Lifetime of Achievement: Daphne Koller

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Daphne Koller
AI Magazine examines the life and legacy of Daphne Koller, as she continues the advancement of digital learning and utilising AI within biomedicine

More than 30 years ago, Daphne Koller was the first machine learning hire in Stanford University’s Computer Science department. Now, she is a celebrated professor, thought leader and biomedical machine learning pioneer.

In addition to being well-known for her contributions to computer science, machine learning and biomedical engineering, Daphne co-founded online education platform Coursera with Andrew Ng in 2012. Until 2016, she served as the organisation’s co-CEO and President, democratising access for all to achieve a world-class education.

Koller also co-founded the digital learning platform Engageli and currently serves as a board member for the organisation.

A pioneer in AI biotechnology

Completing her PhD at Stanford University in 1993, Daphne’s research interests are primarily in representation, inference, learning and decision-making and their applications to computer vision and computational biology.

Her work in this field led her to be elected a member of the National Academy of Engineering in 2011 for contributions to probabilistic models with applications to robotics, vision and biology. 

After leaving her position as Chief Computing Officer at Calico (an Alphabet subsidiary) in 2018, she founded Insitro, a startup organisation committed to drug discovery and development. As founder and CEO, Daphne oversees the organisation’s processes, which includes fusing machine learning and genomics to predict and test treatments for diseases.

Daphne has also been the recipient of numerous awards and accolades, including the MacArthur Foundation Fellowship in 2004 and the ACM Prize in Computing in 2008. More recently, she was made a fellow of the American Academy of Arts and Sciences in 2014 and a member of the National Academy of Sciences in 2023.

With the healthcare industry seeing increasing difficulties in medicine development, Daphne states that the key will be to train powerful machine learning techniques on enough high-quality data to succeed.

“We believe that, for many of these phases, we can develop machine learning models to help predict the outcome of these experiments and that those models, while inevitably imperfect, will outperform predictions based on traditional heuristics,” she says on her LinkedIn.

Insitro: Producing data at scale with machine learning

To achieve this goal, Daphne is spearheading the construction of a diverse team that spans numerous disciplines within life science and machine learning. The company brings together cutting-edge methods in functional genomics and lab automation to build a bio-data factory that can produce relevant biological data at scale, allowing it to create large, high-quality datasets that enable the development of novel ML models. 

“I think we’re only beginning to appreciate the impact that [machine learning technology] will have,” Koller said in an interview with Fierce Pharma. “This is not a niche technology. It’s going to be like computers - you’re going to use it in every place, and the value of the technology will be limited primarily by your imagination of where it can be deployed.”

Likewise, at an event in San Francisco in 2023, Daphne said: “We need to create systems that are trained using reinforcement learning on not just any people, but on students who are in the process of learning.”

insitro aims to bring together high-quality data from humans, whilst also developing cutting-edge methods that can produce large amounts of in vitro data relevant to human disease and therapeutic interventions.

Daphne explains how AI and quantitative biology are merging to create digital biology, a pioneering field, saying: “This is the ability to read the biology digitally at this incredible fidelity at an unprecedented scale, interpret what we see using tools such as machine learning and AI, and then write biology using techniques like CRISPR and combinatorial chemistry, and all sorts of other things to make biology do things that it wouldn't otherwise do."

This new area will have “repercussions in human health, but also in the environment, in energy, in bio-materials, and sustainable agriculture, and many other disciplines that will help make our world a better place, which is why I think it's a really exciting place to be.”

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