Hasso-Plattner-Institut25 Jahre HPI
Hasso-Plattner-Institut25 Jahre HPI
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Advanced Medical Machine Learning Seminar (Sommersemester 2023)

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

Allgemeine Information

  • Semesterwochenstunden: 4
  • ECTS: 6
  • Benotet: Ja
  • Einschreibefrist: 01.04.2023 - 30.04.2023
  • Prüfungszeitpunkt §9 (4) BAMA-O: 01. August 2023
  • 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 18th April, 4:00 pm in G1.E15/16


 

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/14G0NduYO8bsluzTk53bste1ltXx3naQpU-XfK98_Q0Q/edit#gid=0

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/14G0NduYO8bsluzTk53bste1ltXx3naQpU-XfK98_Q0Q/edit#gid=0

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: 18th April, 4:00 pm.
Where: seminar room G1.E15/16 

or via zoom

Join Zoom Meeting
https://uni-potsdam.zoom.us/j/63233470616

Meeting ID: 632 3347 0616
Passcode: 35021474

 

Contact: teaching-lippert(at)hpi.de

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