Our own Mariel Vazques (Math, Microbiology and Molecular Genetics) has been elected as an AMS (American Mathematical Society) fellow!

Congratulations, Mariel!!

Here is a very interesting short Youtube video showing the historical rankings of popular programming languages from 1965 to 2019. According to the author/creator, its data source was the combinations of aggregated statistics from several indexes, GitHub repository access, multiple surveys. Enjoy!

You may be interested in participating in the fifth annual Women in Data Science
(WiDS) conference at Stanford University, which will be held on March 2, 2020.

Dear UCD4IDS participants,

This conference is quite relevant for our activities, and I encourage you to consider submitting your work. The deadline for contributed lectures is quickly approaching: November 4, 2019. Please take a look at: https://www.siam.org/conferences/cm/conference/mds20 .

Sincerely,

Naoki

Our fourth roundtable discussion took place after the statistics seminar talk of Julie Novak (Netflix) on “Statistical Methodologies in Streaming Experimentation at Netflix”.

This discussion was conducted in the Q&A format, with the majority of questions about the structure of data science work at Netflix. We structure the note accordingly.

Q: What is the most pressing problem in data science and machine learning at Netflix?

The following survey conducted by IEEE-USA provides insight into how 26 countries approach AI and regulation of related technologies, and is an interesting read!

https://ieeeusa.org/volunteers/committees/aiaspc/ai-global-survey/

Cédric Villani, the 2010 Fields Medal Winner, and a member of the French Parliament, wrote the following intriguing article on AI, which you may be interested in checking out:

https://www.aiforhumanity.fr/pdfs/MissionVillani_Report_ENG-VF.pdf

Our third roundtable discussion took place after Meisam Razaviyayn’s talk on “Learning via Non-Convex Min-Max games“. His talk slides can be found here.

The following note summarizes the roundtable discussion.

The topics were the Challenges and future of nonconvex optimization, and the landscape of Data Science at USC, the speaker’s home institution.

Our second roundtable discussion took place after Pantelis Loupos’ Statistics seminar talk on “Starting Cold: The Power of Social Networks in Predicting Non-Contractual Customer Behavior". His talk slides can be found here.

The following note summarizes this roundtable discussion.

Michael Mahoney (UC Berkeley), the PI of the NSF-TRIPODS grant at UC Berkeley, wrote a very interesting two-part article on his view and experience on their TRIPODS endeavor in the current SIAM News. The Part II was just published recently. I strongly encourage you to read it. I nodded my head several times while I read this article: