David Ray
General Counsel at ROC
United States
Summary
🤩
Rockstar🎓
Top SchoolDavid Ray is a General Counsel and executive leader with 12 years of experience at the intersection of law, AI and biometric identity, currently steering ROC through NASDAQ readiness, M&A and product strategy while defining ethical AI practices that earned him the 2022 SIA Industry Advocate Award. He has a track record of driving commercial growth—building strategic partnerships that supported $200M+ annual transactions and 3x revenue expansion—while also shaping public policy and go-to-market for population-scale identity solutions. A former Big Law M&A associate and founding partner who led over $300M in transactions and investments, he combines deep corporate and regulatory fluency with hands-on technical curiosity. That technical bent shows in open-source contributions to Numenta’s HTM implementation, where he improved anomaly detection and test reliability, reflecting a rare blend of legal, strategic and machine-learning literacy. Trained at Harvard and Columbia Law, he’s equally comfortable negotiating complex deals, articulating product requirements, and debating the ethics of cognitive technologies.
12 years of coding experience
3 years of employment as a software developer
J.D., J.D. at Columbia Law SchoolA.B., Economics, A.B., Economics at Harvard University
Github Skills (9)
artificial-intelligence10
python10
numpy10
data-structure9
hierarchical-temporal-memory9
algorithm9
data-structures9
algorithms9
unit-test7
Programming languages (7)
Github contributions (5)
numenta/nupic-legacy
Sep 2014 - Jan 2016
Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex.
Role in this project:
ML Engineer
ML EngineerContributions:17 commits, 3 PRs, 1 push in 1 year 4 months
Contributions summary:David primarily contributed to the `nupic-legacy` repository by modifying and testing code related to the Hierarchical Temporal Memory (HTM) implementation. Their work involved debugging and fixing broken tests, along with the creation of new tests for methods like `sparsifyVector` within the KNNClassifier. Furthermore, the user made changes to the anomaly detection algorithm by adding checks and correcting data types. These changes demonstrate a focus on improving the accuracy and reliability of the machine-intelligence algorithms.
hierarchical-temporal-memoryneocortexartificial-intelligencemachine-intelligence
cogmission/Mosaic
Oct 2015 - Sep 2021
Contributions:2 pushes, 1 branch in 5 years 11 months
splitdrag-n-droplayoutjavafxjava
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