# ┌──────────────────────────────────────────────────────────────┐
# │           ahmed@research ~ $ python profile.py               │
# └──────────────────────────────────────────────────────────────┘

class AIQuantResearcher:
    def __init__(self):
        self.name     = "Ahmed"
        self.role     = "AI & Quantitative Researcher"
        self.location = "Egypt 🇪🇬"

    @property
    def research_stack(self) -> dict:
        return {
            "deep_rl"          : ["Policy Gradient Methods", "Actor-Critic Architectures",
                                  "Continuous Action Spaces", "e.g. DDPG, TD3, SAC"],
            "finance"          : ["Algorithmic Trading", "Market Microstructure",
                                  "LOB Dynamics", "Quantitative Strategy Design"],
            "probabilistic_ml" : ["Conformal Prediction", "Uncertainty Quantification",
                                  "Distribution-Free Inference"],
            "islamic_finance"   : ["Shariah-Compliant AI Strategies",
                                  "Riba-Free Portfolio Construction",
                                  "ML-Driven Equity Screening"],
            "llm_agentic"      : ["LangGraph", "LangChain", "PageIndex",
                                  "Agentic Pipelines", "RAG Systems"],
            "cloud_mlops"      : ["Google Cloud Platform (GCP)", "Cloud-native ML Workflows"],
            "competition"      : ["IMC Prosperity 4 — Active"],
            "game_theory"      : ["Ordinal Games", "Strategic Equilibria"],
        }

    def current_focus(self) -> str:
        return (
            "Quantification of Continuous Action Uncertainty in Reinforcement Learning "
            "and its Application to Islamic Finance Equity"
        )

ahmed = AIQuantResearcher()
print(f"👋 Welcome to {ahmed.name}'s profile")
print(f"🔬 Current Focus: {ahmed.current_focus()}")