Suriya Narayanan Rajavel

About Suriya Narayanan Rajavel

My Journey: I build high-performance systems at the intersection of intelligence and physics. My path started with a fundamental question: how can we leverage modern computing—from GPUs to Quantum Processors—to solve the world’s most complex optimization problems?Technical Engineering At Span Technology, I built production-grade LLM systems, designing RAG architectures on AWS that reduced costs by 20% and improved accuracy by 25%. This taught me that the real challenge isn\'t just the model; it\'s the system architecture and the deterministic latency required for real-world impact.Quantum & Systematic Research I apply this engineering rigor to Quantum Information Science and Quantitative Finance. My recent work includes:Quantum Optimization: Designing 11-qubit QAOA circuits in Qiskit for molecular docking, formulating complex problems as QUBO/Ising Hamiltonians.Systematic Research: Developing Markov regime-switching models and pairs-trading strategies with a 1.3 Sharpe ratio, focusing on the feedback loop of hypothesis, backtest, and iteration.High-Performance Computing: Building C++/CUDA inference engines with <10ms p99 latency to bridge the gap between software and hardware.What Drives Me I believe the future of discovery lies in Agentic AI and Quantum-Classical integration. Whether I\'m building AI-enabled learning systems for quantum labs or deploying real-time prediction pipelines, I thrive where engineering discipline meets mathematical intuition.Enablement I’ve trained 50+ students in ML fundamentals and am passionate about technical enablement—translating cutting-edge R&D into structured, teachable frameworks. Always happy to connect with others working in Quantum, AI, or Markets.

Experience

1. Lead Systems Contributor(Open Source)

   Light Water

   Mar 2026 — Present

   Built an autonomous strategy optimization system using Karpathy\'s autoresearch framework and Claude Code — 30 iterations in 20 minutes, zero human intervention, improving a baseline SMA crossover from 133.8% to 290.6% total return (+156.7%)Developed the full autoresearch pipeline: strategy plugin, scoring engine, iteration logging (TSV), automated git commit/revert workflow, and Plotly chart generator with smart scaling modesImplemented 3 technical indicator strategies (Bollinger Bands, Williams %R, VWRSI) as backtester plugins using the @register_strategy decorator architectureBuilt a Norgate-to-Parquet data export script for data provider migrationWrote comprehensive unit tests with pytest across 12 completed tasks, all submitted via standardized PR workflowPublished a technical article on Light Water\'s official blog documenting the autoresearch methodology, AI-discovered insights, and 5 data visualizations — lightwaterdispatch.com/dispatch/autoresearch.htmlCollaborated asynchronously with the founder via Slack and GitHub PRs, following production code review standards

Education

• Bannari Amman Institute of Technology

  Bachelor of Technology - BTech, Artificial Intelligence and Data Science

  2020 — 2024

• University of Florida

  Master's degree, Applied Data Science