Time Series

The Lab's missions

Monitoring of new methods or algorithms to stay on the cutting edge of technology in forecasting, classification, clustering, and anomaly detection
Knowledge management to accelerate the development of future projects thanks to our reusable source code base
Detailed and documented packages on topics such as data quality, preprocessing, and modeling

Our research topics

Forecasting

By developing benchmarks we compare the performance of different use cases such as power consumption forecasting, wind productivity and call center activity forecasting. This is made possible by testing and researching the performance with classical static methods (LASSO, GAM...), machine learning methods (random forest, boosting...), or expert aggregates. But also with more complex approaches, notably via Deep Learning (LSTM, transformers...).

Classification/Clustering

With a repertoire supporting the development of future projects (customer segmentation, clustering of load curves or dimension reduction). But also through writing best practice guides and articles on the main steps of a clustering project.

Anomaly detection

The variety of methods being important, feedback on data quality missions or anomaly detection via sensors (industrial, IoT, etc.) allows us to capitalize on our knowledge. And therefore to direct research on the methods likely to be the most efficient (ML, probabilistic...).

Our publications

- Financial Services & Compliance

Synthetic data or how to share sensitive data…

For a period of six months, 5 students from Centrale Supélec and ESSEC worked collaboratively with Sia Partners on building a Python library to create fake - which we'll call synthetic - data.
But what's the point of creating fake data? How could it help organizations?

2023

- Financial Services & Compliance

Introduction to OpenStreetMap: How to leverage…

In this article, we explore the use of OpenStreetMap for extracting geospatial data and implementing an approach to enhance the overall data quality. We delve into the key steps of data extraction including selecting the area of interest, data collection, cleaning, and preparing data for future use.

2023

- Marketing & Sales

Customer churn prediction with Data Science

Thanks to Machine Learning, companies can significantly improve their activities by leveraging their data. Machine Learning is a field of study of artificial intelligence that gives an AI the ability to "learn" from data.

2023

See our publications

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