🧬 Quitting Physics to Treat Biology Like an Engineering Problem | Richard Yu (Part 1/4)

What It Covers

Richard Yu, cofounder and CEO of Abalone Bio, traces his path from physics undergraduate at UC Berkeley in 1989 through structural biology at Yale and systems biology at the Molecular Sciences Institute, revealing how immigrant upbringing, interdisciplinary training, and serial exposure to entrepreneurial culture shaped his approach to biotech founding.

Key Questions Answered

• •Interdisciplinary entry strategy: Switching from physics to biophysics at Berkeley reframed biology from an observational science into an engineering discipline — a mental model Yu applies directly at Abalone Bio today. Founders with physics or engineering backgrounds should actively seek biology problems where first-principles thinking creates structural advantages over purely observational researchers.
• •Mentor selection over prestige: Yu chose his Yale postdoc advisor Axel Brünger and later Roger Brent at MSI based on intellectual alignment and applied focus, not name recognition. Early-career researchers benefit more from mentors building genuinely new frameworks — Brünger was simultaneously writing code and pipetting at midnight — than from attaching to established academic brands.
• •Cofounder compatibility signal: Yu identifies a specific early signal for cofounder fit with Gustavo Pesce: independently discovering they had both programmed identical text-based Space Invaders games on Apple II computers as children. Shared cognitive instincts and problem-solving defaults — not just complementary skills — predict durable cofounder relationships under startup pressure.
• •Radical honesty as leadership tool: Yu's cofounder modeled direct feedback by publicly telling Yu his conference talk was poor immediately after others offered false praise. Founders should build cultures where honest critique is delivered promptly and specifically — naming what failed and why — rather than allowing politeness to mask performance problems that compound over time.
• •Computational-experimental fluency gap: Yu observes that researchers equally comfortable with wet lab work and quantitative data analysis remain surprisingly rare even in 2024. Biotech founders who deliberately develop both skill sets — as Yu did from Berkeley through Yale structural biology — gain durable advantages in designing experiments and interpreting biological data at the systems level.