Andrés Ladino

Andrés Ladino

Data Scientist



I am currently working as a Data Scientist at Talan working as a consultant for the RATP Group. I was a former postdoctoral researcher in Automatic Control at UGE formely IFSTTAR. My recent research interests include Networked Control Systems (NCS), Cyberphysical Systems (CPS), Intelligent Transportation Systems (ITS) and Artificial Intelligence (AI). Previously, I did my PhD at INRIA/CNRS with the NeCS team developing Short-term Forecasting and estimation techniques for large scale traffic networks. During my last research experience, I worked at the LICIT team working on control techniques for connected and automated vehicles (CAV)s.

I am passioned about the Data Science community and the recent work developed around reproducible research. Fan of #rstats and python.

Please find a recent list of publications here Download my resumé.

  • Artificial Intelligence
  • Automatic Control
  • Intelligent Transportation Systems
  • PhD Automatic Control, 2018

    Université Grenoble Alpes

  • M.E. Electronic Engineering, 2012

    Pontifical Xavierian University

  • B.E. Electronic Engineering, 2008

    Pontifical Xavierian University


Data Analysis

Manipulation, DataViz, Modeling


Predictive, Non-linear, Gurobi, CVX


Hardware in the Loop / Control toolbox


Hardware Oriented Development


PyViz, Pandas, Keras




Data Scientist
Jan 2022 – Present Paris, France

Responsabilities include:

  • Development of new data analysis technologies for predictive maintenance for the RATP Group
  • Data science model and implementation of new features for SERVAL 2. Maintenance application for the metro/train system at RATP.
Université Gustave Eiffel (Former IFSTTAR)
Postdoctoral Researcher
Jan 2018 – Nov 2021 Lyon, France

Responsabilities include:

  • Lead a ENSEMBLE team working on assessment for traffic impact of automated vehicle technologies
  • Implemented (Python, C++) platooning software architectures and interfaces for traffic simulators;
  • Analysed ADAS protocols to ensure platooning communication at simulation level;
  • Core participant in the long program on Autonomous Vehicles IPAM UCLA
Institute of Pure and Applied Mathematics, UCLA
Graduate Researcher
Sep 2015 – Nov 2015 Los Angeles, California

Responsabilities include:

  • Visitor Researcher UCLA;
  • Designed statistical learning algorithms to estimate and predict travel time in traffic networks.
Research Assistant
Sep 2014 – Dec 2018 Grenoble, France

Development of estimation and prediction techniques for traffic systems:

  • Developed and deployed the GTL website (Traffic Use Case for the SPEEDD project);
  • Developed real time forecasting algorithms for traffic networks;
  • Developed algorithms to reconstruct and estimate missing data.
Pontifical Xavierian University
Instructor Professor
Jan 2012 – Jul 2014 Bogota, Colombia

Responsabilities include:

  • Developed the communication programs for the EU funding ADDE SALEM;
  • Instructed courses for 3rd year students in: Automatic Control and Dynamical Systems.
International Business Machines (IBM)
Process Analyst
Jan 2008 – Apr 2009 Bogota, Colombia

Responsibilities include:

  • Analyzed and adapted Business Process Management (BPM) practices IT for SO contracts;
  • Coordinated and deployed Operational Service Manuals (OSM) jointly with IT management for 3 main clients.


DeepLearning.AI TensorFlow Developer
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning, Convolutional Neural Networks in TensorFlow, Natural Language Processing in TensorFlow, Sequences, Time Series and Prediction
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Business Transformation with Google Cloud. Infrastructure and Application Modernization with Google Cloud. Managing Machine Learning Projects with Google Cloud
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Data Scientist with Python
A series of online lectures & projects on how to combine statistical and machine learning techniques with Python programming to analyze and interpret complex data.
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Machine Learning with Python
A series of online lectures & projects on how to combine statistical and machine learning techniques with Python programming to analyze and interpret complex data.
See certificate