Tim Conrad

Dr. Tim Conrad is a researcher at the Zuse Institute Berlin in the Visual and data-centric computing department under the Mathematics of Complex Systems division. He leads projects at the intersection of computational biology, AI, and medical data analysis.

• Projects: Geometric Learning for Single-Cell RNA Velocity Modeling, MODAL MedLab, Sparse Compressed Sensing in -Omics Data, BIFOLD (Big Data and Machine Learning)
• Research Networks: Affiliated with MATH+ and MODAL Research Campus

His research focuses on applying machine learning, network optimization, and sparse data analysis to biological and medical challenges including disease modeling, microbiome dynamics, and ECG classification. Recent work explores hybrid PDE-ODE epidemic models and federated learning in healthcare.

2023-2025 publications highlight trends in AI for biological networks, temporal community detection, and medical signal processing. He co-authored studies on SARS-CoV-2 simulations, proteomics feature selection, and multi-label ECG analysis. His 2004 doctoral thesis at Monash University laid foundations for later work in metabolic pathway analysis.

Awarded as a Zuse Fellow, he contributes to open science initiatives like FAIR data sharing. Collaborations span institutions including Freie Universität Berlin and Charité in medical informatics and clinical applications.