In some sense, I have been “close” to GERAD for some time. As a postdoc at the Centre de recherches mathématiques (CRM) between 2015 and 2017, I was a neighbour of GERAD in the Pavillon André-Aisenstadt, without even being aware of it.

It was only when I joined UQAM as a new professor in business intelligence and data science that I learned more about GERAD. Very quickly it became clear to me that its research field is closely connected to my own interests in applied mathematics and modelling of decision making under uncertainty. I am thrilled to have joined GERAD and am looking forward to participating in its activities and, once this is possible, personally getting to know the community.

I started my career in mathematics during my PhD at the University of Warwick in United Kingdom. Under the supervision of Neil O’Connell, I studied random combinatorial objects, particularly in connection to random matrix theory.

At the end of my PhD I had spent a total of eight years in the UK (including undergraduate). I was excited to move to Canada, for a postdoc in the Department of mathematics at the University of Toronto, where my advisors were Jeremy Quastel and Bálint Virág. I started working on a class of probabilistic model that exhibit a particular type of scaling behaviour, called the KPZ universality class. Beyond its interest for mathematical physics, many different fields of mathematics find their application in this area, in which I still pursue some research projects.

Recently, I have started working on more applied problems that lie at the intersection of probabilistic modelling, machine learning and mathematical optimization. For example, I am interested in developing unsupervised and reinforcement learning techniques to better understand and solve large-scale stochastic and deterministic mathematical optimization problems. In this direction, we have recently developed a graph clustering approach to scenarios based on opportunity cost. I am also interested in applying probabilistic modelling and machine learning techniques to computational biology and personalized medicine. I am looking forward to getting to know you, virtually for the time being and in person as soon as it is possible.

Member of GERAD since November 2020