Abstract
Building an interdisciplinary team set on bringing the sense of smell to computers
Highlights
On, it was clear we needed an interdisciplinary team with expertise in bench chemistry, computational chemistry, machine learning, and machine learning interpret
Who were the players in this project, and how did you bring everyone together?. It was clear we needed an interdisciplinary team with expertise in bench chemistry, computational chemistry, machine learning, and machine learning interpret
We grew the team slowly, starting first with core technical skills, and focused on a narrow scientific challenge for over a year — can we predict what a molecule smells like? Eventually, as we took on more work and harder challenges, we came to need non-technical roles like program management, and business negotiation
Summary
It was clear we needed an interdisciplinary team with expertise in bench chemistry (to recognize whether molecules are safe or harmful, and easy or hard to make), computational chemistry (to model the behavior of molecules), machine learning (to make novel and highly accurate predictions on chemical data), and machine learning interpret-. We grew the team slowly, starting first with core technical skills, and focused on a narrow scientific challenge for over a year — can we predict what a molecule smells like? As we took on more work and harder challenges, we came to need non-technical roles like program management (to keep multiple interlocking projects and partners on track), and business negotiation (to gain access to new data and problems). Did you encounter any challenges or any benefits of working with people from different backgrounds and expertise?. We spend a lot of ‘virtual’ time in cross-functional teams, drawing on very different expertises and perspectives. A book that has inspired a lot of how I think about building and running diverse teams working on a complex problem is ‘‘Team of Teams’’ by General Stanley McChrystal
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