Imke Mayer

PhD Student in Statistics and Applied Mathematics

École des Hautes Études en Sciences Sociales

École Polytechnique

Introduction

In October 2018 I have started a position as PhD student in statistics and applied maths at EHESS and École Polytechnique under the supervision of Jean-Pierre Nadal and Julie Josse. My current research focuses on the analysis of heterogeneous data with missing values and on causal inference with missing values. I develop methods and models which will be applied on a French database on severely traumatized patients, Traumabase®, to help answer questions related to traumatic brain injury. For this project I work closely with the anaesthesists Tobias Gauss and Jean-Denis Moyer, members of the Traumabase® Group.

Interests

Causal Inference
Missing values
Machine Learning
Biostatistics

Education

MSc in Applied Mathematics (Mathématiques - Vision - Apprentissage), 2018

École Normale Supérieure Paris-Saclay
BSc in Applied Mathematics, 2016

Sorbonne Université (former Université Pierre et Marie Curie)
BSc in Computer Science, 2016

Sorbonne Université (former Université Pierre et Marie Curie)

Experience

April 2018 – September 2018

Baltimore

Visiting Student Researcher

Center for Imaging Science, Johns Hopkins University

Topic: Global optimality of sparse dictionary learning (subject of my master’s thesis).
Advisor: René Vidal.

June 2017 – July 2017

Paris

Research Intern

LPSM, Sorbonne Université (former LSTA, Université Pierre et Marie Curie)

Topic: Control of False Discovery Rate in Regression Models.
Advisors: Claire Boyer and Maxime Sangnier.

September 2016 – January 2017

Berlin

Working Student

Foodora GmbH

Data analyses, mainly based on Google Analytics, for Business Intelligence and Global Logistics Operations Teams. Supervisor: Tobias Schmidt

July 2016 – August 2016

Berlin

Data Science Intern

Foodora GmbH

Data analyses, mainly based on Google Analytics, for Business Intelligence and Global Logistics Operations Teams. Supervisor: Tobias Schmidt

Recent & Upcoming Talks

Causal Inference with Incomplete Confounders

Jun 3, 2019 5:00 PM

51es journées de Statistique de la SFdS

Causal Inference with critical care data

May 28, 2019 2:00 PM

Séminaire Data Science pour les acteurs de la TraumaBase/TraumaMatrix

Project

Presentation of the article 'Invariant Causal Prediction for Nonlinear Models' by Heinze-Deml et al.

May 23, 2019 10:00 AM

CMAP Machine Learning Journal Club

Causal Inference with Incomplete Confounders: Treatment Effect Estimation of Tranexamic Acid on Mortality for Traumatic Brain Injury Patients

Apr 30, 2019 11:00 AM

Parietal Meeting

(Poster) Causal Inference with Missing Values: Treatment Effect Estimation of Tranexamic Acid on Mortality for Traumatic Brain Injury Patients

Mar 28, 2019 12:00 AM

EuroCIM 2019

PDF

(Poster) Causal Inference with Missing Values: Treatment Effect Estimation of Tranexamic Acid on Mortality for Traumatic Brain Injury Patients

Mar 20, 2019 6:20 PM

DAGStat 2019

PDF

Causal Inference with Missing Values: Treatment Effect Estimation of Tranexamic Acid on Mortality for Traumatic Brain Injury Patients (Talk given by Julie Josse)

Jan 22, 2019 4:00 PM

Séminaire de Probabilités et Statistique

Slides

Presentation of Ben Haeffele's paper on Structured Low-Rank Matrix Factorization: Global Optimality, Algorithms, and Application

Dec 13, 2018 10:00 AM

CMAP Machine Learning Journal Club

Slides

Introduction to Causal Inference

Nov 26, 2018 10:00 AM

Julie Josse’s students group meeting

Slides

Projects

R Forwards

R Foundation taskforce on women and other underrepresented groups.

TraumaMatrix

A decision support tool for critical care management.

R-miss-tastic

A unified platform on missing values, founded by the R Consortium. Have a look at Nick Tierney’s blog post introducing this project.

CV

My CV is available in English, French and German.

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