Julie Josse, the statistical missing link

At first glance, it's hard to make a connection between head trauma management and statistical research. Since 2013, however, statistician Julie Josse has been working with intensive care physicians to improve the treatment of polytrauma patients. " From the arrival of the firefighters to the management at the hospital, there is a significant loss of information and decision errors. The goal of the TrauMatrix project is to create a typology of accident victims to better guide first aid," explains the researcher.

Missing data

The statistical processing of the data collected by the thirty Trauma Centers involved in this project makes it possible to identify typical patient profiles based on the medical information recorded by the emergency services (blood pressure, heart rate, etc.). Julie Josse also assists doctors in collecting data: " For statistical work to be useful, you have to know the field of application. Her specialty, missing data in statistical analysis, is indispensable here since information is often missing, either because of forgetfulness in the emergency, or because the patient's condition did not allow certain examinations.

Another challenge of this project is to evaluate the effectiveness of treatments for head trauma. With serious accidents, clinical studies are very difficult to set up, primarily because patient consent is often impossible. Statistical analysis is then a means of evaluation, thanks to the method of causal inference. " This method makes it possible to understand, between different treatments, whether the differences observed are actually due to the different treatments and not to other variables. So we have to disentangle the effects," explains the scientist. And to give a telling example, that of hydroxychloroquine: " The causal inference method has, for example, made it possible to show that the positive effects on people treated with hydroxychloroquine in hospital were linked to the youth of the patients treated and not to the effectiveness of the drug administered."

Silicon Valley

Applied to many fields, causal inference is very much in vogue. Julie Josse put her knowledge to work in the Google brain team in 2016: " A small bubble where researchers have all the means at their disposal to conduct fundamental research. " This is not the first time the young researcher has met the scientific elite. Before joining Inria in 2020, she was hosted for 18 months at Stanford University between 2013 and 2016, and then she was a professor at Polytechnique between 2016 and 2020. Two very different experiences of scientific excellence: " the American conviviality of Silicon Valley versus the austerity of the French school ".

Her degree in applied mathematics obtained in Brest did not predestine Julie Josse to this prestigious career. As a mathematician, she preferred the precision of demonstrations to the vagaries of statistics. The randomness of her student orientations finally led her to a master's degree in applied statistics and then to a position as a statistical engineer at Agrocampus in 2007. There, her first works on the statistical processing of sensory studies sealed her taste for the discipline. She started a PhD on the statistical management of missing data, which earned her the prize for the best thesis in 2010.

" The academic world of statistics is very open "

His involvement in the statistical scientific community around open access and knowledge sharing has opened doors for him. " The academic world of statistics is very open, as shown by the R project which offers researchers the opportunity to make their statistical processing programs freely available online," explains the woman who was elected to the R software foundation following her contributions. As a PhD student, she organized a meeting of this community in Rennes in 2009, under the dubious eye of some colleagues who could not see how the doctoral student could join the global research in statistics. " However, major international statisticians came, in particular Trevo Hastie from Stanford University. A meeting that earned me an invitation there!"

Meetings and the originality of her research on missing data do not explain everything. Julie Josse's career path also impresses by her ability to systematically carry out two jobs at once: engineer and doctoral student for three years, teacher-researcher at Agrocampus with an additional part-time position in Silicon Valley for the next three years, then professor at Polytechnique while participating in Google Brain. And during the Covid epidemic, she joined forces with emergency physicians to create an application that would provide real-time information on the availability of hospital beds ( Icubam project).

With Muse funding to set up her team, Julie Josse now joins the Institut Desbrest d'Epidémiologie et de Santé Publique (IDESP) to strengthen statistical research in health, in particular on allergies. Her Inria-Inserm team, entitled PreMeDICaL (precision medicine by data integration and causal learning), aims to improve patient care by combining clinical expertise with the wealth of multi-source data.