Dr. Guillaume HOCHARD

Associate Professor
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Dr. Guillaume HOCHARD

Biography

With 15 years of experience in artificial intelligence, he is now an associate professor at aivancity.

Passionate, rigorous, and committed, his career path has led him to specialize in the leadership, management, and implementation of generative AI projects, from research to industrialization, including R&D and modeling.

 

 

Education & Degrees

YearUniversityDegree/Position
2016Polytechnic School    DSSP – Big Data & Machine Learning
2011Telecom ParisTech    PhD – Statistics, machine learning, and graphs on satellite images
2006ENSGM2 GIS – Geographic information systems
2005    ENSTA Bretagne    Engineer – Electronics and Signal Processing

Professional experience

YearFunction
2025Associate Professor aivancity
2023–2024    VP of AI | Ryte.ai (AI-driven healthcare platform)
2021–2023    AI Product Director | Symphony AI - Retail & Consumer Packaged Goods
2017–2021    Senior Manager | Quantmetry (Cap Gemini Invent)
2019–2021    AI Expert | High Authority for Health
2011–2017    Head of Product, Lead Data Science | Sixense (Vinci)
2006–2010    Research scientist | CEA (French Atomic Energy Agency)

Publications

  • "Climate risk and machine learning: from attribution to storm intensity prediction" - Hochard G., French Statistical Society, Environment and Statistics Group, November 20, 2020
  • Short-term storm intensity forecasting: a comparison of deep learning and machine learning methods for multivariate and multimodal time series forecasting - Hochard & Ferlande, 40th International Symposium on Forecasting, Virtual, October 26-28, 2020
  • "Improving Forecasting Performance with Topological Data Analysis" - Minervino, Hochard, Ibnouhsein & Brunel, 40th International Symposium on Forecasting, Virtual, October 26-28, 2020
  • "Deep Learning approach for short term Storm Forecasting" - Ferlande & Hochard, European Safety and Reliability Conference ESREL 2020 PSAM 15, November 1-5, 2020
  • "Combining statistical and machine learning methods to improve energy consumption forecasting performance" - Hochard & Blanche, 39th International Symposium on Forecasting, Thessaloniki, June 16-19, 2019
  • "Is it possible to predict background noise levels from measured meteorological data with machine learning techniques?" - Bigot & Hochard, INCE Europe, 8th International Conference on Wind Turbine Noise Lisbon – June 12-14, 2019
  • "Cyclone Artificial Intelligence PrintsInvestigation" - Poster session at AI & Climate-Ocean-Atmosphere Day, February 6, 2019, Rennes, and at INRIA TS Days, March 25-26, 2019, Rennes
  • Co-author of the white paper "AI, explain yourself! When performance isn't enough," 2018
  • Member of the translation team for the book Deep Learning by A. Courville, I. Goodfellow, and Y. Bengio, 2018
  • Ning, Zhangwei, and Guillaume Hochard. “Eyes in the Heavens: Satellite Technologies in Remote Site Monitoring.” Geo-Strata—Geo Institute of ASCE 21, no. 6 (2017): 50–55.
  • Satellite auscultation for infrastructure monitoring: application of satellite radar interferometry for modeling, monitoring, and anomaly detection - Guillaume Hochard, Fabien Ranvier (Soldata), CFBR proceedings, 2012
  • PhD thesis: Hochard, Guillaume. “Change Detection in Radar Imaging (Change Detection in InSAR imagery Processing of long time series).” PhD diss., Télécom ParisTech, France, 2011.
  • Hochard, Guillaume, Renaud Binet, and Jean-Marie Nicolas. “Stable coherent area in SAR interferometry.” In 2009 IEEE International Geoscience and Remote Sensing Symposium, vol. 2, pp. II-825. IEEE, 2009.

See also