Elizabeth Fons

Elizabeth Fons

PhD candidate

University of Manchester

Biography

I recently completed a PhD in Computer Science at the University of Manchester, as part of a Marie-Curie Fellowship funded by the EU. During my PhD I was also a Research Associate at AllianceBernstein, London. The broad topic of my research is the study of machine learning applications for time-series analysis with applications on finance, covering deep neural networks, automated data augmentation and hidden Markov models.

I hold an MSc in Physics from University of Buenos Aires. I completed my MSc thesis at the Max Planck Institute for Physics in Munich, where I worked on pattern recognition of W-boson events during collisions inside the ATLAS experiment at CERN.

Download my resumé.

Interests
  • Deep Learning
  • Time Series
  • AutoML
Education
  • PhD in Computer Science, 2021

    University of Manchester

  • BSc + MSc in Physics, 2016

    University of Buenos Aires

Publications

Adaptive Weighting Scheme for Automatic Data Augmentation. 2021.
Evaluating data augmentation for financial time series classification. 2021.
Augmenting transferred representations for stock classification. ICASSP 2021, 2021.
A novel dynamic asset allocation system using Feature Saliency Hidden Markov models for smart beta investing. Expert Systems with Applications, 2020.

Talks

Regime switching models for smart beta investing