Hyperlex

Development of a NLP pipeline to automate the process of analyzing legal documents for a SaaS contract management platform.

• Continuous improvement of Hyperlex AI engine in close collaboration with the Product team
• Managed several PoC projects to solve various NLP tasks (e.g. information extraction, anomaly detection) for our clients

Hyperlex

• Benchmarking state-of-the-art methods for text classification in legal documents
• Integration of those methods into Hyperlex AI engine which leads to a significant qualitative improvement for our customers

ENS Paris-Saclay

I completed the Master 2 Mathématiques, Vision, Apprentissage (MVA) in parallel of my last year at MINES ParisTech. Master MVA is a prestigious research Master in France, specialized in Computer Vision and Machine Learning. Taught by leading researchers, it aims to bring students abreast with the cutting edge in research.

Attended courses:

• Computer Vision and Object Recognition (C. Schmid, J. Ponce, J. Sivic)
• Probabilistic Graphical Models (F. Bach)
• Reinforcement Learning (A. Lazaric)
• Convex Optimization (A. d’Aspremont)
• Algorithms for Speech and NLP (E. Dupoux)
• Machine Learning with Kernel Methods (JP. Vert, J. Mairal)
• Curse of dimensionality (S. Mallat)

NEC Laboratories Europe

I worked with the Data Science group on memory networks for aspect-based sentiment analysis. We further extended the system to tackle sentiment analysis in financial headlines.

Institute for Infocomm Research

I worked with the Visual Attention Lab on activity recognition in videos where I proposed and developped an object detector based on recurrent neural network.

MINES ParisTech

MINES ParisTech is one of the top and oldest French Engineering School. With more than 1,200 students (Masters and Ph.D) and its 18 research centres covering a wide range of topic, it has built a strong link with companies and industries.

Attended courses:

• Statistics
• Machine Learning
• Probability
• Optimization
• Image Processing
• Stochastic processes