General Assembly Meeting in Dresden

Mar 18, 2024, 9:30 AM → Mar 19, 2024, 3:45 PM Europe/Berlin

Dorint Hotel Dresden

Monday, March 18

9:30 AM Registration + Welcome Coffee

Welcome + Overview

Conveners: Prof. Erhard Rahm (Leipzig University / ScaDS.AI Dresden/Leipzig), Prof. Wolfgang E. Nagel (TU Dresden / ScaDS.AI Dresden/Leipzig)

Project News / Transfer & Service

Conveners: Dr Eric Peukert (Leipzig University / ScaDS.AI Dresden/Leipzig), Dr René Jäkel (TU Dresden / ScaDS.AI Dresden/Leipzig)

1 Robotics Lab

Speaker: Prof. Roberto Calandra (TU Dresden)

2 Deep Learning for the Analysis of Images and Text Data in Oncology

Speaker: Prof. Jakob N. Kather (TU Dresden)

3 Announcement

Speaker: Dr Eric Peukert (Leipzig University / ScaDS.AI Dresden/Leipzig)

11:15 AM Coffee Break

4 Pain Points of Developing AI-Enabled Systems in Industry

Speaker: Prof. Norbert Siegmund (Leipzig University / ScaDS.AI Dresden/Leipzig)

5 Hybrid Mixed Reality Interfaces for Immersive Data Analysis

Speaker: Prof. Raimund Dachselt (TU Dresden / ScaDS.AI Dresden/Leipzig)

6 Streamlining Data Sharing in Machine Learning with Dataverse

Speaker: L. Sherpa

7 PhD: Deep Learning for Acute Stroke Care

Speaker: Mrs Marie-Sophie von Braun (Leipzig University / ScaDS.AI Dresden/Leipzig)

8 PhD: Redefining ‘differential signalling’ in models of synaptic dynamics by considering transition states in spiking neurons with homogeneous frequency input spikes

Speaker: Mr Ferney Beltran Velandia (Leipzig University / ScaDS.AI Dresden/Leipzig)

12:55 PM Lunch

9 Breakout Sessions + Networking

1: Team Lead Session
2: Graduate School

3:55 PM Coffee Break

10 PI Session and Networking

11 Dinner

Tuesday, March 19

Track 1

12 Basics of HPC / Data Management: New Filesystems, Workspaces, Data Transfer

10:30 AM Coffee Break

13 Software Management: Module System, Virtual Environments / Running Programs: Batch System

12:00 PM Lunch

14 Parallel Hands-On Sessions

Prerequisites: to follow the hands-on session on HPC please have your ZIH login at hand.

A: Guided hands-on
- In the session, you'll receive ready-to-use notebooks to acquaint yourself with fundamental HPC features. Following this, you'll be equipped to start with your own research question using HPC. No prerequisites are required.

B: Consultancy with your own code/data
- Please bring your own pipeline/problem to work on, with the assistance of our HPC experts. We aim to help you with setting up your software stack, starting with distributed training, setting up an ML Ops workflow, investigating performance, and many more.

C: OmniOpt - Efficient Parallel Hyperparameter Optimization on HPC
-In this session, learn to optimize hyper-parameters (HPs) crucial for neural networks and other machine-learning methods efficiently. Explore OmniOpt, a specialized tool for TU Dresden's HPC cluster, designed to streamline HP optimization for various problems. Leveraging HPCs powerful GPUs, CPUs, and storage ensures swift handling of even large problems. We will cover (i) a brief HP optimization overview, (ii) hands-on OmniOpt usage with a practical example, and (iii) result evaluation using OmniOpt's toolbox. You are encouraged to bring your own code for optimization. 
Link: https://scads.ai/transfer-2/verfuegbare-software-dienste-en/omniopt/

Track 2

15 Discuss improvements for data sharing / common services

Speaker: Mr Matthias Täschner (Leipzig University / ScaDS.AI Dresden/Leipzig)

10:30 AM Coffee Break

16 Licensing of material

Speaker: Mr Robert Haase (Leipzig University / ScaDS.AI Dresden/Leipzig)

12:00 PM Lunch

17 Clean Code (Robert Martin)

Speaker: Mrs Mariia Tkachenko (Leipzig University / ScaDS.AI Dresden/Leipzig)