”I applied to BigDataFinance project because the challenge of solving real-life problems, which involve high-dimensional datasets, have always been one of my primary research interests”
I come from Colo
mbia, one of the most beautiful countries in South America, where I pursued a Bachelor’s degree in Electronic Engineering and a Master’s degree in Engineering. I have experience in probabilistic models, kernel methods, and high dimensional data analysis. These techniques were used for feature extraction, feature selection, functional connectivity, classification, and low dimensional representations from high dimensional datasets, enabling to enhance forecasting and embedding representations for energy market.
I applied to BigDataFinance project because the challenge of solving real-life problems, which involve high-dimensional datasets, have always been one of my primary research interests. I am particularly interested in data analysis, data mining, and machine learning, because by using these techniques, it is possible to find intrinsic relationships inside data sets. These findings could help to guide decisions in many economic or industrial fields. Consequently, high-dimensional data analysis allows to bridge research and practice, and this is precisely my fascination about this topic.
Finally, BigDataFinance drove me to UK, where I am working on my research project, and pursuing a PhD in Computer Science at The University of Manchester. This is a great opportunity to excel in a highly competitive environment.
Sergio Garcia Vega is based at The University of Manchester 2016-2019, and his research project is Distributed and Real-time Machine Learning for Financial Data Analysis.
Artikkeli Sergio Garcia Vega from The University of Manchester julkaistiin ensimmäisen kerran BigDataFinance.