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Tina Seelig: Creativity (Morning Mentors #2)
14 Jul 2018
talks research business

Qualifications: Management Science and Engineering Professor, Directory of Stanford Technology Ventures Program

Seelig’s talk on creativity has applications in entrepreneurship and research. It’s fascinating how something simple as reframing problems by asking what would change if I solved this problem can stimulate new ideas and jump-start creativity.

  • You gain knowledge by paying attention to the world and being more observant than ANYONE else
  • Knowledge is a toolbox for imagination. The more you know, the more you can work with. You need to know things deep enough to create metaphors for other areas
Richard Hamming: You and Your Research (Morning Mentors #1)
06 Jul 2018
talks research

Qualifications: Turing Award winner, Bells Labs Alumni, Hamming code inventor, Professor

One of the most important talks that I have ever watched about the nature of research and success by a giant of computing, telecommunications, and mathematics. Very rewatchable and tremendously inspiring.

  • You MUST Work on important problem in your field
  • Consider the implications of your work on the future, is it worth doing?
  • Turn defects into assets (digital vs. analog hamming differentiation)
  • Change the nature of the problem to find the underlying question and nature
  • Spend time studying related research domains (Jon Tucci studied all layers at Bell Labs)
  • Work on the right problem, at the right time. “…million races being run, just get in one and win”
RDMA Explained: Part 1
23 Apr 2018
RDMA networks hardware

This is the first part of a multi-part post going over RDMA, current research and RDMA’s role in the future of networking.

“Bandwidth problems can be cured with money. Latency problems are harder because speed of light is fixed—you can’t bribe God” - Anonymous

How to Write a Good Abstract
11 Apr 2018

A couple years ago I had the opportunity to attend a talk by John Wilkes. Before he began his talk on Borg, Google’s cluster scheduler, he began with an un-scheduled lecture on how to sell your research.

Diving into Deep Learning
30 Sep 2015
machine learning

Neural networks have rapidly become the de facto standard in computer vision and speech recognition. Growing interest in understanding these algorithms have motivated a boon of learning resources.

So where does someone look to obtain a basic understanding of neural networks? While the high level intuitions behind neural networks are easy to pick up, the details can be subtle and challenging to grasp. Luckily, several brilliant professors have stepped up to the challenge.