Laurent El Ghaoui

Permanent URI for this collection

https://vinspace.online/handle/123456789/12

Interim Vice Provost of Research & Innovation

Dean, College of Engineering & Computer Science

College of Engineering and Computer Science

BIOGRAPHY

Prior to his current appointment at VinUniversity, Prof. El Ghaoui taught at the Department of Electrical Engineering & Computer Science and Department of Industrial Engineering & Operations Research at University of California, Berkeley (ranked #32 worldwide according to the QS World University Rankings 2021). He also taught Data Science within the Master of Financial Engineering at UC Berkeley’s Haas Business School. Besides being a researcher and a lecturer, Prof. El Ghaoui is also a consultant and an entrepreneur. According to him, these experiences solving real-world problems have supplemented his research life tremendously.

RESEARCH INTERESTS

Operations Research, Robust Optimization, New computational models and algorithms for deep learning, Machine learning and statistics, with emphasis on sparsity issues.

Browse

Now showing 1 - 1 of 1

Topic analysis in news via sparse learning: a case study on the 2016 US presidential elections
(2017-06) Ghaoui, Laurent El; Calafiore, Giuseppe C
Textual data such as tweets and news is abundant on the web. However, extracting useful information from such a deluge of data is hardly possible for a human. In this paper, we discuss automated text analysis methods based on sparse optimization. In particular, we use sparse PCA and Elastic Net regression for extracting intelligible topics from a big textual corpus and for obtaining time-based signals quantifying the strength of each topic in time. These signals can then be used as regressors for modeling or predicting other related numerical indices. We applied this setup to the analysis of the topics that arose during the 2016 US presidential elections, and we used the topic strength signals in order to model their influence on the election polls.

Browse

Recent Submissions