About Me

I was born in Australia, and studied Pure Mathematics and Philosophy for my undergraduate degree at the University of New South Wales. I completed a Phd at Oxford in 2014, under the supervision of Prof. Jon Chapman and Tiina Roose.

Postdoctoral experience at INRIA Sophia Antipolis, France, University of Sydney and University of Utah

Postdoctoral experience at INRIA Sophia Antipolis, France, University of Sydney and University of Utah

Education

Ph.D.; University of Oxford ; ; 2014

B.A.; University of New South Wales; Philosophy; 2007

B.S.; University of New South Wales; Pure Mathematics; 2007

B.A.; University of New South Wales; Philosophy; 2007

B.S.; University of New South Wales; Pure Mathematics; 2007

2022 Fall Courses

MATH 792B - PRE DOCTORAL RESEARCH

MATH 371 - PHYSIOLOGY AND MEDICINE

MATH 790A - DOCT DISSERTATION & RES

MATH 337 - LINEAR ALGEBRA

MATH 371 - PHYSIOLOGY AND MEDICINE

MATH 790A - DOCT DISSERTATION & RES

MATH 337 - LINEAR ALGEBRA

Office Hours

Monday 2-4 pm

Teaching Interests

I enjoy teaching a wide range of mathematics. I have taught first year calculus, 3rd year undergraduate mathematical biology, and a graduate course on stochastic processes.

Past Courses

MATH 111: CALCULUS I

MATH 211: CALCULUS III A

MATH 371: PHYSIOLOGY AND MEDICINE

MATH 373: INTRO TO MATHEMATICAL BIOLOGY

MATH 373: INTRODUCTION TO MATHEMATICAL BIOLOGY

MATH 691: STOCHASTIC PROCESSES

MATH 691: STOCHASTIC PROCESSES WITH APPLICATIONS

MATH 211: CALCULUS III A

MATH 371: PHYSIOLOGY AND MEDICINE

MATH 373: INTRO TO MATHEMATICAL BIOLOGY

MATH 373: INTRODUCTION TO MATHEMATICAL BIOLOGY

MATH 691: STOCHASTIC PROCESSES

MATH 691: STOCHASTIC PROCESSES WITH APPLICATIONS

Research Interests

Mathematical Biology

Stochastic Processes

Dynamical Systems.

Stochastic Processes

Dynamical Systems.

Conference Proceeding

The Effect of Stochastic Bursting on Biological Clock Precision

European Control Conference Proceedings, May 2020

European Control Conference Proceedings, May 2020

Journal Article

MacLaurin, James, & Robinson, Peter (2019). Determination of effective brain connectivity from activity correlations.

MacLaurin, James, & Bressloff, Paul (2020). Wandering bumps in a stochastic neural fields: a variational approach.

MacLaurin, James, & Bressloff, Paul (2020). Phase Reduction of Stochastic Biochemical Oscillators.

MacLaurin, James (2018). Synchronization of stochastic hybrid oscillators driven by a common switching environment.

MacLaurin, James, & Salhi, Jamil , & Toumi, Salwa (2018). Mean field dynamics of a Wilsonâ€“Cowan neuronal network with nonlinear coupling term.

*Phys Rev E*,MacLaurin, James, & Bressloff, Paul (2020). Wandering bumps in a stochastic neural fields: a variational approach.

*Physica D*,MacLaurin, James, & Bressloff, Paul (2020). Phase Reduction of Stochastic Biochemical Oscillators.

*SIAM Journal of Applied Dynamical Systems*,*19*(1), 151-180.MacLaurin, James (2018). Synchronization of stochastic hybrid oscillators driven by a common switching environment.

*Chaos: An Interdisciplinary Journal of Nonlinear Science*,*28*(12),MacLaurin, James, & Salhi, Jamil , & Toumi, Salwa (2018). Mean field dynamics of a Wilsonâ€“Cowan neuronal network with nonlinear coupling term.

*Stochastics and Dynamics*,*18*(06), SHOW MORE

Bressloff, P, & MacLaurin, James (2018). Synchronization of stochastic hybrid oscillators driven by a common switching environment.

Bressloff, Paul, & MacLaurin, James (2018). Stochastic Hybrid Systems in Cellular Neuroscience.

