My friend Todd posted this on facebook:
' I get the same reaction when I use the word "orthogonal". '
16 January 2010
15 January 2010
16 November 2009
09 November 2009
persistence
Last Thursday I did an interview with some women in a qualitative research methods course. They were looking to identify things that help or hurt a woman's self-efficacy in a graduate program in engineering. We had about an hour to talk and I tried to help identify what helped me and what didn't. It's difficult to pinpoint really, and I certainly don't feel like anything that helped me was specific for helping women.
One of the interviewers asked me a very good question though. Almost an hour had passed and we had been talking about various classes, research experiences, and mentor interactions I had over the past 5 years. So then she asked, It seems you have persisted through some ups and downs. Why? What has helped you persist?
This is such a good question. Why do some of us stick around for so many years and others of us do not? First and foremost, I have had amazing support. My advisors and mentors at both schools (and all places in between) have been incredibly generous and inspirational. With full conviction and without exaggeration I can say that I would not be here without them. But that's another question-- I was asked, "Why did you stay?" not "Why didn't you leave?"
All I could say is that I love to learn. I'm doing it for me now, to learn new things every day. I just want to know. I want to see how it all works out. I remembered the times I spent banging my head against my discrete stochastic processes book or fighting (literally) through a proof with my peers until we got it right. Or way back at Rice when I worked daily with Violeta and Steve as the design and implementation of our algorithm continually informed one another. Or that moment in the first spring when I arrived at UW, when how to do the proof of the math extra credit question just popped into my head three weeks after it was due, and I spent until midnight nailing down all the details.
Now I should get back to work and see if I still persist after the next two weeks-- I'm working toward a paper deadline!
One of the interviewers asked me a very good question though. Almost an hour had passed and we had been talking about various classes, research experiences, and mentor interactions I had over the past 5 years. So then she asked, It seems you have persisted through some ups and downs. Why? What has helped you persist?
This is such a good question. Why do some of us stick around for so many years and others of us do not? First and foremost, I have had amazing support. My advisors and mentors at both schools (and all places in between) have been incredibly generous and inspirational. With full conviction and without exaggeration I can say that I would not be here without them. But that's another question-- I was asked, "Why did you stay?" not "Why didn't you leave?"
All I could say is that I love to learn. I'm doing it for me now, to learn new things every day. I just want to know. I want to see how it all works out. I remembered the times I spent banging my head against my discrete stochastic processes book or fighting (literally) through a proof with my peers until we got it right. Or way back at Rice when I worked daily with Violeta and Steve as the design and implementation of our algorithm continually informed one another. Or that moment in the first spring when I arrived at UW, when how to do the proof of the math extra credit question just popped into my head three weeks after it was due, and I spent until midnight nailing down all the details.
Now I should get back to work and see if I still persist after the next two weeks-- I'm working toward a paper deadline!
05 October 2009
Cross-Post: My experience volunteering at the Oral History archive
Over the past year I have been volunteering at the Oral History archive at the UW-Madison. I wrote a posting for their blog and it was posted today.
Women at UW in Science and Engineering: An Insider’s View of an Oral History Project
Women at UW in Science and Engineering: An Insider’s View of an Oral History Project
07 August 2009
We are all "statisticians"
This NYTimes article basically describes what I do, and what I find to be the most important area of technology today. I don't like the name "statistician" because of the very specific ideas that this conjurs up in people's minds. As the article says, the "new breed" of statisticians are actually computer scientists, engineers, and mathematicians... but "new breed" are really the operative words. That is definitely what we are.
Quoting:
"The new breed of statisticians tackle that problem. They use powerful computers and sophisticated mathematical models to hunt for meaningful patterns and insights in vast troves of data. The applications are as diverse as improving Internet search and online advertising, culling gene sequencing information for cancer research and analyzing sensor and location data to optimize the handling of food shipments.
"Even the recently ended Netflix contest, which offered $1 million to anyone who could significantly improve the company’s movie recommendation system, was a battle waged with the weapons of modern statistics.
"Though at the fore, statisticians are only a small part of an army of experts using modern statistical techniques for data analysis. Computing and numerical skills, experts say, matter far more than degrees. So the new data sleuths come from backgrounds like economics, computer science and mathematics."
Quoting:
"The new breed of statisticians tackle that problem. They use powerful computers and sophisticated mathematical models to hunt for meaningful patterns and insights in vast troves of data. The applications are as diverse as improving Internet search and online advertising, culling gene sequencing information for cancer research and analyzing sensor and location data to optimize the handling of food shipments.
"Even the recently ended Netflix contest, which offered $1 million to anyone who could significantly improve the company’s movie recommendation system, was a battle waged with the weapons of modern statistics.
"Though at the fore, statisticians are only a small part of an army of experts using modern statistical techniques for data analysis. Computing and numerical skills, experts say, matter far more than degrees. So the new data sleuths come from backgrounds like economics, computer science and mathematics."
Denial of Service
"Denial of Service." This is a term we should all become familiar with. It sounds like a pretty harmless thing, but it's the term technologists use to describe very serious attacks on internet infrastructure that have potential to seriously disrupt commerce, government, and crisis communication infrastructure.
A denial of service attack is what silenced twitter on Thursday, August 6. The attack on Estonia in April of 2007 was also a denial of service attack.
The WSJ had a good opinion piece about the state of these online attacks. Quoting: "As the attacks against Estonia show, the task cannot be delayed -- the increasing sophistication and accessibility of malware means these problems will only become worse. The future of the Web is at stake."
A denial of service attack is what silenced twitter on Thursday, August 6. The attack on Estonia in April of 2007 was also a denial of service attack.
The WSJ had a good opinion piece about the state of these online attacks. Quoting: "As the attacks against Estonia show, the task cannot be delayed -- the increasing sophistication and accessibility of malware means these problems will only become worse. The future of the Web is at stake."
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