Portrait of Valérie Pisano

Valérie Pisano

President and CEO, Leadership Team

Biography

Valérie Pisano is the President and CEO of Mila. A prominent leader in Canada’s artificial intelligence landscape, she is recognized for her strategic vision and transformational leadership. With over 20 years of experience in growth management, she notably served as Chief Talent Officer at Cirque du Soleil and co-founded the Mobïus project on bias to accelerate the dialogue on female leadership in the corporate world.

Since 2018, she has led Mila, the world’s largest academic research center in deep learning, founded by Professor Yoshua Bengio, the world's most cited researcher and recipient of the AM Turing Award. Under her leadership, the Institute has experienced exponential growth, establishing itself as a pillar of the Canadian AI ecosystem with a reach that extends far beyond national borders. Today, Mila boasts a community of over 1,500 researchers and 150 industrial partners, and stands as a global benchmark for AI governance, notably through key collaborations with the OECD and the United Nations.

As a former consultant with McKinsey Canada, she focuses on how humans can adapt to and benefit from this technological revolution. She holds a degree in Finance and Economics from HEC Montréal and currently serves on the boards of directors of LawZero, Chartwell, and Énergir.

Publications

COVI White Paper - Version 1.1
Hannah Alsdurf
Prateek Gupta
Daphne Ippolito
Richard Janda
Max Jarvies
Tyler Kolody
Sekoul Krastev
Robert Obryk
Dan Pilat
Nasim Rahaman
Jean-François Rousseau
Abhinav Sharma
Brooke Struck … (see 3 more)
Yun William Yu
The SARS-CoV-2 (Covid-19) pandemic has caused significant strain on public health institutions around the world. Contact tracing is an essen… (see more)tial tool to change the course of the Covid-19 pandemic. Manual contact tracing of Covid-19 cases has significant challenges that limit the ability of public health authorities to minimize community infections. Personalized peer-to-peer contact tracing through the use of mobile apps has the potential to shift the paradigm. Some countries have deployed centralized tracking systems, but more privacy-protecting decentralized systems offer much of the same benefit without concentrating data in the hands of a state authority or for-profit corporations. Machine learning methods can circumvent some of the limitations of standard digital tracing by incorporating many clues and their uncertainty into a more graded and precise estimation of infection risk. The estimated risk can provide early risk awareness, personalized recommendations and relevant information to the user. Finally, non-identifying risk data can inform epidemiological models trained jointly with the machine learning predictor. These models can provide statistical evidence for the importance of factors involved in disease transmission. They can also be used to monitor, evaluate and optimize health policy and (de)confinement scenarios according to medical and economic productivity indicators. However, such a strategy based on mobile apps and machine learning should proactively mitigate potential ethical and privacy risks, which could have substantial impacts on society (not only impacts on health but also impacts such as stigmatization and abuse of personal data). Here, we present an overview of the rationale, design, ethical considerations and privacy strategy of `COVI,' a Covid-19 public peer-to-peer contact tracing and risk awareness mobile application developed in Canada.
COVI White Paper-Version 1.1
H. Alsdurf
T. Deleu
Prateek Gupta
Daphne Ippolito
R. Janda
Max Jarvie
Tyler Kolody
S. Krastev
Robert Obryk
D. Pilat
Nasim Rahaman
I. Rish
J. Rousseau
Abhinav Sharma
B. Struck … (see 3 more)
Yun William Yu