Linus Liang

Linus Liang is a founder-turned-investor with more than a decade of operating experience across big data, mobile, gaming, medical devices, and social enterprise. He earned a B.A. in Computer Science from UC Berkeley and later returned to school at Stanford University, where he collected an M.S. in Computer Science, an M.A. in Education, and an MBA. Early in his career he worked as a database researcher at IBM and a Program Manager at Microsoft, and spent time on the investment team at Andreessen Horowitz.

As an operator, Liang co-founded CLZ Concepts, a server-scaling and social-gaming startup that pivoted onto Facebook and was acquired by Zynga within roughly a year — he joined as one of Zynga's earliest employees (often cited as the tenth). He is best known for co-founding Embrace, the maker of a low-cost infant incubator that sells for roughly 1% of the cost of a traditional unit (~$200 vs. ~$20,000) and can operate without constant electricity. He spent about five years living in India and China commercializing the device, which is credited with helping hundreds of thousands of premature babies across more than a dozen countries and earned recognition including a Tech Museum Award and an Economist Innovation Award, with backers such as Marc Benioff and Jeff Skoll.

Liang joined Signia Venture Partners after his Stanford MBA, starting as a Senior Associate and rising to Partner over nearly a decade. At Signia he concentrated on enterprise, AI, and data-infrastructure companies and supported portfolio names such as BlueTalon and Pepperdata. In 2023 he co-founded Kyber Knight Capital with fellow Signia veteran Sunny Dhillon, launching a $120M debut fund focused on pre-seed and seed investing in commerce, AI, and labor, backed by a marquee LP roster reported to include John Hennessy (Alphabet chairman), Michael Eisner, and Meg Whitman.

Alongside investing, Liang co-created and teaches Stanford Graduate School of Business courses on Big Data and Frontier Technologies, drawing on his distributed-systems research background and emerging-markets operating experience.

• Invests at pre-seed and seed, typically writing checks in the ~$500K–$3M range.
• Focuses on the application layer of AI — "where technology meets real work" — rather than the model or infrastructure layers.
• Looks for founders rebuilding long-static workflows in industries like healthcare, legal, and logistics: "These founders are using AI not because it's a trend, but because it finally allows them to solve a problem that people have been struggling with for years."
• Draws on his own operating and technical roots (enterprise, data infrastructure, big data) to back deeply technical teams.
• On his personal edge as an investor: *"I like helping founders prove something when everyone else says it can't work."*
• Prizes coachability in founders — listening deeply and accepting feedback: *"Conviction without self-awareness becomes a liability, not a strength."*