Louise Naud

Louise Naud

AI / ML scientist

Role
Scientist at Docugami
Location
New York, NY, US
LinkedIn followers
500 followers

About Louise Naud

ML/CV Research Scientist with Green card. I graduated from Ecole Normale Superieure de Cachan, France, in 2015 as a MSc student in Mathematics and Machine Learning. I did my master thesis at the California Institute of Technology, where I was working on joint training Deep Neural Networks and Max Margin Markov Networks applied to Stereo Imaging in the EE (Pr Perona) and GPS departments (Pr Avouac). I have been working in start ups ever since.I was previously working as a research analyst in Prof. Perona\'s group at Caltech; my work revolved around social behavior recognition among mice. I worked on improving a boosted regression algorithm to detect to pose of animals with a 3D sensor. Beforehand, I worked at Thales, at the VisionLab (a mixt Thales / CEA team) on intelligent video surveillance systems. I was also working on two european projects (Sercur-ED and ProtectRail) and on the 3D-Zenith project (demonstrator for Thales TechnoDays 2012). During this time, I had the opportunity to work on ways to extract video descriptors and on the implementation of an artificial retina (presented at THALES research days 2013).I worked at the Center of Mathematical Morphology on real time and robust algorithms for smart video surveillance applications, as a research engineer. I developped a DLL for Sagem Sécurité (worldwide leader in biometrics) to segment motion zones in camera fields. I had the opportunity to use Morph-M and Mamba, mathematical morphology based librairies. In order to satisfy real time expectations, these librairies use SSE2.I also had the opportunity to lead meetings with up to 7 partners (from both the industry and universities).Specialties: Image/video processing, software development, Mathematical Morphology, Statistics, C/C++, Python, Java, MATLAB, OpenCV, Visual C++.

Experience

  1. Scientist

    Docugami

    Jul 2023 — Present · New York, NY, US

    Table Structure Recognition (Metrics improved by 25+% wrt previous system)- DETR / DINO / EVA- Highly scalable Document Clustering / Information Discovery - LLMs / VLMs in Euclidean / Hyperbolic spaces

Education

  • Universidad Politécnica de Madrid

    Networks, Project Management

    2006 — 2006

  • Lycée Condorcet

    Maths, Physics

    2003 — 2004

  • Telecom Bretagne

    Engineering Degree, Image Processing

    2004 — 2007

  • Ecole Normale Supérieure de Cachan

    Master's Degree, Mathematics and Machine Learning

    2014 — 2015

Skills

  • Statistics
  • Matlab
  • Convex Optimization
  • C++
  • Java
  • Linux
  • Mathematical Modeling
  • Algorithms
  • Video Processing
  • Software Development
  • Python
  • Latex
  • Visual C++
  • Signal Processing
  • Physics
  • Data Science
  • Computer Science
  • Image Processing
  • Mathematics
  • Data Analysis
  • Computer Vision
  • Machine Learning
  • Big Data
  • Opencv
  • Applied Mathematics
  • Research
  • Digital Image Processing
  • Software Engineering
  • Morphology
  • Text Categorization
  • C
  • Programming

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