In this talk I gave an overview of a recent client project in which AWS
Lambda was used to provide a scalable R-backend for a public-facing web
application. This backend performed a number of different operations,
including; evaluating a Bayesian Network model; rendering a parameterised PDF
report via R Markdown, and creating data
visualisations with {ggplot2}.
The frontend and backend code for this application is available publicly on
GitHub here.
Similarly, the infrastructure as code to host the front and backend is
available here.
I gave this talk at the North East Data Science meetup in September 2022.

# Talks

- Scaling R with AWS Lambda
- Ants, Circle Pits, & Peter Jackson
- Bayesian statistics in Astrophysics
- Hash functions and password cracking
- Parameter inference for collective behaviour

I gave this talk at Newcastle University’s postgraduate forum seminar series.
This seminar series is intended to be more relaxed than a more traditional academic
seminar environment. Speakers are encouraged to lighten the mathematical load, and
deliver a talk that is accessible to mathematicians from all disciplines.
NB. The original slides were presented in reveal.js
format. However, GitHub’s dependabot was
*continually* unhappy with the accompanying package-lock.json file. In an
attempt to permanently silence dependabot, I have converted these reveal.js
slides into PDF format.

I delivered this talk to Newcastle University’s applied mathematics department
in October 2019. The intention of this talk was to introduce attendees
to Bayesian statistics, highlight how it differs from frequentist statistics
and provide an astronomically motivated case study. All the code associated with
these slides can be found in this repository

Cryptographic hash functions have been described as the workhorses of modern
cryptography, having uses in message authentication, digital signatures and
password verification. But how do they work and how safe really are they?
In this talk I gave a live
demonstration of password cracking using the software
hashcat and one of
the university’s GPU equipped machines. This machine allowed us to make *over
4 billion* password attacks per second.
I concluded the talk by discussing how to set and manage passwords in a secure
and safe manner.

In this talk, given in 2018 at Newcastle University, I discussed work I was
completing as part of my PhD. In particular, I gave a brief introduction to
the phenomenon of collective behaviour and the related mathematical models used
to simulate these behaviours. I then showed how we can use the Stan programming
language to learn about individual behaviours from
field data.