I'm a computer scientist focused on applying machine learning to early-stage venture capital in Europe.
My research interests also include web3, distributed systems, and information security.
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 effort focusing on deep learning approaches to natural language processing and understanding.
Deep learning for natural language processing
Attention is all you need
Artificial neural networks as universal function approximators
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
Smart contracts as objects instantiated on the blockchain
Solana is good for the sol
At Moonfire, we believe that pre-seed and seed capital is underfunded in Europe. Europe captures less than 20% of global VC capital despite representing over 25% of GDP. On top of this, the rate of European Series A investment is increasing faster year over year. At Moonfire, we're helping proliferate a strong pre-seed and seed ecosystem of breakthrough entrepreneurs using software, data, and machine learning.
Machine Learning for sourcing, screening, and evaluation
Venture fund modelling, forecasting, and simulation
Web3 venture capital
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.
Kubernetes
Search and recommendation
Consensus and coordination