Data Science

HEC Paris Trains Future Professors

Our PhD Students Got Talent

This special issue aims to show the excellence and diversity of the research conducted by HEC Paris PhD candidates and alumni. You will find a selection of cutting-edge findings, answering crucial questions such as: Is AI a threat to human creativity? Should we listen to the Wall Street gurus? How to better manage one’s promotion? How much do we value our private data? What are ambiguity and risk attitudes? How bad is the mere presence of a phone? HEC Paris PhD Program, headed by finance professor Johan Hombert, supports its students throughout their thesis writing and job placement in the best universities and business schools, such as the MIT, Wharton and Harvard Business School. Most PhD alumni continue to collaborate with professors at HEC, thanks to the strong relationships they have developed during their journey.

October 13th, 2021

Data Science

August 26th, 2021

Why Do We Share Our Personal Data? The Privacy Paradox Explained

The business model of many tech companies is based on collecting and using data about their customers. Google and Facebook generate revenues by selling targeted ads tailored to users' personal information. Amazon shows you the product they forecast you will buy. Tesla collects data on drivers' behavior and is said to plan using these data to enter into the insurance business. Google has just acquired smartwatch producer Fitbit, which collects data about users' health. The list goes on and on. So why most of us still widely share our personal data, even when we claim to be worried by the lack of online privacy?

Associate Professor

Finance

Data Science

December 09th, 2020

7 minutes

“A $%^* Sexist Program”: Detecting and Addressing AI Bias

A major issue facing companies that use AI, algorithmic bias can perpetuate social inequalities — as well as pose legal and reputational risks to the companies in question. New research at HEC Paris offers a statistical method of tracking down and eliminating unfairness.

By Christophe Pérignon

Data Science

December 04th, 2020

8 minutes

How Can We Force Companies To Keep Our Data Safe?

With online shopping, loyalty programs, smart devices and many other aspects of business and daily lives, companies collect vast amounts of our personal data. The risk is that they may be leaked or misused. A team of researchers designs measures that regulators and companies can undertake to preserve consumer privacy.

By Ruslan Momot

Data Science

December 10th, 2019

How Big Data Gives Insight Into Investor Uncertainty

Investor uncertainty plays a key role in economics, affecting asset prices and investment decisions. Getting a useful measure can be important to financial professionals and also government actors, to establish monetary policy. An HEC Paris researcher and two economists of the US Federal Reserve’s Board of Governors found a new way to gauge uncertainty: using data on internet clicks related to specific news.

By Thierry Foucault

Data Science

September 20th, 2019

Scientific Research: Should Negative Results Be Published?

Many call for a systematic publication of scientific negative results in order to make the production of scientific knowledge more efficient. Raphaël Lévy, Assistant Professor in the Economics and Decision Sciences Department, explains why such dissemination of knowledge may actually be beneficial, but also points to potential undesired consequences.

Assistant Professor

Economics and Decision Sciences

Data Science

September 17th, 2019

Legal Data Mining, Machine Learning and Visualization

Legal Data Mining Conference gathered professionals and academics from the technology, Artificial Intelligence and Law fields to discuss the future of Law. The two-day workshop focused on both the fundamental and practical issues of legal data mining. The event was organized by David Restrepo Amariles (Assistant Professor of Law at HEC Paris) and Ken Satoh (Professor at the National Institute of Informatics of Japan) in March 2019 at the Barreau de Paris.

Associate Professor

Tax and Law

Data Science

September 11th, 2019

cascad: A new certifying organization to help double-check scientific results

While scientific findings need to be assessed by peers and journal referees, the confidentiality of original data often makes the process arduous. An accredited organization launched by Christophe Pérignon (HEC Paris) and colleagues with access to the original research data can now ensure reproducibility of results. This not only promises huge gains in time and effort for researchers but will also shore up trust in scientific results.

Professor

Finance

Data Science

September 06th, 2019

How Can Data Help People's Lives?

Based on his recent research and work for the EU Commission, "Unlocking Privately-Held Data to Create Public Value", Alberto Alemanno, Professor of European Union Law and Regulation at HEC Paris, discusses the concept of "Data for Good", whereby private data such as those collected by social media, telecoms and banks, can be shared with public authorities so as to save lives, such as in natural disasters, and improve them through better designed and more effective policies.

Jean Monnet Professor

Tax and Law

Data Science

March 28th, 2019

How HEC Paris Professors Enhance Their Research and Courses Using a Data Visualization App

In the following interview, two researchers at HEC Paris, Professor of Marketing Peter Ebbes and CNRS Research Professor Emmanuel Kemel, explain how they use the web apps R and Shiny*, to visualize results of data analysis, to help students in understanding the formulas used for those analysis, and to help disseminate the research among academics and practitioners.

CNRS Research Professor

Economics and Decision Sciences