CV

General Information

Full Name Mélanie Roschewitz
Email m.roschewitz21@imperial.ac.uk
Languages English, French, German

Research Experience

  • Oct 2021 - Now
    PhD in Computing
    Imperial College London, Departement of Computing, UK
    • Under the supervision of Prof. Dr. Ben Glocker.
    • Fully funded by an Imperial College President's Scholarship.
    • My research focuses on reliability, robustness and safety of AI systems for medical imaging.
  • Apr.22 - Oct.22
    ML Research Intern
    Kheiron Medical Technologies, London, UK
    • Investigating domain generalisation and model robustness in breast screening applications.
  • Apr.20 - Sep.21
    Applied Researcher (I & II)
    Microsoft Research Cambridge, Health Intelligence, UK
    • Part of Project InnerEye
    • Developing open-source machine learning models for medical image analysis and personalised treatment.
  • Sep.19 - Mar.20
    AI Resident
    Microsoft Research Cambridge, All Data AI, UK
    • Part of the Enterprise Knowledge team: constructing a knowledge base from business data using unsupervised ML and probabilistic programming.
  • Feb.18-Aug.18
    Student Research Assistant
    ETH Zürich, Chair of Risk and Insurance Economics, CH
  • Jun.17 - Aug.17
    Statistics Intern
    Statistics Canada, Ottawa, CA

Education

  • 2019
    M.Sc. Data Science (distinction)
    ETH Zurich, CH
    • Original title: Master of Science ETH in Data Science, mit Auszeichnung. GPA: 5.8/6.
    • Courses include: Machine Learning, Big Data, Computational Statistics, Deep Learning, Computational Biology, Ultrasound Imaging, Experimental Design.
  • 2017
    Postgraduate diploma in Statistics (distinction)
    Université de Strasbourg, FR
    • Original degree title: Maîtrise en Statistique, mention très bien. Rank 1/14.
  • 2016
    B.Sc. Mathematics (distinction)
    Université de Strasbourg, FR
    • Original degree title: Licence de Science, Technologies, Santé, Mention Mathématiques, mention très bien. Rank 1/85.

Teaching activities

  • 2022 - Present
    Graduate Teaching Assistant
    Imperial College London, UK
    • Machine Learning For Medical Imaging: guest lecturer, coursework design and marking (Spring 2024)
    • Deep Learning & Machine Learning For Imaging: supervision of a weekly exercise session and marking of coursework (Spring 2023)
    • Probability & Statistics: supervision of a weekly exercise session and marking of weekly assignments (Spring 2022)
  • Fall 2018
    Teaching Assistant
    ETH Zürich, CH
    • Big Data: supervision of a weekly 2-hour exercise session. Design of exercise sheets and solutions.

Outreach & community activities

  • Outreach
    • Lecturer for the "GirlsWhoML workshops" (Fall 2022 and 2023), a series of lectures designed to introduce core principles of Machine Learning to women studying subjects not related to computer science, to enable them to leverage these tools in their own field.
    • Research talk at Imperial College’s "girls-only computing taster day", tailored for high school students aged 14-18; sharing my path to becoming a computer scientist as well as examples of AI applications in the healthcare domain.
    • Assistant for the "Hello World Hack", day of introduction to coding for girls in primary schools (aged 6-9), helping them to solve coding and machine learning games.
  • Reviewing activities
    • Reviewed for various ML for health venues: Nature Medicine, MICCAI workshops, NeurIPS Deep Generative 4 Health workshop...

Scholarships

  • 2021 - 2025
    Imperial College President's PhD Scholarship
    • Awarded to candidates with excellent academic performance and promising research potential.