Bressloff, Paul, & MacLaurin, James (2018). A variational method for analyzing stochastic limit cycle oscillators.

Bressloff, Paul, & MacLaurin, James (2018). A variational method for analyzing limit cycle oscillations in stochastic hybrid systems.

Mukta, Kamrun, & MacLaurin, James, & Robinson, Peter (2017). Theory of corticothalamic brain activity in a spherical geometry: Spectra, coherence and correlation.

Inglis, James, & MacLaurin, James (2016). A General Framework for Stochastic Traveling Waves and Patterns, with Application to Neural Field Equations.

Faugeras, Olivier, & MacLaurin, James (2015). Asymptotic Description of Neural Networks with Correlated Synaptic Weights.

Faugeras, Olivier, & MacLaurin, James (2014). A Large Deviation Principle and an Expression of the Rate Function for a Discrete Stationary Gaussian Processs.

Faugeras, Olivier, & MacLaurin, James (2014). A Representation of the Relative Entropy with Respect to a Diffusion Process in Terms of Its Infinitesimal Generator.

Faugeras, Olivier, & MacLaurin, James (2014). Asymptotic description of stochastic neural networks. I. Existence of a large deviation principle.

Faugeras, Olivier, & MacLaurin, James (2014). Asymptotic description of stochastic neural networks. II. Characterization of the limit law.

MacLaurin, James, & Jon, Chapman, & Wyn Jones, Gareth, & Roose, Tiina (2013). The study of asymptotically fine wrinkling in nonlinear elasticity using a boundary layer analysis.

MacLaurin, James, & Wyn Jones, Gareth, & Chapman, Steven, & Roose, Tiina (2012). The buckling of capillaries in solid tumors.

*Chaos: An Interdisciplinary Journal of Nonlinear Science*, 1--16.Bressloff, Paul, & MacLaurin, James (2018). Stochastic Hybrid Systems in Cellular Neuroscience.

*The Journal of Mathematical Neuroscience*,*8*(1),Bressloff, Paul, & MacLaurin, James (2018). A variational method for analyzing stochastic limit cycle oscillators.

*SIAM Journal on Applied Dynamical Systems*,*17*(3), 2205-2233.Bressloff, Paul, & MacLaurin, James (2018). A variational method for analyzing limit cycle oscillations in stochastic hybrid systems.

*Chaos*,*28*(6),Mukta, Kamrun, & MacLaurin, James, & Robinson, Peter (2017). Theory of corticothalamic brain activity in a spherical geometry: Spectra, coherence and correlation.

*Physical Review E*,*96*,Inglis, James, & MacLaurin, James (2016). A General Framework for Stochastic Traveling Waves and Patterns, with Application to Neural Field Equations.

*SIAM Journal of Applied Dynamical Systems*,*15*(1), 195-234.Faugeras, Olivier, & MacLaurin, James (2015). Asymptotic Description of Neural Networks with Correlated Synaptic Weights.

*Entropy*,*17*(7), 4701-4743.Faugeras, Olivier, & MacLaurin, James (2014). A Large Deviation Principle and an Expression of the Rate Function for a Discrete Stationary Gaussian Processs.

*Entropy*,*16*(12),Faugeras, Olivier, & MacLaurin, James (2014). A Representation of the Relative Entropy with Respect to a Diffusion Process in Terms of Its Infinitesimal Generator.

*Entropy*,*16*(12),Faugeras, Olivier, & MacLaurin, James (2014). Asymptotic description of stochastic neural networks. I. Existence of a large deviation principle.

*Comptes Rendus Mathematique*,*352*(10), 841-846.Faugeras, Olivier, & MacLaurin, James (2014). Asymptotic description of stochastic neural networks. II. Characterization of the limit law.

*Comptes Rendus MathÃ©matiques*,*352*(10), 847-852.MacLaurin, James, & Jon, Chapman, & Wyn Jones, Gareth, & Roose, Tiina (2013). The study of asymptotically fine wrinkling in nonlinear elasticity using a boundary layer analysis.

*Journal of the Mechanics and Physics of Solids*,*61*(8),MacLaurin, James, & Wyn Jones, Gareth, & Chapman, Steven, & Roose, Tiina (2012). The buckling of capillaries in solid tumors.

*Proceedings of the Royal Society A*,*468*(2148), 4123-4145.COLLAPSE