I'm a mathematician & software engineer currently finishing a PhD in applied probability theory. Other areas I'm interested in are finance, stochastic simulation methods, operations research, and software engineering. I have extensive experience in software roles including work at Google & NICTA.
Research Interests:
Applied probability
Asymptotic analysis
Monte Carlo Methods
Qualifications:
Bachelor of Engineering (Software, 1st class Honours) / Science (Mathematics)
Bachelor of Science (Mathematics, 1st class Honours)
The broad aim to develop mathematical models for population dynamics that account for local population behaviour, individual variation, spatial structure, and differing migration patterns, and to calibrate these models to real data.
Prizes, awards and special recognition
2016
Second place in the 2016 Advanced Sampling and Exploration Matlab Competition was awarded to Patrick Laub. Awarded from the ACEMS.
Andersen, L. Nørvang, Laub P., & Rojas-Nandayapa L.
(2018). Efficient Simulation for Dependent Rare Events with Applications to Extremes. Methodology and Computing in Applied Probability. doi: 10.1007/s11009-017-9557-4
Laub, P., Asmussen S., Jensen J. L., & Rojas-Nandayapa L.
(2016). Approximating the Laplace transform of the sum of dependent lognormals. Advances in Applied Probability. 48(A), 203-215. doi: 10.1017/apr.2016.50
