About

I founded and run Talos, a public benefit corporation developing new wet-lab research models and AI systems to accelerate biomedicine. We're currently in stealth. I am always looking for cracked drug hunters, engineers, and operations people. hello@talos.bio

I also direct biotechnology investments at Starbloom Capital, where I invest at the intersection of biology and AI and manage a portfolio of 25+ companies. I look for technologies that become possible or substantially more useful as AI improves. I'm equally interested in the parts of drug development and medicine that greater intelligence alone won't accelerate, and what it would take to remove those bottlenecks. Lastly, I'm interested in near-term (clinical stage) high-leverage (large indication) longevity therapeutic interventions that can help to pull the most people possible into the incredible future that lies around the corner, such as promising treatments in neurodegeneration, pan-oncology, frailty, and cardiometabolic disease.

Some of the questions that interest me as an operator and investor:

  • How do we use AI to cure all disease in the next 20 years? What needs to be built besides AGI?
  • How do we enhance our intelligence and cognitive flexibility to keep up with AI?
  • How do we do more top-down human biology? I am partial to starting from what we actually want to study and subtracting the minimal number of pieces necessary to get to something tractable, rather than going bottom up from molecular hypotheses or cells in a dish.
  • Can we program cell therapies to do much more impressive things, such as automatically home to sites of damage, clear the damage out, and differentiate into new tissue in situ?
  • Can we get much better at gene therapy? Can we develop BioShock-style plasmids to customize and enhance ourselves?
  • Can we build artificial wombs? Reversible cryo-sleep? Tricorders? Mind uploading? What are the technology trees that lead us to utopian sci-fi futures?

Previously, I was a postdoc and research fellow at Stanford University and EMBL, working on a successor to image-enabled cell sorting. The project aimed to enable higher-resolution imaging, image-based single-cell barcoding, and on-device computer vision for sorting cells. My work included training convolutional neural networks, developing algorithms to compress them, and optimizing them to run more efficiently on the FPGAs used by modern cell sorters.

Prior to that, I earned my Ph.D. at Stanford in the Genetics and Neuroscience departments co-advised by Tony Wyss-Coray and Stephen Montgomery. My thesis research developed new methods to measure the aging of organs and cells in the body with proteomics, as well as new biomarkers for neurodegenerative diseases. My publications are on Google Scholar.

Outside work, I like arduous outdoor adventures and type-2 fun, video games, novel experiences, making new friends, and playing music, especially guitar and violin.