Stephen Becker Email & Phone Number
@colorado.edu
2 phones found area 303
LinkedIn matched
Who is Stephen Becker? Overview
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Stephen Becker is listed as Associate Professor at Applied Mathematics CU Boulder, based in Denver Metropolitan Area, United States, United States. AeroLeads shows a work email signal at colorado.edu, phone signal with area code 303, and a matched LinkedIn profile for Stephen Becker.
Stephen Becker previously worked as Assistant Professor at University Of Colorado Boulder and Goldstine fellow at IBM Research at Ibm. Stephen Becker holds Phd, Applied Math from California Institute Of Technology.
Email format at Applied Mathematics CU Boulder
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AeroLeads found 1 current-domain work email signal for Stephen Becker. Compare company email patterns before reaching out.
About Stephen Becker
I am a researcher in applied mathematics, studying convex optimization, and specifically I work on algorithms to solve large-scale sparse and low-rank inverse problems. My work has been applied to compressed sensing (we built a CMOS radio frequency receiver/ADC), image processing, and data-mining (i.e. collaborative filtering via matrix completion).From 2011--2013 I was in Paris, thanks to a 2 year fellowship from the Fondation Sciences Mathématiques de Paris. In 2013--2014, I am a Goldstine postdoctoral fellow at IBM Research in Yorktown Heights.Specialties: Convex optimization, optimization, large-scale data sets, fast algorithms
Listed skills include Algorithms, Applied Mathematics, Machine Learning, Optimization, and 21 others.
Stephen Becker's current company
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Stephen Becker work experience
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Associate Professor
Current
Assistant Professor
Assistant professor in the applied math department (amath.colorado.edu) at CU. Research and teaching responsibilities.
Postdoctoral Researcher
Optimization research on first-order methods for largescale datasets (solving previously intractable problems, or speeding up algorithms); applications to machine learning and image processing. Design of compressed sensing CMOS receiver. Research in quantum tomography reconstruction and end-member detection (e.g. non-negative matrix factorization).
Staff Scientist In Applied & Computational Mathematics
Continue development of a compressed sensing CMOS ADC.
Grad Student In Applied & Computational Math
My research is in several fields: convex optimization, compressed sensing (aka compressive sampling), and collaborative filtering. Work is both theoretical and computational.
Founding Researcher
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Stephen Becker education
Phd, Applied Math
B.A., Math, Physics
Frequently asked questions about Stephen Becker
Quick answers generated from the profile data available on this page.
What company does Stephen Becker work for?
Stephen Becker works for Applied Mathematics CU Boulder.
What is Stephen Becker's role at Applied Mathematics CU Boulder?
Stephen Becker is listed as Associate Professor at Applied Mathematics CU Boulder.
What is Stephen Becker's email address?
AeroLeads has found 1 work email signal at @colorado.edu for Stephen Becker at Applied Mathematics CU Boulder.
What is Stephen Becker's phone number?
AeroLeads has found 2 phone signal(s) with area code 303 for Stephen Becker at Applied Mathematics CU Boulder.
Where is Stephen Becker based?
Stephen Becker is based in Denver Metropolitan Area, United States, United States while working with Applied Mathematics CU Boulder.
What companies has Stephen Becker worked for?
Stephen Becker has worked for Applied Mathematics Cu Boulder, University Of Colorado Boulder, Ibm, Laboratoire Jacques-Louis Lions At Paris-6 University, and California Institute Of Technology.
How can I contact Stephen Becker?
You can use AeroLeads to view verified contact signals for Stephen Becker at Applied Mathematics CU Boulder, including work email, phone, and LinkedIn data when available.
What schools did Stephen Becker attend?
Stephen Becker holds Phd, Applied Math from California Institute Of Technology.
What skills is Stephen Becker known for?
Stephen Becker is listed with skills including Algorithms, Applied Mathematics, Machine Learning, Optimization, Latex, Convex Optimization, Scientific Computing, and Matlab.
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