CV ↗ Thesis ↗ Linear Algebra ↗

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Hi, I’m Alex Loftus. I am a textbook author, communicator, kaggle competition winner, and PhD student with David Bau’s group. I am interested in understanding how we can use techniques from interpretability in code models to understand training dynamics, steer large models at inference time, reduce hallucinations, and create truly customized systems. I have worked as a data scientist, a machine learning engineer, and as a master’s student in biomedical machine learning at Johns Hopkins University.

I’ve been fortunate to work with a number of brilliant people over the years. Here are some fun projects which resulted:

I have a number of academic side-interests, including spectral theory, information geometry, the history of science and mathematics, the mechanics of the visual system, constitutional law, various causal relationships between geography and history, and ethics (I am a big fan of Kant, Hume, Ross, and some modern ethicists like Susan Wolf). I am an avid traveler and am (slowly) learning Spanish.

Misc

I grew up in Seattle, WA. I was a competitive Starcraft 2 player in high school (grandmaster league - competed/won in seattle-area tournaments!). I studied behavioral neuroscience during my undergraduate years, with a philosophy minor focused on ethics. I got interested in math and programming and started a computational neuroscience club, where I taught weekly seminars. I also spent a lot of time partner dancing and playing guitar at open mic nights!

Set up a meeting with me here: calendly.com/alexloftus2004

Talks & Publications

Recent Posts

October 10, 2024
Formalizing Lesswrong-Style Science
Being Clear About What We’re Talking About
April 28, 2024
Research directions in interpretability
Research Directions in Interpretability
March 27, 2024
On mutual reciprocity in Relationships
On mutual reciprocity in relationships

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