Daniel Salnikov

About

Hello there, allow me to give you some information about myself.
I am Daniel Salnikov a PhD student at Imperial College London supervised by Professor Guy Nason. and by Professor Mario Cortina Borja. We are working on high-dimensional nonparametric methods, parsimonious models for multivariate time series, and statistical learning. Currently, we are exploiting networks to model complex processes. Our aim is to develop and use powerful statistical machine learning methods in a medical context, understanding how and why statistical machine learning methods succeed and fail at particular tasks might enable us to use in them in sensitive contexts where model interpretation, replication and explainability are as, if not more, important than forecasting accuracy.

During my undergraduate studies I became interested on probability, statistics, optimization and analysis. Fortunately, the field of statistical learning combines themes from said fields to understand complex methods and machine learning models. My main interest at the moment is studying how concepts from high-dimensional and nonparametric statistics, optimization and analysis might help us grasp a better understanding of complex machine learning models. Also, I am interested on improving and/or proposing methodologies by incorporating theoretical results into algorithm design. Simply put, the journey an idea has from mathematical abstraction to statistical learning model ending in machine learning software is one I enjoy traveling.

Thanks for reading, feel free to look at the rest of the page to learn more.

Work

"We love to wonder, and that is the seed of science."
-Ralph Waldo Emerson.

Welcome to my work page, here you can find links to some of my selected works. Please note that this section is still under construction. However, you can find two selected works below:

• Daniel Salnikov. Bayesian Statistical Learning for Heavy-Tail Models. Bachelor's thesis, Instituto Tecnológico Autónomo de México ITAM, Mexico City, Mexico, August, 2021.
• Daniel Salnikov. A Constructive Proof of the Glivenko-Cantelli Theorem. arXiv, 2110.13236. October, 2021.
• Link to my GitHub page.

Fun

“The bottom line is to have fun and enjoy life."
-Rekha.

Welcome to my fun page, here you can find some information about my hobbies and varied interests. On my free time I enjoy hiking, jogging and tasting delicious food. Getting lost in a new city and trying out new foods, and losing myself in nature and wandering in nature are one of my preferred activities. Also, I am an avid movie goer and sci fie reader, The Foundation and Robot series by Isaac Asimov are personal favourites.

An ideal day for me would be going for a walk on a fjord, heading back to a town centre for a delicious dinner with a nice view and a captivating conversation.

Contact

• LinkedIn
• Github

Elements

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