How Alexander Johansen is Pioneering the Role of ML in Health and Bio Science | Experiment Exchange
Machine learning holds significant promise for fields like proteomics, therapeutics, and more—but blockers like access to datasets and issues of health privacy make progress complicated.
Alexander Johansen is a Ph.D. student in computer science studying the intersection between computer science, bioinformatics and digital health. Within his lab at Stanford University, Alexander has applied Natural Language Processing to proteins, explored the history of wearables data privacy, and more.
In this episode, SigOpt’s Head of Engineering Michael McCourt speaks with Alexander about his pioneering work and how SigOpt has played a role in advancing progress.
1:29 - Intro
2:09 - What Alexander's lab works on
5:40 - Who makes up Alexander's team
8:39 - Should only the FDA be involved?
12:31 - NLP for proteomics
17:44 - How Alexander uses SigOpt to power his research
21:24 - How Alexander collaborates with other areas of study
24:28 - Picking the right health data to prioritize
Follow Alexander on Twitter: / alexrosejo
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✔️ Learn more about SigOpt: https://sigopt.com
✔️ Learn more about the Stanford Center for Personalized Health: https://stanford-health.github.io/
✔️ Follow us on Twitter at / sigopt
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