Nicolas N.

- Refactoring of scientific Python code

- Performance improvement

- Advice on potential inconsistencies/errors in the data pipeline

- Design/algorithm consulting

I was in charge of multiple and varied tasks mostly centered around our defi and gaming activity:

- setting up our data stack, to be used for our frontend, and for analysis (a mix of many tools, mostly the graph)

- analyzing blockchain data, user activity, player behavior

- smart contract analysis (especially for investment purposes)

- automation in various domains (day to day activity, gaming, data retrieval)

- adding functionality to some existing code base to interact with more dexes

Some light experience with aws, react, typescript.

I did a postdoc in a team of mathematicians working mainly with the blue brain project. It was a collaboration between computer neuroscientists and mathematicians.

My research mainly involved doing **graph analysis**, on big graphs coming from the brain model of the rats. We extensively used TDA (**topological data analysis**) to compute (topological) graph invariants.

My work mostly involved using a range of data analysis methods and sometimes creating new ones to apply to our "big connectome graph".

Base code was almost always Python, with some C/C++ code binding when we needed fast computation.

Here are a few activities I was involved with:

- computing graph invariants (often on supercomputer via slurm)

- creating variations of those invariants

- applying known methods to our data (i.e., reading neuroscience papers that analyze real data and doing the same on synthetic data to compare)

- using a wide range of models depending on the data (from simple regression to random forest, not much DNN as they didn't really suit our use cases)

Besides that, I also had the usual teaching/mentoring; I taught linear algebra at EPFL, mostly tutorials, supervising a few interns.