Poster Presentations: Session 2

Poster Presentations: Session 2

Harnessing the Power of Machine Learning to Rapidly Transform LC-MS Spectra into the Identity and Absolute Concentration of Detected Metabolites
Mimoun Cadosch Delmar Akerman, Matterworks

Molecular Generative Neural Networks: Navigating Latent Vector Space to Create New Tools for Analysis and Prediction
Alex Clark, Ph.D., Collaborative Drug Discovery

Real Time LC-Automated Analysis and Assessment of System Suitability
Nicole Ferreira, M.S., Merck

Rapid AI generation of Optimised Compound Designs Guided by User Interactions
Tamsin Mansley, Ph.D., M.R.SC., C.Chem., C.Sci. (Optibrium Inc.)

ML Algorithm for Detecting Activated T Cells: An Automated Multi-Cycle Tracking Workflow
David Nizovsky, 100XBIO

Learning Microbial Growth Dynamics
Vasu Rao, University of Michigan

AI Driven Automation of Model Selection and Data Quality Control in SPR Production Screens
Daniel Siegismund, Genedata AG

Generative AI Automation and Enhanced Untargeted Drug Metabolite Analysis Using High-Resolution Mass Spectrometry (HRMS): A Case Study in Lipid Identification
Lalin Theverapperuma, Ph.D., Expert Intelligence

Representation Learning of Cell Painting Images in Combination with Biological Knowledge Graph
Zhiyong Xie, Xellar Biosystems