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

Advanced Medical Machine Learning Seminar (Sommersemester 2024)

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

Allgemeine Information

  • Semesterwochenstunden: 4
  • ECTS: 6
  • Benotet: Ja
  • Einschreibefrist: 01.04.2024 - 30.04.2024
  • Lehrform: Vorlesung
  • Belegungsart: Wahlpflichtmodul
  • Lehrsprache: Englisch
  • Maximale Teilnehmerzahl: 10

Studiengänge, Modulgruppen & Module

IT-Systems Engineering MA
Data Engineering MA
Digital Health MA
  • SCAD: Scalable Computing and Algorithms for Digital Health
    • HPI-SCAD-C Concepts and Methods
  • SCAD: Scalable Computing and Algorithms for Digital Health
    • HPI-SCAD-T Technologies and Tools
  • SCAD: Scalable Computing and Algorithms for Digital Health
    • HPI-SCAD-S Specialization
  • APAD: Acquisition, Processing and Analysis of Health Data
    • HPI-APAD-C Concepts and Methods
  • APAD: Acquisition, Processing and Analysis of Health Data
    • HPI-APAD-T Technologies and Tools
  • APAD: Acquisition, Processing and Analysis of Health Data
    • HPI-APAD-S Specialization
Software Systems Engineering MA

Beschreibung

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

Voraussetzungen

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.

Literatur

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

Leistungserfassung

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.

Termine

Kick-off event details:
When: 11th April, 9:15 a.m.
Where: pool room G2.U10/14
or via zoom using the below link:
https://zoom.us/j/5639734929?pwd=MWlnWStLRWVCdzk3eGhIb3dUTWlhUT09

Contact: teaching-lippert(at)hpi.de

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