Please note that I am still building this section. It is my hope that in time this section will grow into a set of pages for each project that will allow me to present purpose, hypotheses, outcomes, but also associated thoughts about those project in a way that can go beyond that which is included in published papers or software source code. I have yet to add content for these thoughts and works in the area of de-risking deep-tech entrepreneurship, such as:
The OS Playbook: A data-driven approach to due diligence and de-risking for Angel and Venture Capital investment in deep-tech startups or in fund portfolios heavily engaged in deep-tech.
Applying rigorous decision analysis to Angel and early-stage VC investment, and to applied sci-tech development in general. An important component of this is to apply senstivity analysis to factors in the decision making process that have a range of uncertainty.
How to tackle the special challenges that come with partnerships between a scrappy technology startup and and pioneering academic labs.
Contrasting the unique strengths of R&D in a well-funded startup environment (e.g. create best-in class cross-disciplinary teams in minimal time) with those of an established university lab (e.g. persistence across significant time-spans in the pursuit of tested answers).
Knowing when a technology is ready for the transformation from laboratory demonstration to commercial deployment with successful market-fit and time-lines that survive the startup "valley of death".
Why a "moonshot" is precisely the wrong analogy for the "fail-fast" requirement that retains investment efficiency in ambitious startups.
Please check again to see content appear here about the topics above (as soon as I manage to schedule time for the necessary updates). If you already have questions for me about these topics, please feel free to contact me.