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A solution for parsing sentiment insights from news documents for the GSAM Team.

License: MIT License

Python 79.60% HTML 1.14% JavaScript 2.58% CSS 0.21% HTML 6.48% JavaScript 9.56% CSS 0.43%
sentiment-analysis spacy-nlp absa

aspect-based-sentiment-analysis's Introduction

Hi there 👋

  • 🏘️ London, U.K.
  • 💼 Software Engineer, Bloomberg
  • 🎓 Master of Engineering in Computing, Imperial College London
    • 🥇 1st Class Honours, Dean's List, ...
  • 🧰 Stack:
    • 😄 Python, TypeScript, JavaScript, C++
    • 🙂 Java, C
    • 🤔 Haskell, Go, Swift, Rust
  • 💡 Interests: type theory, programming language design, static analysis

📚 Publications

  1. Type-Safe Web Programming Using Routed Multiparty Session Types in TypeScript

    Master's Thesis, supervised by Prof. Nobuko Yoshida

  2. Generating Interactive WebSocket Applications in TypeScript arXiv

    PLACES 2020: Proceedings of the 12th Workshop on Programming Language Approaches to Concurrency- & Communication-cEntric Software

  3. Communication-Safe Web Programming in TypeScript with Routed Multiparty Session Types arXiv

    CC 2021: Proceedings of the 30th ACM SIGPLAN International Conference on Compiler Construction

aspect-based-sentiment-analysis's People

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