorial optimization
  • Graph theory

Giuseppe (Joe) Campolieti
Associate Professor

  • Applied mathematics
  • Mathematical finance and physics
  • Pricing and hedging of financial derivatives; option pricing and model calibration
  • Path-integral methods; simulation (Monte Carlo) methods

Wing Chan
Associate Professor

  • Econometrics
  • Derivatives
  • Risk management
  • Asset pricing models

Yuming Chen
Professor

  • Dynamical systems
  • Functional differential equations
  • Mathematical biology

Ross Cressman
Professor Emeritus

  • Game theory
  • Dynamical systems
  • Rational behaviour
  • Mathematical biology

Maria Gallego
Associate Professor

  • Public economics
  • Political economy
  • Elections
  • Legislative bargaining

Shohini Ghose
Professor

  • Quantum computing
  • Quantum communication
  • Classical and quantum chaos
  • Equity, diversity and inclusion in science

Angèle Foley
Professor

  • Combinatorics
  • Algorithms
  • Optimization

Ian Hamilton
Professor

  • Gold nanostructures and semiconductor nanocrystals
  • Quantum and classical mechanics
  • Chemical bonding and reactivity

Chin Hoang
Professor

  • Theoretical computer science
  • Graph algorithms
  • Graph theory
  • Discrete mathematics

Shengda Hu
Professor

  • Algebraic geometry
  • Symplectic topology
  • Generalized geometry

Sapna Isotupa
Professor

  • Inventory control
  • Queueing systems
  • Workforce management

Madhu Kalimipalli
Professor

  • Modeling Volatility
  • Derivatives
  • Bond markets
  • Market microstructure

Alexei Kaltchenko
Associate Professor

  • Information theory
  • Quantum information theory and quantum computing
  • Data compression

Marc Kilgour
Professor

  • Multiple-person, multiple-objective decision analysis including game theory
  • Multiple-criteria decision analysis
  • International strategy
  • Environment management

Ilias Kotsireas
Professor

  • Symbolic computation
  • Combinatorial designs
  • High-performance computing

Y. George Lai
Professor

  • Computational finance/Monte Carlo and quasi-Monte Carlo methods and applications
  • Stochastic analysis with applications in finance and insurance
  • Portfolio optimization

Roman Makarov
Professor

  • Mathematical finance
  • Statistical theory and modelling
  • Numerical analysis

Philip Marsh
Professor

  • Cold regions hydrology
  • Snow and permafrost hydrology
  • Climate change and hydrologic modelling
  • Hydrology of Arctic deltas

Connell McCluskey
Professor

  • Mathematical epidemiology
  • Lyapunov methods
  • Global stability

Roderick Melnik
Professor

  • Mathematical modelling in Applied Sciences and Technologies
  • Applied and Computational Mathematics
  • Low dimensional nanostructures and coupled models
  • Partial differential equations and numerical methods

Adam Metzler
Associate Professor

  • Applied probability
  • Quantitative finance
  • Credit risk

Gabriel Moreno-Hagelsieb
Professor

  • Genomics
  • Metagenomics
  • gene regulation in prokaryotes
  • functional/comparative genomics

Michael Pavlin
Associate Professor

  • Business analytics
  • Pricing and contract theory
  • Structural econometrics
  • Energy markets, services, healthcare

Stephen Perry
Professor

  • Biomechanics
  • Neurophysiology
  • Dynamic Balance Control
  • Footwear and Orthotics

R. Mark Reesor
Professor

  • Applied probability and statistics
  • Quantitative finance
  • Risk measurement and management

Steven Roberts
Associate Professor

  • Geo-computation
  • Optimization for spatial problems
  • Spatial analysis

Colin Robertson
Associate Professor

  • Spatial-temporal analysis
  • Spatial modelling at the animal/human health interface
  • Citizen science
  • Landscape scale spatial pattern analysis

Manuele Santoprete
Professor

  • Applied mathematics
  • Celestial mechanics
  • Chaotic dynamics
  • Geometric mechanics

Ketan Shankardass
Associate Professor

  • Health equity
  • Social epidemiology
  • Chronic stress
  • Environmental health

Andriy Shkilko
Associate Professor

  • Equity and option market structure
  • Market regulation
  • High-frequency and algorithmic trading
  • Short selling

David Soave
Associate Professor

  • Statistical genetics
  • Predictive modelling for health outcomes
  • Design and analysis of two-phase studies

Cristina Stoica
Professor

  • Mathematics of classical mechanics, n-body problems in particular
  • Continuous and discrete symmetries in dynamics
  • Geometric mechanics
  • Data science, in particular functional and shape data analysis

Xu (Sunny) Wang
Professor
Graduate Coordinator

  • Statistical learning and data mining in drug discovery
  • Mining business and economic data
  • Applied statistics
  • Industrial statistics

Marek Wartak
Professor

  • Simulations of photonic devices
  • Computational photonics
  • Plasmonics

Zilin Wang
Associate Professor

  • Survey sampling theory
  • Resampling techniques
  • Multilevel models
  • Nonparametric regression techniques

Chester Weatherby
Assistant Professor

  • Number theory
  • Transcendence/algebraic independence
  • Baker’s theory on linear forms in logarithms
  • Special values

Kaiming Zhao
Professor

  • Lie algebras
  • Representation theory
  • Division algebra and linear algebra