I'm a computer scientist professionally focused on applying deep learning for natural language to founder and company evaluation objectives within the early-stage venture capital domain.
My core research focus is on deep learning and natural language processing but I'm also passionate about distributed systems and cognitive science.
I'm also an extremely psyched skier and climber. I'm a strong advocate for the power of the outdoors to help people develop meaningful human relationships through shared experiences in the mountains.
I've been working with distributed data systems and data analytics for my entire career. For the past several years, I've spent most of my professional and scientific effort focusing on deep learning approaches to natural language processing and understanding. I'm especially interested in novel techniques for training deep learning models to perform well within data-constrained domains.
Transformer-based Natural Language Processing
Data-constrained deep learning
Multitask multimodal deep learning
Artificial neural networks as universal function approximators
I've spent a significant majority of my career working on large, stateful, distributed systems in high-throughput production environments. Within the stack, I'm really passionate about coordination and communication protocols, performance (of both systems and engineers), and autonomous infrastructure operations.
Search and recommendation
Consensus and coordination
Given my background working with distributed systems, cryptography, and economics, my personal mental model of blockchains is one of Byzantine fault tolerant distributed systems with cryptographic verifiability and economic security.
A consensus and validation approach to blockchain architecture
Solana validator infrastructure and staking tooling