Founder & CEO Profile in Washingtonian

Meghan Gaffney Buck, VEDA's Founder & CEO, shares her experience as a women in tech.  Her advice for other women starting their own companies:

"Look for people who will give you honest, brutal advice. I’ve been lucky to have those mentors, both male and female, who know what they’re doing, who’ve done this before, and who are willing to tell me when I’m wrong. Also, it’s important to figure out how to own your story and your successes because the fact of the matter is, less than 5 percent of venture capital money goes to women-run companies. So we don’t have to be good, we have to be perfect. But that doesn’t mean you can’t be part of the 5 percent, and it doesn’t mean that number can’t change. So instead of being discouraged by it, it’s important to own your victories along the way: your first contract, your first revenue, your first hire. It’s good to be able to say, “Great, we broke that barrier—now on to the next thing.”

 

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Meghan Buck
VEDA Wins the Medstar #Patient2Consumer Challenge!

VEDA Founder & CEO pitched at the 1776 Medstar Patient2Consumer Challenge and won a coveted opportunity to partner with one of the nation's leading health systems to prove VEDA's ability to make healthcare smarter.  More updates to come as the cohort begins in October 2017!

Learn More Here

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Winners!

Meghan Buck
VEDA Co-Founder Releases Gausspy Code Base

In order to understand where we came from, scientists start by exploring why galaxies are born, how they grow up, and why they die.

We live in a galaxy, and the life cycle of every galaxy is quite a story, always with these three phases. It is easy to *see* galaxies in each phase, but without better understanding of star formation and how gas is turned into stars, we will never know WHY they age, and why they die.

For over 50 years, astronomers have been manually measuring and modeling star formation, but future understanding depends on analyzing more data from larger net generation telescopes. In the absence of the ability to utilize the amount of data necessary to measure star formation, theorists have relied instead on models that are often compelling, but unconfirmed.

All of that is about to change.

READ MORE AT MEDIUM: https://medium.com/@RobertRLindner_54129/can-machine-learning-answer-the-question-where-did-we-come-from-223894bfeea6#.41lotlbno

Meghan Buck