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The second roundtable discussion of this quarter was held before Prof. Bin YU (UC Berkeley, Stat)'s Joint Math/Stat Colloquium talk: Veridical Data Science. Her talk slides can be found here.

The roundtable discussion kicked off by the host asking the guest speaker about the status of data science activities at the Berkeley campus.

The format of our roundtable discussions for Winter 2020 has been changed from that of Fall 2019: we have decided to have a roundtable discussion once a month instead of every week, and schedule it before a seminar talk with refreshments instead of after a seminar talk.

Happy New Year to you all!

I just recently found out two potentially quite useful websites for people who are interested in data science and machine learning.

(1) Nextjournal https://nextjournal.com/ : allows you to develop you notebooks for reproducible research and publish them or share them with your collaborators.

The tenth and final roundtable of the quarter was held after Krishna Balasubramanian’s Statistics seminar talk, “Normal Approximations for Stochastic Iterative Estimators (and Martingales)”. His talk slides can be found here.

The first part of the roundtable followed a question and answer format, so we recreate that here.

I found the following article on Ars Technica: https://arstechnica.com/science/2019/12/how-neural-networks-work-and-why-theyve-become-a-big-business/ quite interesting and well written although the author does not trace some important history of the development of neural networks such as K.

Our ninth roundtable discussion took place after Javad Lavaei’s MADDD seminar talk “Computational Techniques for Nonlinear Optimization and Learning Problems”. His talk slides can be found here.

Our eighth roundtable took place after Grace Yi’s statistics seminar talk “Making Sense of Noisy Data: Why and How?” Her talk slides can be found here.

- Henry Kautz, Division Director, NSF/CISE/IIS

THE WHITE HOUSE

Office of Science and Technology Policy

FOR IMMEDIATE RELEASE
November 20, 2019

White House OSTP Releases Progress Report on Advancing AI R&D

Here is a slightly old (July 30, 2019) article on the Julia Programming Language in the journal Nature: https://www.nature.com/articles/d41586-019-02310-3 .

It's a very good short read! You may want to try out Julia if you haven't.

So, enjoy!

Our seventh roundtable discussion took place after Rishidev Chaudhuri’s MADDD seminar talk “Noise driven synaptic pruning.” The topic of the roundtable discussion was: Challenges and future of graph/network data analysis in neuroscience. It was conducted in a Q&A format between the host and the speaker with responses from the audience.

See the website https://insights.dice.com/2019/11/13/mathematicians-engineers-jobs-november/

Have a great weekend!

Our sixth roundtable took place after Thomas Strohmer’s talk “A Rigorous Framework for Data Clustering”. His talk slides can be found here.

Dear all,

This long weekend, you may be interested in watching the following timely and interesting PBS program: In the Age of AI, which traces a new industrial revolution that will reshape and disrupt our lives, our jobs and our world, and allow the emergence of the surveillance society.

Have a wonderful weekend!

Naoki

Our fifth roundtable discussion took place after Yu Zhang’s talk “Improving Power Grid Reliability and Efficiency via Advanced Signal Processing and Machine Learning”.  His talk slides can be found here.