DJ Patil

Dr. DJ Patil is a Data Scientist in Residence at Greylock Partners.

He has held a variety of roles in academia, industry, and government. These include the Chief Scientist, Chief Security Officer and Head of Analytics and Data Teams at the LinkedIn Corporation. Additionally he has held a number of roles at Skype, PayPal, and eBay.

As a member of the faculty at the University of Maryland, his research focused on nonlinear dynamics and chaos theory applied to numerical weather prediction. As an AAAS Science & Technology Policy Fellow for the Department of Defense, Dr. Patil directed new efforts to leverage social network analysis and the melding of computational and social sciences to anticipate emerging threats to the US. He has also co-chaired a major review of US efforts to prevent bioweapons proliferation in Central Asia and co-founded the Iraqi Virtual Science Library (IVSL).

More details can be found on his LinkedIn profile and he can be followed on Twitter (dpatil).

Be Mr. Knapp

My commencement address at the iSchool at Berkeley.

I would have never in my life thought I would have been asked to give a commencement speech. This year when I was asked again (last year’s is here), I was once again caught off guard….
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How we can consumerize health care

The Zero Overhead Principle can bring lessons from the consumer space to health care.

Recently I wrote about one of my key product principles that is particularly…
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Data Jujitsu: The art of turning data into product

Data Jujitsu: The art of turning data into product

Smart data scientists can make big problems small.

Having worked in academia, government and industry, I’ve had a unique opportunity to build products in each sector. Much of this product development has been around building data products. Just as methods for general product development have steadily improved, so have the ideas for developing data products. Thanks to large investments in the general area of…
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Building data science teams

Building data science teams

Data science teams need people with the skills and curiosity to ask the big questions.

A data science team needs people with the right skills and perspectives, and it also requires strong tools, processes, and interaction between the team and the rest of the company.

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