Brandon Liu
JD Student, Furman Academic Scholar at New York University School of Law
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolBrandon Liu is a multidisciplinary technologist and lawyer-in-training with 15 years of experience building production-grade systems, leading engineering teams, and shaping AI policy. He pairs deep hands-on backend expertise—demonstrated by contributions to networkx (improving PageRank robustness) and retry semantics in Resque—with public-sector work on algorithmic accountability at the FTC and CFPB. Currently a JD student and Furman Academic Scholar after doctoral study at Cornell Tech, he blends rigorous technical research in information science with regulatory and sociopolitical perspectives from LSE and SOAS. His career moves fluidly between startups, global health research, and government fellowships, showing an unusual combination of product delivery, academic publishing, and policy impact. Known for shipping pragmatic fixes that improve algorithmic robustness, he brings both code-level rigor and a strategic view of how law can govern emerging AI risks. Based in New York, he focuses on making complex socio-technical systems auditable, equitable, and resilient.
15 years of coding experience
9 years of employment as a software developer
Doctor of Law - JD, Doctor of Law - JD at New York University School of LawMaster of Science (M.Sc.) Development Studies, Master of Science (M.Sc.) Development Studies at SOAS University of LondonB.A. Computer Science, B.A. Computer Science at Harvard UniversityDoctor of Philosophy - PhD Information Science, Doctor of Philosophy - PhD Information Science at Cornell UniversityLondon School of Economics and Political Science
Github Skills (19)
graph-algorithms10
resque10
python10
retrying10
plugin10
ruby10
callback10
retry-policy10
exception-handling10
retry-logic10
minitest10
mechanism10
retry-pattern10
scipy9
graph-analysis9
Programming languages (8)
Github contributions (5)
lantins/resque-retry
Aug 2015 - Nov 2015
A resque plugin; provides retry, delay and exponential backoff support for resque jobs.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:18 commits, 3 PRs, 33 comments in 2 months
Contributions summary:Brandon primarily contributed to enhancing the retry mechanism within the Resque plugin. Their work included adding hooks to trigger actions before and after retries, allowing for custom logic integration. Significant changes involved implementing callbacks and exception handling strategies to handle retries and failures gracefully. These changes involved modifications to core plugin files and related testing, solidifying the retry capabilities.
exponential-backoffresqueresque-jobsexponentialresque-plugin
networkx/networkx
Oct 2013 - Nov 2013
Network Analysis in Python
Role in this project:Back-end Developer
Back-end DeveloperContributions:28 commits in 10 days
Contributions summary:Brandon primarily contributed to the `networkx/networkx` repository by modifying and improving the PageRank algorithm implementation. Their work included fixing docstrings, adhering to PEP8 style guidelines using autopep8, and adding a new parameter, `dangling_edges`, to the `google_matrix` function. Furthermore, the user implemented and tested changes related to handling dangling nodes within the PageRank calculations and updated tests accordingly. These changes enhance the functionality, readability, and robustness of the graph analysis algorithms.
graph-analysispythoncomplex-networksgraph-theorygraph-visualization
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