// investment associate · deep tech · neuroscientist · builder
About
I'm an Investment Associate at Midlands Mindforge, an early-stage VC investing in life sciences and deep tech and partnered with 8 universities in the UK. My job is finding & backing founders who are changing the game with science.
I'm a / person - an interdisciplinary PhD in neuroscience & mechanical engineering across two institutions - Brighton & UCL. Wearing many hats necessitates ruthless efficiency. So if a process is manual, I automate it, and if I have a lot of data, I visualise it to uncover the patterns.
I specialise in university commercialisation — cultivating relationships with academic researchers as they're navigating the commercialisation process. In early-stage startups, I'm looking for substance over style.
Alongside my investment work, I build and automate workflows for investment teams, and coach peers and colleagues across my network on how to do the same. I also advise early-stage scientific founders when I have the right domain expertise - building in deep tech is hard enough and good science deserves a fighting chance.
Projects
Finds the biggest acquirers in a given industry, searches their press releases and provides a summary of relevant deals.
I've built a functioning community app to streamline dealflow processes for Alma Angels, an angel investor community focused on supporting female-founders.
A script to chunk large datasets, filter artefacts and visualise extracellular neuronal signals I recorded on an HD-MEA.
Automated monitoring pipeline that tracks portfolio companies across news, publications, and web signals, delivering structured intelligence rather than raw alerts.
An LLM-powered clustering system that analyses startup portfolios by problem-solution patterns, surfacing competitive landscapes and emerging opportunity spaces that traditional categorisation misses.
Research
Before I became an investor, I was a scientist. My research spans neuroscience, mechanobiology, and AI - published across high-impact journals with 641 citations and an h-index of 7.
I am most interested in ageing, memory and Alzheimer's disease. The through-line is the same regardless of domain: find signal in complex data and communicate it clearly.
I ran LLM quality control on this project, which turned out to be decent practice for what I do now.
First-author review on my exact areas of expertise. Ranked in the journal's top accessed and downloaded articles of 2021.
HD-MEA electrophysiology on human brain organoids — one of the more technically demanding projects I've worked on, from an analysis perspective. See: 03 custom analysis scripts.
Writing
Investigating why AI companies remain unprofitable despite massive investment and user adoption, examining how inference costs create unfavorable unit economics.
Talking about how I decide when to use AI tools to automate work tasks versus when to preserve hands-on learning, with case studies from venture capital due diligence.
Deep dive into the neuroscience therapeutics landscape, exploring how to evaluate novel mechanisms of action in brain-focused biotech companies.
Exploring the emerging field of DNA-based data storage, where biological molecules become the next frontier for long-term information storage.
Analysis of antibiotic resistance and the economic incentives shaping pharmaceutical development in infectious disease.
Always open to an interesting conversation. Reach out if you want to work together.