Matthias Orlowski
As a Machine Learning Engineer at Bayer, Matthias Orlowski has contributed to various projects, focusing on natural language processing in pharmacovigilance and medical image processing in radiology and early drug discovery. Matthias studied in Konstanz, Nottingham (UK), Durham (North Carolina, USA), and Berlin, where he earned a PhD from Humboldt University in 2015. Prior to joining Bayer, Matthias gained diverse experience in multiple roles and organizations, tackling projects in consumer targeting, campaigning, and recommender systems.
Session
The visual exploration of large, high-dimensional datasets presents significant challenges in data processing, transfer, and rendering for engineering in various industries. This talk will explore innovative approaches to harnessing massive datasets for early drug discovery, with a focus on interactive visualizations. We will demonstrate how our team at Bayer utilizes a modern tech stack to efficiently navigate and analyze millions of data points in a high-dimensional embedding space. Attendees will gain insights into overcoming performance challenges, optimizing data rendering, and developing user-friendly tools for effective data exploration. We aim to demonstrate how these technologies can transform the way we interact with complex datasets in engineering applications and eventually allow us to find the needle in a multidimensional haystack.