Giang H.

Master’s in Applied Mathematics (in progress) | Software Engineer | Algebraic Structures in Computation I work between software engineering and the mathematical foundations of computation. Professionally, my background spans backend engineering, data engineering, applied machine learning, and observability tooling. I’ve built and optimized API layers, data-processing logic, and data workflows; developed models for computer vision, forecasting, and NLP; implemented anomaly‑detection pipelines; and recently worked on AI‑assisted automation using RAG and agentic frameworks. These roles gave me practical intuition for how real systems compute — the constraints of performance, complexity, and structure. Academically, I’m pursuing a Master’s in Applied Mathematics. My current thesis studies non‑commutative Gröbner bases for decoding skew cyclic codes — a topic that strengthens my algebraic foundations and serves as an entry point into group theory, representation‑inspired techniques, and algebraic aspects of information theory. My broader research interest lies in algebraic and structural approaches to computation: how algebraic operations (monoids, groups, non‑commutative algebras), tensor‑style structures, and logical–algebraic frameworks inform complexity, circuit models, parallel computation, and the limits of efficient algorithms. I’m exploring graduate paths in Algebraic Methods for Computation, Theoretical Computer Science, or Algorithms, Combinatorics & Optimization (ACO), with the long‑term goal of understanding computational hardness through rigorous algebraic and structural principles. Always happy to connect with researchers or practitioners interested in algebraic viewpoints on computation, complexity, or the mathematical structure of algorithms. 🔗 More about my work: https://sites.google.com/view/coding-blog