Hi, I'm Mo.

I work across scientific machine learning, applied AI, and agentic systems. During my PhD, I focused on the application of machine learning in computational neuroscience, using deep neural networks, latent variable models, and implicit neural representations to better understand the visual system.

At Noselab, I work on data-driven medicine: analyzing clinical data for biomarker discovery, building reproducible analytical pipelines, and developing AI workflows that help people navigate scientific evidence and internal knowledge.

Outside work, I build tools around human–AI collaboration and explore how people can work with agents and be more productive without giving up control and understanding. I like turning complex ideas into practical tools and learning from how people actually use them.

Want to compare notes or work on something together? Find a time to chat or send me an email.