Aria Haghighi is a seasoned engineering and AI leader with 15+ years building NLP and machine learning systems across startups and tech giants, including co-founding Prismatic and leadership roles at Facebook, Apple, Amperity, and Twitter Cortex. She combines deep research credentials—a PhD in NLP from UC Berkeley, multiple best-paper awards, and a Microsoft Research Fellowship—with hands-on product and engineering execution, from real-time relevance ranking to large-scale content understanding. As VP of Data Science at Amperity and Senior Manager at Twitter she shipped advances in entity matching, CLV modeling, and socially-aware pretraining that materially improved personalization and content integrity. A persistent open-source contributor in the Clojure ecosystem (notably improving clojupyter, clj-time, and plumatic/schema), she brings low-level engineering chops alongside strategic product vision. Based in Seattle, she now cofounds and advises startups, marrying academic rigor with pragmatic product strategy to launch and scale ML-driven products.
15 years of coding experience
9 years of employment as a software developer
PhD, Computer Science, PhD, Computer Science at University of California, Berkeley
Post-doc, Computer Science, Post-doc, Computer Science at Massachusetts Institute of Technology
El Camino Real HS
BS, Mathematics, BS, Mathematics at Stanford University
Clojure(Script) library for declarative data description and validation
Role in this project:
Back-end Developer
Contributions:66 commits, 1 comment in 5 months
Contributions summary:Aria primarily refactored and modified the Clojure(Script) library's core functionalities related to data validation and schema definitions. They updated the internal structure, renaming functions and improving the handling of sequences and records within the schema. Their contributions involved refining error handling and providing clearer validation messages. These changes appear to enhance the library's robustness and streamline its schema definition and validation capabilities.
Contributions summary:Aria primarily contributed to the core functionality of the Clojure Jupyter kernel. Their work included fixing issues with lazy sequence output and implementing tests for mime conversion. They also addressed race conditions within the core application and refactored and enhanced the display features, including adding support for HTML, LaTeX, and Markdown. The user also added a function to load Javascript to the frontend and addressed display of images.
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