Moberg Minds: Tony Okeke

Hi, I’m Tony, and I’m a Machine Learning Engineer at Moberg Analytics. I started here in August 2024 after completing my BS and MS in Biomedical Engineering at Drexel University with concentrations in Neuroengineering and Bioinformatics. My path into machine learning was shaped by early experiences at Penn Medicine and GSK. At Penn Medicine, I worked as a research assistant studying COVID progression in ICU patients and identifying biomarkers for patient outcomes. At GSK, I built models for analyzing RNA sequencing and spatial transcriptomics data. Those roles showed me that I could channel my (admittedly obsessive) love for programming into work that genuinely helps people.

At Moberg, I’m something of a generalist – I work on whatever the company needs, which keeps things interesting. Most days, that means full-stack development on the Moberg Clinical Platform, building new features to support our customers. I’ve also spent significant time developing models to detect artifacts in neurophysiological waveforms. One of my proudest accomplishments here has been leading development on ACME, a body-worn sensor suite for collecting data from medics and patients on the battlefield. I taught myself Kotlin from scratch and built the entire application in about six months, which reinforced just how much I love tackling unfamiliar challenges. More recently, I have been leading development on our Critical Care Copilot, an AI agent designed to interact with our platform’s analytic tools in order to assist clinicians in managing patients.

What draws me to this work is the opportunity to make a tangible impact at a startup where contributions are visible and meaningful. Knowing that what I build directly affects patient outcomes is incredibly fulfilling. Outside of work, I spend most of my time coding for fun, experimenting with large language models, or diving into niche technical rabbit holes. On weekends, you’ll probably find me grilling steaks and watching UFC fight nights with my friends.