Guillaume Chevillon
Professor, ESSEC Business School, Paris 

Pedagogy & Research: Economics, Forecasting, Statistics, AI & data analytics, Creative Technologies.

Founding Academic Director:

ESSEC Metalab for Data, Technology & Society – the school's center for developing Pedagogy & core/applied Research,  transforming corporations and shaping the public discussion on the AI & Data revolution since 2020.
ESSEC | CentraleSupélec Master in Data Sciences & Business Analytics – since 1995, training 150-180 students from 30 nationalities every year to a unique blend of data science, AI, deep learning and their contemporary business uses.  Consistently ranked top in Europe & worldwide. 


WELCOME TO MY HOMEPAGE. 

I am an Econometrician who works on Economics and Forecasting, and more recently on their interaction with AI. 

I am (full) Professor at ESSEC Business School, in the greater Paris area and codirector of the ESSEC Metalab for Data, Technology & Society that we founded in 2020. The Metalab fosters  academic research, develops pedagogical programs, federates a community of companies and interested individuals, and participates in the public discussion (see my Media & Texts page for information about my recent contributions).   I am also a member of the OECD network of AI experts and of the Executive Committee of the Society for Nonlinear Dynamics and Econometrics (SNDE), I am a former Head of the Department of Information Systems, Decision Sciences & Statistics at ESSEC (2020-22). 

At ESSEC, I am also the founding Academic Director, and have been in charge since 1995 of the ESSEC | CentraleSupélec Master in Data Sciences & Business Analytics – we're proud of this program which uniquely blends very advanced courses and professional projects for about 180 students per year with very diverse backgrounds and representing about 30 nationalities. It is recognized as one of the most challenging and rewarding programs in Data Science or in Business Analytics (it has on average been ranked #1 in Europe, #3 worldwide by QS). 

On the Research side, as Economics cannot be a proper experimental science (contrary to Physics and Natural Sciences, economists cannot and will not conduct large scale experiments on economies), if we have any hope for it ever to become a proper "science" rather than a set of opinions, we need to be able to refute and reject wrong theories.  This is the purpose of econometricians:  we develop tools to judge economic theories by their empirical relevance. The lack of experimentation implies that we have to resort to historical data and see what laws and principles are permanent and hidden. This is in fact a form of data sciences developed specifically with social sciences in mind. 

In this context my interests have also been recently about the interplay between Data Sciences and Social Sciences since both are ultimately about understanding human behavior and how we can have a progressive modelling strategy, i.e. truly moving towards science.  My specific focus of interest lies in dynamic phenomena, their models and the principles of dependence over time generated by human or social forces, and of course forecasting! I mostly work on theory but have applied my work in macroeconomics, energy, finance and most recently climate change and cultural studies. 

I obtained an MPhil and a DPhil in Economics from the University of Oxford, and a Master in Engineering from Ecole des Mines de Paris. I have been a visiting scholar or professor at, inter alia, Brown, Oxford, NYU, Keio, UNSW Sydney and the NY Federal Reserve. I regularly publish or am interviewed in mainstream media, please refer to the corresponding pages to read my contributions. 

News

September 2024

Academic year 2023/24:

Previous year summaries here.