Evan Becker
Applied Scientist at Amazon Web Services (AWS)
Los Angeles, California, United States
Summary
👤
Senior🎓
Top SchoolEvan Becker is an applied scientist and UCLA PhD candidate specializing in the training dynamics of deep generative models, with a focus on implicit bias, regularization, and high-dimensional convergence and generalization. With nine years of experience blending research and applied work, he has transitioned from undergraduate bio-systems modeling to industry roles at Amazon and AWS, where he applies theoretical insights to production-scale problems. His background in electrical engineering and prior research on automated assembly of signaling networks reflects a strong foundation in algorithm design and simulation across C++ and Python. Evan brings practical experience with statistical filtering and ODE modeling from synthetic biology projects, an unusual cross-disciplinary asset for machine learning research. A former Stamps Scholar, he combines rigorous academic training with hands-on implementation and a track record of publishing and shipping research-informed systems. Based in Los Angeles, he is driven to uncover the necessary conditions that make deep models both predictable and deployable.
9 years of coding experience
3 years of employment as a software developer
Bachelor of Science in Electrical Engineering, Electrical Engineering, Bachelor of Science in Electrical Engineering, Electrical Engineering at University of Pittsburgh Swanson School of EngineeringUniversity of California, Los Angeles
Spanish
Github Skills (10)
planning5
sensor3
motion-planning2
filtering2
computer-vision2
object-detection1
mission-control1
ras1
magellan1
decision-making1
Programming languages (2)
Github contributions (5)
evbecker/evbecker.github.io
Jul 2018 - Jan 2024
Contributions:5 pushes in 5 years 6 months
evbecker/climate-spatial-downscaling
Feb 2022 - Mar 2022
Contributions:19 commits, 11 pushes, 3 branches in 1 month
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