PhD Student | Financial Markets & Machine Learning | Atlanta, GA
PhD Research: LLM-Based Market Microstructure Analysis
Developing novel obfuscation testing methodology to validate Large Language Model understanding of financial market constraints without temporal context.
Paper #1: "Validating Large Language Model Understanding of Market Microstructure Through Obfuscation Testing"
- 71.5% detection rate, 91.2% predictive accuracy
- Proves LLMs detect dealer hedging constraints from structure alone
- Full 2024 validation across 242 trading days
Active Project: gex-llm-patterns
- AutoGen-TradingSystem - Production-ready trading platform using Microsoft AutoGen with multi-agent orchestration
- gex-llm-patterns - PhD research on LLM pattern detection in gamma exposure analysis
- ImproveBloodPressureMeasurements ⭐ 9 - ML-based blood pressure measurement accuracy improvement
- Transcript-ClusterViz - Conversation clustering and visualization using NLP
- nverma42/Chatbot - Collaborative chatbot development project
- NLPIntro - Natural language processing exploration
- Network-Compression-Analysis - Fast Wavelet Transform compression for neural networks
- BotNet Traffic - Botnet Traffic detection
Primary: Python (99% of work)
Also Proficient: C#, C++, TypeScript, JavaScript, Java
Domains: LLMs, Algorithmic Trading, Market Microstructure, NLP, Healthcare ML, Signal Processing
- 🎓 PhD (In Progress) - Financial Markets & Machine Learning
- 🎓 M.Sc. - Computer Science
- 🎓 B.Sc. - CGDD & SWE
- ☁️ AWS Certified Practitioner
- PhD Symposium 2025: Testing LLM Structural Reasoning in Complex Systems
📝 Blog: Post Essentials 📧 GitHub: @iAmGiG
Validating AI understanding of complex systems through rigorous methodology