Law Does Not Return a Boolean
Fidryn is a proposed programming language for legal instruments: precise where law is mechanical, explicit where judgment enters, and incapable of hiding authority, discretion, or ambiguity inside a Boolean.
Senior ML research scientist / Boston, Massachusetts
I build learning systems and think about memory, agency, and control.
I’m a senior machine learning research scientist working where learning systems meet information theory and dynamical systems. Most of my questions begin with a simple one: what lets an intelligent system carry experience forward?

Selected work
Work / 01
Fidryn is a proposed programming language for legal instruments: precise where law is mechanical, explicit where judgment enters, and incapable of hiding authority, discretion, or ambiguity inside a Boolean.
In progress
A few problems I keep returning to.
I am interested in models that can carry useful experience across very long horizons without making memory prohibitively expensive.
What would it take for an agent to keep learning after deployment—to accumulate skills, revise its world model, and remain useful over time?
I use ideas from control and information theory to ask how intelligent systems gain influence, and how they might do so without diminishing ours.