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About Code Ocean

We’re living in the era of Computational Science

Computational Scientists are at the epicenter of breakthrough life science research today. We help them do their work.

Bioinformatics is more important than ever

Three trends make Computational Scientists some of the most important people working in Life Science R&D today.

Data Management Colour@8x Massive data A massive and increasing flow of heterogenous data from labs and public databases.
Cloud Compute@8x Cheap compute An abundance of relatively cheap cloud storage and compute, primarily driven by AWS.
Machine Learning Colour@8x AI/ML acceleration A significant acceleration of developments in data science, AI, and machine learning.

But it’s still a huge challenge to work in this discipline:

$ 28 B
Spent on non-reproducible preclinical research every year
74 %
Of publicly-available R files fail to run without errors
96.8 %
Of Jupyter notebooks aren’t reproducible as documented
Accent image

That’s why we’ve built the industry standard for computational Life Science R&D

Compute Scalability@8x Easy to provision and scale in the cloud Launching something in the cloud is difficult and frustrating if you don't know how, or if you don't have the support. It should be easy to start and scale.
Collaboration@8x Simple to work together with peers

It should be easy for computational teams to work together. Nobody should need to say or hear "but it works on my machine" ever again. 
Reproducibility@8x Fully reproducible, traceable, and reusable

Reproducibility and traceability is vital for progress. It's also important for quality assurance, publications, mergers and acquisitions, and the FDA...
Data Architecture@8x Avoids tech debt, improves architecture

Inconsistency in environments, data, and versions compound over time. It should be much easier to have solid data architecture without slowing down.

Our mission is to champion the Computational Scientist

The people working at the intersection of data, science, and mathematics are already making incredible breakthroughs. We're here to help them make even more.

Read our origin story

The Code Ocean Leadership team

Simon Adar

Co-founder and CEO

Simon Adar

Co-founder and CEO

Simon Adar

Simon is the co-founder and CEO of Code Ocean. He is a researcher turned entrepreneur who founded Code Ocean as part of his postdoc at Cornell-Tech, Cornell University. His background is in signal and image processing, hyperspectral imaging, and spectroscopy. During his PhD, Simon worked with the German Space Agency (DLR) and other research institutions around Europe. Simon is passionate about research, scientific innovation, and cloud computing.

Ram Dayan

Co-founder and CTO

Ram Dayan

Co-founder and CTO

Ram Dayan

Ram is the co-founder and CTO of Code Ocean. Together with a founding team, Ram built the Code Ocean platform using cutting-edge technologies, bringing his 30+ years of programming experience from diverse industry fields. Prior to Code Ocean, he led software development at Picitup, developing various image processing applications, and at iOnRoad, where he developed an augmented driving mobile app, later acquired by Harman International.

Emma Supper

Co-CEO and CCO

Emma Supper

Co-CEO and CCO

Emma Supper

Emma Supper is Co-Chief Executive Officer and Chief Commercial Officer of Code Ocean. She trained as a scientist before moving into industry, earning a PhD in Medical Sciences from Kyoto University and conducting research at the Wellcome Trust Sanger Institute. Prior to Code Ocean, Emma held commercial and strategic leadership roles across the life sciences technology ecosystem, including positions at Illumina, uMotif, and Seven Bridges (Velsera), where she built and led global business development teams supporting major pharmaceutical and research organisations. In addition to her executive role at Code Ocean, Emma advises several emerging companies in the life sciences sector on commercial strategy and market development.

Daniel Koster

CPO

Daniel Koster

CPO

Daniel Koster

Daniel oversees product strategy, internal interfaces, and client-facing activities. Previous achievements include the development of a deep learning platform for plant trait phenotyping and patented software for early detection of disease symptoms in plants. He has two articles published on the cover of the esteemed journal Nature and over 1,200 citations. Daniel holds a PhD from Delft University of Technology and was a postdoctoral fellow at the Weizmann Institute of Science.

Want to help make it happen?

Join our team