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Building Intelligent Systems That Learn, Reason and Evolve

Systems Thinker  |  Applied AI Engineering  |  Computational Finance  |  Algorithmic Trading

Welcome to my AI Notes.

I'm Shyaam Prasadh, an AI researcher and engineering leader working at the intersection of artificial intelligence, reinforcement learning, agentic systems, statistical modelling, computational finance, and decision intelligence.

Over the past decade, I've worked across quantitative finance, enterprise AI, machine learning research, and large-scale decision systems. My work spans building autonomous AI agents, developing statistical models for financial markets, algorithmic trading, and sports betting, designing enterprise AI platforms, and applying machine learning to complex real-world decision problems.

Today, I lead Enterprise AI Engineering at Entain, where I build large-scale AI systems, LLM-powered products, and intelligent agent architectures deployed across multiple business domains.

This website serves as my personal research notebook, documenting ideas, experiments, papers, and engineering lessons from building intelligent systems that continuously improve over time.

"How do we build intelligent systems that continuously learn, reason, adapt, and evolve?"
Shyaam Prasadh
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AI Research & Engineering

Shyaam Prasadh, Ph.D.  |  GitHub  |  sprasadhpy.github.io

Building intelligent systems that learn, reason, and evolve.

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