What inspired your interest in statistics and probability, and how did your experiences lead you to pursue research opportunities in Canada?
I've always had a passion for mathematics—it’s been my favorite subject since high school. My real interest in statistics and probability was sparked during my time at INSEA in Morocco, where I trained in statistics and applied economics. It was there that I met S. El Adlouni - who encouraged me to pursue research and helped connect me with networks in Canada. Moving to Canada was pivotal for my career, as it allowed me to collaborate with incredible mentors and colleagues. In copula-based inference techniques, a topic now discussed at MATRIX, I have worked with several esteemed collaborators and mentors, citing B. Rémillard, C. Genest, and T. Bouezmarni.

Could you share some insights into your current research and its significance in your field?
As a faculty member in the School of Public Health, my research is driven by questions related to data and public health challenges. Since starting in 2020, I have established a research program that encompasses statistical and mathematical modelling projects, focusing on theoretical and methodological approaches with applications primarily related to climate change and public health. Techniques that I have co-developed or utilised with my collaborators include large language models, time series methods (modelling multivariate time series, change-point problems, independence tests, etc.), copula techniques, and deterministic and stochastic compartmental models (ordinary differential equations and stochastic differential equations). My applications aim to enhance the surveillance of public health threats, such as developing an early warning system that can utilise data to predict outbreaks, as well as timely forecasting the dynamics of threats like infectious diseases.

Do you have any interesting discoveries or ideas that came up during the research program at MATRIX?
Absolutely! One of the things I appreciated most about MATRIX was the opportunity for face-to-face collaboration. During the free afternoons, I worked with P. Krupskii and B. Rémillard on extending the results of a previous article. Having time set aside for discussions was incredibly valuable. We were able to brainstorm important problems and explore potential solutions, and these in-depth conversations led to the beginnings of a new project—something that would have been difficult to achieve through weekly online meetings alone.

I also advanced a high-dimensional data project with Sévérien Nkurunziza on LASSO methods for the estimation of discretely observed diffusion processes with high-dimensional data. We had this project in mind for a year, but it was at MATRIX that we truly had the time to discuss it and begin writing an article. In addition, I was also able to discuss other ideas on spatial statistics, change-point techniques and high-dimensional regularisation approaches with other participants. The time and space that MATRIX provided for collaboration made all the difference.

Can you share a few words about your extended visit to an Australian university as part of your scholarship?
As part of my scholarship, I had the opportunity to extend my visit to the School of Mathematics and Statistics at the University of Melbourne. It was a true privilege to be in a place where one of the most influential statisticians worked. This extended visit allowed me to connect with domestic colleagues, fellow researchers and students in the field as well as attend some insightful lectures. I also had the chance to collaborate further with P. Krupskii and B. Rémillard on joint research ideas. Additionally, I’m planning to return to give a short course on dependence modelling and time series.

What moments or insights made the experience particularly memorable for you?
My time at MATRIX was truly enriching, both professionally and personally. The scientific part was outstanding, and the nature around is gorgeous. The opportunities to collaborate with world-class researchers, combined with the beautiful environment, made it an unforgettable experience.

A standout moment was Dietrich von Rosen’s talk on the differences between regularisation and constrained estimation, which sparked new ideas. I was also introduced to Bayesian modular inference by M.S. Smith, factor copulas by H. Joe, and dependence using machine learning techniques by G.Y. Yi, among other valuable methods. Additionally, I was glad to learn more and appreciate the new way of thinking about dependence modelling as presented by G. Geenens. Talks on climate change problems in Australia, especially on extreme events, data and statistical approaches, were highly instructive.

Beyond the science, the natural beauty of the MATRIX campus—seeing kangaroos and various bird species—made it a special experience. Playing snooker, the piano, and ping-pong in the evenings added to the fun and socialising. I hope to return soon and co-organise more workshops. It was very sad to leave after such a productive and enjoyable two weeks, but I’m looking forward to coming back!

My time during this visit was incredibly prolific, and as I looked back at my photos in Canada, I noticed I looked exhausted—though in the best way possible. Thank you, MATRIX and the Simons Foundation, for supporting me and giving me this wonderful opportunity.