Munich Datageeks January Edition

We are thrilled to announce our next Meetup on January 25th at CIB software.

Format:

• 2 talks (each ca. 40 min incl. discussion)
• Time for networking + food + drinks before, in between and after the presentations
• Talks are held in English
• We will be taking photos and film footage at the event. These will be used to share news about our meetups and to publicize upcoming events.

The lineup:

Talk 1: Konrad Grosser - Pretraining Multimodal Transformers for Document Understanding

Abstract:
The talk gives a historical overview of AI training based on concrete previous projects. It then describes the state of the art in vision transformers and bimodal transformers, and explains some principles for pre-training large multimodal transformers for document understanding. These are illustrated with examples from the RIDMI research project, which is currently carried out jointly by CIB and Fraunhofer IAIS.

Bio:
Konrad Grosser is currently a Senior Data Scientist in the AI team of the CIB Group. He studied mathematics at the ETH Zurich and holds an MScs in population genetics from the University of Vienna. Before joining the AI team at CIB, he worked as a research scientist in statistical genetics at the LMU, focusing on the population genetics of hematopoietic neoplasms. He has a broad interest and experience in machine learning and statistics, with a focus on automated document lifecycle management.

Talk 2: Florian Haselbeck - Advancing Synthetic Protein Design with Large Language Models

Abstract:
Accurate prediction of protein properties is an essential task in many areas of biotechnology, including enzyme engineering and protein-hybrid optoelectronics. In recent publications, approaches based on protein language models have shown superior performance both in predicting protein function and structure and in generating novel sequences. In this talk, we will show the benefits of large language models for predicting protein thermophilicity and thermostability, and give an outlook on how these models will revolutionize the design of synthetic proteins.
Bio:
Florian is a research assistant at the Professorship of Bioinformatics at the TUM Campus Straubing for Biotechnology and Sustainability. He recently received his PhD in Machine Learning for Time Series Forecasting. Before starting his PhD, Florian worked as a data scientist and software developer at Audi AG. He holds an M.Sc. in Computer Science and IT Management and a B.Eng. in Mechatronics.