Welcome
I'm Andrew. My career focuses on power infrastructure and the role of energy in society, and I am currently working on the opportunities and problems that accompany advances in the capabilities of AI systems. This site covers the topics that don't fit neatly on my LinkedIn page. You can reach me there or by email.
I have had a succession of commercial roles in the power sector, ranging from derivatives trading to power plant management to global corporate strategy. I have degrees in Physics and Technology and Policy, and a chief concern of mine is relating those disciplines to each other. Since 2018 I have been affiliated with the MIT Energy Initiative and have had a taste for what academic research is all about. I run BrainWander with a friend, and I participate actively at the Boston MFA.
Some topics top-of-mind for me:
- How soon will ASI arrive, and what can we do with AI in the meantime?
- Who captures the most value in the economic chain from primary energy to commercial computation?
- How can modern portfolio theory be adapted to drive investments in physical infrastructure and real estate?
Recent Activity
Grid impacts of highway electric vehicle charging and role for mitigation via energy storage
The buildout of EV charging networks is necessary to address consumer range anxiety concerns, but also may apply localized stress to the power grid. This paper specifically shows the necessity of u...
Energetica: An intuition pump for the role of energy in human activity
The relationships between the economy, energy, and sustainability feel at once obvious and slippery. Energetica is an ongoing effort to show how energy maps *fundamentally* to the economy. It's also the closest I've come to connecting a Physics education to an Energy career. (Beyond that, Energetica is a fun web simulation that pushes the limits of browser-based computation.)
Mosaic: Hyper-personalized graded reading with spaced repetition
Advances in generative AI have massive consequences for language learning. Mosaic harnesses GenAI to bridge the gap between vocabulary flashcard practice and natural reading fluency by building bespoke reading passages and integrating reading with SRS. It's an evolution for me as a long-time Anki user and language learner.
Bookie: Structuring data from an LLM's latent space
Can we take advantage of the omniscience of AI to create useful (though flawed) novel datasets? Bookie is a modern web app and experiment in using LLMs to synthesize a multidimensional "book landscape" that supports syntopic reading. It's a great tool for learning more about the book you're reading and for putting the next one on your list, and it's a showcase of automated content generation.