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

Trends in AI and Deep Learning Research Seminar (Sommersemester 2024)

Lecturer: Prof. Dr. Gerard de Melo (Artificial Intelligence and Intelligent Systems) , jingyi Zhang (Artificial Intelligence and Intelligent Systems)

General Information

  • Weekly Hours: 4
  • Credits: 6
  • Graded: yes
  • Enrolment Deadline: 01.04.2024-30.04.2024
  • Teaching Form: Lecture / Exercise
  • Enrolment Type: Compulsory Elective Module
  • Course Language: German

Programs, Module Groups & Modules

IT-Systems Engineering MA
Data Engineering MA
Digital Health MA
Cybersecurity MA
Software Systems Engineering MA
  • DSYS: Data-Driven Systems
    • HPI-DSYS-C Concepts and Methods
  • DSYS: Data-Driven Systems
    • HPI-DSYS-T Technologies and Tools
  • DSYS: Data-Driven Systems
    • HPI-DSYS-S Specialization
  • 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


Deep Learning is the foundation for most modern approaches to AI, especially for large language models (LLMs), natural language processing (NLP), and computer vision (CV). Recent advances such as ChatGPT and other Transformer models as well as multimodal models such as Midjourney and CLIP show the effectivess of deep learning solutions in tackling many complex single-modality and multimodal problems.

This seminar aims to build upon recent research in LLMs, NLP, CV, and deep learning.

Potential topics that could be explored in this seminar include Transformer models for NLP, vision-and-language models, etc. The specific list of topics will be presented in the first session.


The main focus is on research, so depending on the topic, some prior familiarity with ML/AI, especially Deep Learning, is probably needed. For many topics, you will need some prior experience with PyTorch, Tensorflow, or Jax, and prior experience in training deep neural networks with GPUs. For example, you can take our "Natural Language Processing" course, Christoph Lippert's Deep Learning course, or Dagmar Kainmüller's computer vision course to acquire the prerequisite knowledge. The specific prequisites for each topic will be explained in the first session.


This seminar focuses on practical research skills. Depending on the topic, you can either investigate it alone or in a team. Students will work on these projects throughout the semester, supported by weekly meetings with their mentor.


The grade will be based on the following:

  • 25% Final Presentation
  • 75% Project (7 to 10-Page Paper and Code Submission)


Important criteria for the evaluation of the project include the project effort, the quality of the paper, and the reproducibility of the code. Further details will be given during the seminar.


Potential topics are presented on the first day (Monday, April 8, 15:15-16:45 in HPI Main Building, room H2.57/58).

There will be a mid-term presentation during the semester in addition to a final presentation at the end of the semester. 

Slides for organization are here https://drive.google.com/file/d/106uJItKJoZzlE9q73qhfNqonWM7Su-Px/view?usp=sharing

Slides for the topics are here     https://drive.google.com/file/d/13vD9qkz11TwaFgEAJ_ZWh-p3SKJ3COgd/view?usp=sharing