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Stef van Grieken

Co-founder & CEO - We're hiring!

Stef van Grieken is a seasoned professional with a diverse career spanning various leadership roles in prominent organizations like Google and start-ups.

With a background in Industrial Engineering and Philosophy from the University of Groningen, Stef has a strong educational foundation that complements his extensive work experience.

As a Senior Product Manager at Google AI (Brain), Stef has overseen product management for teams exceeding 90 members with budgets exceeding $50 million, showcasing his robust leadership and strategic skills.

Having worked in Europe and the United States, Stef brings a global perspective to his work, leveraging his cross-cultural experiences to drive innovation and success.

His areas of expertise include automotive, transportation, mapping, operating systems, and machine learning, reflecting a comprehensive knowledge base across diverse technology domains.

Stef has held key positions such as Co-Founder & CEO at Cradle, Angel Investor at Operator Exchange, and various Senior/Product Manager roles at Google, including in Artificial Intelligence, Automotive, and Special Projects.

He has also contributed to social impact initiatives through his role as a Technical Program Manager at Google and as Chairman of the Board at Open State Foundation, showcasing his commitment to community engagement and innovation.

Moreover, Stef's experience as a Founder in Residence at Startupbootcamp and as a Policy Advisor at the European Parliament highlights his versatility and expertise in navigating different professional arenas.

For investment opportunities, Stef invites individuals to explore options at operator.exchange, underlining his active involvement in the investment landscape.

Highlights

Aug 29 · linkedin

One of the harder issues we had to solve in building Cradle was to bring together a team of people from two very complex disciplines and get them to work together productively. I spoke to bio-it world on building teams at the intersection of technology and biology.

Aug 19 · linkedin

We are still very early in machine learning for protein engineering. A core belief we have held at Cradle is that the only way to build a high quality product with best in class generative models is to invest in a low-latency, high throughput lab. This lab allows us to build 'foundational datasets', a/b test new releases of our models and demonstrate generalisation across many protein modalities (i.e. enzymes, antibodies, car-t's, peptides etc).

Two years ago we set a high bar: we wanted our lab to be able to complete an experimental round in 2 weeks, at 384 throughput for many different assays. This meant trying to reduce latency in every step of our DBTL cycle.

In this blog series we share the methods we developed. This month: express and purify 384 variants in just 3 days of relatively light lab work and not breaking the bank. The protocol is added to the blog-post. Give it a try and feel feel to ask us questions!

Follow Cradle for more methods being published to speed up your research and development.

The blogpost with protocol link is in the comments!

Stef van Grieken
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Location

Zurich, Zurich, Switzerland