When I share that I help VCs with technical due diligence focused on AI, I often get asked about my background and how I got started in this.
Maybe not surprisingly now, but it’s been a great way to put my unique background in academia and industry and start-up experience to use. :)
As an operator with 10+ years as an IC and Data Leader, I’ve invented, developed, scaled and supported AI algorithms to answer business questions in real-time across industries and globally – and gave talks about the "good, bad and ugly" of doing so at a number of conferences.
As an educator, I’ve also created a graduate course and taught 80+ graduate students over 3 years on software development best practices for how to do the same .
I’ve helped VCs and accelerators with pitch deck due diligence focused on DeepTech in AI and IoT.
I know first-hand the challenges and trade-offs in developing AI algorithms to improve a company’s product-market-fit. Now I help VCs evaluate this.
Fun Fact: I have a PhD in Statistics from UCLA, where I developed a novel image compression algorithm and uncovered similarities between two storms on Jupiter -- a finding confirmed by NASA’s Juno mission 6 years later.