Summary
Panagiotis Papasaikas is a research scientist in Basel with 10 years of experience applying machine learning and statistical inference to genomics and transcriptomics, focused on gene regulatory networks. He leads integrative analyses of high-throughput omics to study development, cell differentiation and reprogramming at FMI-NIBR, building pipelines that combine RNA-seq, iCLIP, ChIP-seq and ribosome profiling. His background spans probabilistic graphical models, EM-based semi-supervised methods and regularization techniques developed during PhD and postdoctoral work at Carnegie Mellon and CRG, with a long-standing emphasis on splicing and post-transcriptional regulation. He has a track record of translating complex statistical methods into reproducible analysis workflows and visualizations used in network-based studies. Based in Switzerland, he blends deep computational expertise with domain knowledge in molecular biology, enabling cross-disciplinary collaboration between wet lab and data science teams. An underappreciated strength is his sustained focus on method-driven software for interpretable regulatory network reconstruction rather than black-box prediction.
10 years of coding experience
7 years of employment as a software developer
National Center for Scientific Research "Demokritos"
PhD, Computational Biology, PhD, Computational Biology at Carnegie Mellon University
B.Sc, Biology, B.Sc, Biology at Ethnikon kai Kapodistriakon Panepistimion Athinon / University of Athens
English, French, Greek, Spanish