Partner
Lux CapitalCheck size: Firm-level: Lux says it can invest from an initial $100K through high-conviction follow-ons as large as $100M across the company-building arc. This is not Lan's personal standard check range.
Lan is a Lux generalist with a defined intersection across computation and biology: computational analytics in biotech and healthcare, data and ML infrastructure, platform therapeutics, developer tooling, and AI applications. Her investment lens centers on scrappy, independently curious underdogs working at technical frontiers and developing knowledge through experimentation rather than consensus.
Scrappy, independently curious founders—especially underdogs—building at the frontier of what is technically possible. Her own research history and chosen maxim emphasize empirical learning, while Lux favors brilliant scientists and engineers pursuing fields others consider too hard, too early, or too confusing.
No personal pass criteria are public. Her published lens implies weaker fit for consensus-following teams without independent curiosity, claims unsupported by experiments, and products lacking a meaningful frontier in computation, biology, infrastructure, tooling, or applied AI.
Bring the experiment, not only the vision: explain the technical or scientific unknown, how you tested it, what the evidence changed, and which next experiment most efficiently reduces uncertainty. Show independent insight, why the platform compounds across products or datasets, and how the team connects computational depth to a real healthcare, developer, or industry workflow.
Identify the most consequential technical unknown, design an efficient experiment that can change the team's beliefs, and use the evidence—not field consensus—to choose the next frontier to pursue.
Test whether data, models, developer infrastructure, or computational analytics create a compounding advantage in biological understanding, therapeutic development, or healthcare execution rather than a one-off analysis.
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Lan's hands-on research has spanned glioblastoma segmentation, nanocomposite fluid-flow simulation, Alzheimer's drug therapies, and other computational and scientific work. She earned a Stanford BS in Computer Science in two and a half years, graduating at the top of her class as Phi Beta Kappa. At Stanford she co-directed TreeHacks and served as Managing Partner of Dorm Room Fund, where she founded the Female Investors' Track and led the Female Founders' Track.