Hi, my name’s Matt Lane. I’m currently a PhD candidate in Data Science at UTK while working in the Computational and Predictive Biology Group at Oak Ridge National Laboratory under Dr. Dan Jacobson.

Right now, my research focuses on using a mix of statistical methods, graph theory, and machine/deep learning to analyze and predict complex biological systems. Working at ORNL, I get to tackle these challenges with some of the most powerful computing systems out there: Frontier, Andes, Summit, and Perlmutter.

Some of the projects topics I’m currently working on include:

• Developing an LLM-powered, agent-based pipeline for automated gene set interpretation, integrating biological databases and literature mining to streamline systems biology analysis.

• Using Explainable AI to reverse engineer massive Predictive Expression Networks for Multiplex Omics models.

• Maintaining and Developing well-documented and tested scientific software packages for publication.

• Creating metabolomic profile networks by extracting peaks and processing LC / GC - MS data.

• Exploring topological perturbation in networks to predict phenotypic effects of genetic modulation.

• Applying geometric deep learning for node embedding and link prediction on large, sparse networks.

history

Before this, I spent some time as a software engineer at Bayer Crop Science, building software for collecting, storing, and analyzing crop data from the field after earning my M.S. in Computer Science at the University of Missouri–St.Louis, working with Dr.Sharlee Climer. My research there focused on network theory techniques to analyze cerebrospinal fluid metabolites in Alzheimer’s patients.

Prior to the masters work and working as a software engineer, I worked for the Missouri Botanical Garden doing educational outreach. Bugs and other critters don’t get as much love as they deserve.