Student projects

A collection of open research projects for those interested in working with me.

Contact: lmax DOT fgv AT gmail

Working environment: I am a hands off supervisor with a strong focus on fostering independence and scientific curiosity. You should expect to be given loads to read and also suffer through a few 'lectures' on how to do Science properly. I make a point of always being available via email and for pre-booked one-on-one sessions.

Undegraduate (Scientific Initiation [IC] and Honours thesis [TCC])

If you're an undergraduate student who (a) likes Statistics and Biology and wants to do Scientific Initiation and/or (b) is looking to complete an undergraduate thesis under my supervision but does not have a clear project in mind, there are a few projects listed here that might pique your interest. These range from programming for Public Health data analysis to theoretical statistics. So pick your poison and shoot me an email.

Coding projects

If you like programming and would like to flex your coding muscles in Scientific Computing problems, take a look at the projects in Programming Projects and see if anything whets your appetite.

Master's degree

A few projects suitable for a MSc Dissertation (in Applied Mathematics) are listed here. Feel free to contact me about them, but know that it is probably best to complete coursework before you start the dissertation. The projects all involve graduate-level Statistics and many involve some non-trivial programming.

PhD

Now, if you're a prospective PhD student without a project proposal, please take a look at this page to see if anything piques your fancy. And then contact me. If you already have an interesting project you think I could supervise, also feel free to shoot me an email.

For PhD-level work I expect a solid theoretical basis, as well as a commitment to the production and maintenance of Free and open software and adhrence to the best current practices in Scientific Reproducibility. I also expect a commitment to the absolute highest standards of scholarship and a drive to contribute to the peer-reviewed international published literature.

Current students

• 2022- Eduardo Adame Salles (IC, INCTMat), "Shape-constrained Gaussian Processes with derivative information".
• 2023- Ezequiel Braga (IC), "Estendendo a formulação de modelos conjuntos em Stan".
• 2023- Iara Castro (IC, CNPq), "Utilizando dados públicos para mitigar a dengue".
• 2023- Rodrigo Kalil (IC, FAPERJ), "Estendendo a formulação de modelos conjuntos em Stan".
• 2022- Wellington Silva (MSc, CAPES), "Efficient Bayesian computation for intractable count models".
• 2023- Igor Michels (MSc, CAPES), "Modelagem Matemática do Futebol Brasileiro".
• 2023- Isaque Pim (MSc, CAPES), "Spatial confounding for areal data".
• 2023- Felipe Shardong (PhD, CAPES), "Mathematical modelling of antimicrobial resistance in Brazil".
• 2024- Atílio Leitão Pellegrino (PhD, CAPES), "Combining forecasts from epidemiological models: theory and methods".

A list of former students is also available.