Hasso-Plattner-Institut25 Jahre HPI
Hasso-Plattner-Institut25 Jahre HPI

Advanced Medical Machine Learning Seminar (Sommersemester 2024)

Lecturer: Prof. Dr. Christoph Lippert (Digital Health - Machine Learning) , Sumit Shekhar

General Information

  • Weekly Hours: 4
  • Credits: 6
  • Graded: yes
  • Enrolment Deadline: 01.04.2024 - 30.04.2024
  • Teaching Form: Lecture
  • Enrolment Type: Compulsory Elective Module
  • Course Language: English
  • Maximum number of participants: 10

Programs, Module Groups & Modules

IT-Systems Engineering MA
Data Engineering MA
Digital Health MA
Software Systems Engineering MA
  • MALA: Machine Learning and Analytics
    • HPI-MALA-C Concepts and Methods
  • MALA: Machine Learning and Analytics
    • HPI-MALA-T Technologies and Tools
  • MALA: Machine Learning and Analytics
    • HPI-MALA-S Specialization


Kick-off event on 11 April!

This seminar consists of semester-long research projects. The projects span topics from core machine learning research, such as generative models, uncertainty quantification, and interpretability; as well as applications in the biomedical and health sciences, such as epidemiological N-of-1 trials, genetics, and medical imaging. Students are expected to work closely with their individual supervisors (PhD students and PostDocs at the Digital Health - Machine Learning group), make substantial progress on their task, and give a presentation at the end of the semester. Especially successful projects may additionally lead to the publication of a scientific paper.

Students are required to have good coding skills (language will depend on the topic, but mostly Python and R) and have at least a basic understanding of modern machine learning, e.g. through the Deep Learning lecture at HPI or similar online courses.

project list link https://docs.google.com/spreadsheets/d/1o2W-5qLHpLeZ5B9Se45eGjoWtRwXC7BQegLmFDQg9n0/edit?usp=sharing


Precise requirements differ between the different research projects. In all cases, basic skills in machine learning/deep learning and/or statistics are highly preferred. Ambitious students may take this seminar in parallel with the Introduction to Deep Learning course.


project list link https://docs.google.com/spreadsheets/d/1o2W-5qLHpLeZ5B9Se45eGjoWtRwXC7BQegLmFDQg9n0/edit?usp=sharing


Students will work on a project for the course, and the seminar will end with a short presentation and/or a short written report. Details to follow.


Kick-off event details:
When: 11th April, 9:15 a.m.
Where: pool room G2.U10/14
or via zoom using the below link:

Contact: teaching-lippert(at)hpi.de