Machine Learning Interest Group (MLIG)

If you want to present at the next ONLINE MEETUP, please write a short e-mail (philipp.roesch@unibw.de). Thanks!
 

The Machine Learning Interest Group (MLIG) aims to bring together scientific staff with an interest in Machine Learning/Artificial Intelligence. It is currently open for researchers from University of the Bundeswehr Munich and Helmut Schmidt University/University of the Federal Armed Forces Hamburg. At the moment we are over 190 people in the MLIG. 

 

Our goals:

  • Platform for ML/AI topics at UniBw M and HSU
  • Simplify networking between researchers
  • Encouraging exchange between scientists – across institutes/departments/universities 

 

What we offer:

  • We have regular ONLINE MEETUPs (via BBB) where researchers present their work in the domain of Machine Learning. Usually we have 2-3 presentations which last 15 minutes each. After all presentations we have dedicated breakout rooms, where each topic can be discussed in more depth. 
  • We hold in-person regulars' tables (STAMMTISCH) at UniCasino/Brandl to get to know each other. Before the regulars' table we explore an exciting place at the university together. There are unique opportunities to gain insights into different research fields. For example, we have already visited the GPU cluster "Monacum One" together or the reopened computer museum "datArena".
  • We are organised in an Ilias group. This group has a FORUM for questions, problems, ideas. Moreover, we have an INTRODUCE YOURSELF section where you can leave some words about you and your interests.

 

If you want to join, please do the following:  

 

We look forward to meeting you!

 

Our meetings

Registration and details on Ilias (only internally accessible)!

14.03.2024, tba

 Julia Waldmüller (CODE): Social Bot Detection Vanessa Vohs (SOWI): AI for Defence - the EUs approach towards military AI Murat Cankaya (INF): Multi task learning approaches for object detection in satellite images
Beginning of February 2024, tba

 

 6th STAMMTISCH at [tba soon] and UniCasino

27.06.2023, 16:30/18:00

 5th STAMMTISCH at Institut für Fahrzeugtechnik und Mechanik (Wehrtechnik 3/1) and UniCasino

25.05.2023, 16:00-ca.17:30

 Florian Babl (CODE): AI for Knowledge Extraction from news articles Fabian Deuser (ETTI):
Generating Novel Views from Public Images
  

06.02.2023, 16:00-ca.17:30

New AI/ML team at UniBw M of Prof. Dr. Eirini Ntoutsi

 Prof. Eirini Ntoutsi (INF/CODE): An overview of fairness-aware Machine Learning [Paper1][Paper2] Arjun Roy (FU Berlin): Fairness in multi-task learning [Paper] Tai Le Quy (FU Berlin): Fairness-aware clustering models in collaborative learning [Paper]

18.01.2023, 16:30/18:00

 4th STAMMTISCH at Automated Vehicle-in-the-Loop and UniCasino
17.11.2022, 17:00/18:00 3rd STAMMTISCH at UniBw's computer museum datArena and Brandl
25.10.2022, 16:00 Prof. Oliver Rose (INF): Model-based Decision Making with Simulation or ML - Friends or Foes? Sonja Häffner (CISS): Building advanced objective dictionaries for the prediction of conflict
Johannes Flotzinger (BAU): Damage Recognition on Massive Constructions [Paper]
08.09.2022, 16:30/18:00 2nd STAMMTISCH at Automated Vehicle-in-the-Loop and Bar&Pizzeria da Giovanni
29.06.2022 Thomas Roßberg (LRT): Enable satellites to see vegetation through clouds with Deep Learning Joschka Kersting (CODE/Uni Paderborn): Human Language Comprehension — Extract, Classify and Weight Implicit Aspect Phrases like Humans Do Fabian Deuser (ETTI): Less Is More: Linear Layers on CLIP Features as Powerful VizWiz Model [Paper]
03.05.2022

State-of-the-art ML project presentation from Airbus and DesignAI (German):

ASTARTES – Wie AlphaStar die Art und Weise, wie wir Entscheidungen treffen, verändert
13.04.2022 1st STAMMTISCH at ETTI's MonacumOne GPU cluster and UniCasino
02.02.2022 Fabian Deuser (ETTI): CNN-based Audio Signal Processing and Beyond Moritz Dannehl (CODE): XFL: eXtreme Function Labeling Arthur Müller (SOWI): Post-Training and Fine-Tuning of BERT-Based Models for Political Language in German Tweets
08.07.2021 Martin Denk (LRT): Reduction of Image Rotation Variety using Moment of Areas for CNNs [Paper] Benjamin Haser (LRT): Analysis of Phobos internal Structure & SuperResolution  
28.04.2021 Sarah Rudigkeit (LRT): Artificial intelligence based cell-tracking for the evaluation of radiation effects in eucaryotic cells Simon Gottschalk (LRT): An Optimal Control Framework for Deep Reinforcement Learning  
11.03.2021 Peter Mortimer (LRT): Semantic Segmentation in Unstructured Outdoor Environments n/a Philipp J. Rösch (ETTI): Positional Information in Transformer-based Models for Language and Vision [Paper]
10.02.2021 Maren Hülsmann (LRT): AI4Space Moritz Dannehl (CODE): Using Machine Learning to Understand
Semantics of Binary Machine Code		 Philipp J. Rösch (ETTI): Multimodal Machine Learning: Processing Images and Text at the same time

 

Your orga team