Alejandro Escontrela
Research Intern, Frontier AI & Robotics at Amazon
Berkeley, California, United States
Summary
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Senior🎓
Top SchoolAlejandro Escontrela is a PhD student at UC Berkeley and research intern in Frontier AI & Robotics at Amazon, combining nine years of hands-on software and research experience across Google Brain, DeepMind, and industry internships. He works at the intersection of machine learning, probabilistic programming, and robotics, with a practical focus on reinforcement learning that bridges simulation and real-world control. Alejandro has contributed to influential open-source robotics tooling—improving factor-graph operations in the widely used GTSAM library—demonstrating attention to both algorithmic design and C++ performance. Backed by NSF fellowship and a Chancellor’s Fellowship, he brings aerospace engineering roots and dual bachelor’s training to bear on problems requiring rigorous systems thinking and probabilistic inference. Colleagues describe him as someone who turns theoretical ideas into production-ready algorithms that learn to solve messy, real-world tasks.
9 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD Artificial Intelligence, Doctor of Philosophy - PhD Artificial Intelligence at University of California, BerkeleyBachelor's degree Aerospace Aeronautical and Astronautical Engineering, Bachelor's degree Aerospace Aeronautical and Astronautical Engineering at Georgia Institute of TechnologyBachelor's degree Aerospace Engineering and Computer Science Double Major, Bachelor's degree Aerospace Engineering and Computer Science Double Major at University of Central Florida
German, Spanish, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (11)
unit-testing10
graph10
factors10
nonlinear-optimization10
c-language10
cprogramming-language10
linear-algebra9
robotics8
slam8
3d-mapping8
boost7
Programming languages (9)
Github contributions (5)
borglab/gtsam
Apr 2020 - Apr 2020
GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:10 commits, 1 PR, 17 comments in 3 days
Contributions summary:Alejandro primarily focused on enhancing the GTSAM library by adding and improving features related to factor graph manipulation. Their contributions involved implementing a new `addPrior` method for `NonlinearFactorGraph` and associated unit tests. Furthermore, the user refactored the code by replacing `push_back` with `emplace_shared` for improved efficiency, while also addressing pull request feedback. They also reorganized the file structure by moving `PriorFactor.h`.
smoothingsparsec-plus-plushierarchicalpattern-recognition
Waultics/coinmarketcap-history
Jul 2018 - Jun 2019
💰Obtain USD price history data for CoinMarketCap-listed cryptocurrencies.
Contributions:48 commits, 4 PRs, 35 pushes in 11 months
usdcoinbasecoingeckogdax-apicrypto
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