I'm an interdisciplinary researcher exploring how intelligent systems reason — from the symbolic structures of compilers to the emergent cognition of LLMs. My work seeks convergence between Neurosymbolic AI, Programming Language Theory, and Binary Analysis, drawing from mathematics, cognitive science, and social theory.

class Samuele95:
    def __init__(self):
        self.role = "Interdisciplinary AI Researcher"
        self.education = "MSc AI & Robotics @ UniCam"
        self.core_question = "How do intelligent systems reason?"

        self.research = {
            "neurosymbolic_ai": ["Reasoning Systems", "Context Engineering",
                                 "LLM Cognition", "Symbolic-Neural Integration"],
            "languages": ["Compilers", "Type Theory", "VMs", "Formal Semantics"],
            "binary": ["Malware Analysis", "Reverse Engineering", "Binary Understanding"]
        }

        self.foundations = ["Mathematics", "Cognitive Science", "Neuroscience",
                           "Psychology", "Sociology", "Critical Theory"]

    def philosophy(self):
        return "The deepest insights emerge at disciplinary boundaries"

Neurosymbolic AI	Languages & Compilers	Malware & Binary Analysis
Investigating reasoning mechanisms in LLMs through context engineering. Exploring symbolic-neural integration.	Formal language theory, type systems, VMs, and the mathematical foundations of computation.	Static/dynamic analysis, reverse engineering, program behavior at the lowest level.
How do machines think?	How do we translate intent into execution?	Where intent meets implementation.

I believe the most profound insights emerge at the boundaries between disciplines. My research integrates:

📚 Sociology & Critical Theory — Criminal sociology and social theory through:

• Foucault — Power structures & knowledge systems
• Bentham & the Panopticon — Surveillance & control
• Weber — Rationalization & bureaucratic reasoning
• Le Bon — Crowd psychology & collective behavior
• Malatesta — Anarchist theory & decentralized organization

                    NEUROSYMBOLIC AI
                   Reasoning Systems
                  Context Engineering
                          |
         +----------------+----------------+
         |                |                |
         v                v                v
    MATHEMATICS      COGNITIVE         SOCIAL
    Type Theory       SCIENCE          THEORY
   Formal Systems   Neuroscience      Psychology
         |                |                |
         +----------------+----------------+
                          |
         +----------------+----------------+
         |                |                |
         v                v                v
     COMPILERS       BINARY           AI COGNITION
    & LANGUAGES     ANALYSIS         LLM Reasoning
   Formal Semantics  Reverse Eng.   Context Windows

• Neurosymbolic AI bridges formal symbolic systems with neural learning
• Context Engineering mirrors how humans construct meaning through contextual frames
• Binary Analysis requires understanding both formal semantics and adversarial psychology
• Compiler Design embodies the transformation of human cognitive structures into machine execution

Compilation Pipeline:

• Lexical Analysis — Tokenization, finite automata (Flex)
• Parsing — LL/LR parsers, AST construction (Bison, ANTLR)
• Semantic Analysis — Type checking, symbol tables
• Code Generation — IR design, optimization passes
• Runtime Systems — Memory management, GC, JIT

Virtual Machine Architecture:

• Stack-based and register-based VM design
• Bytecode instruction sets and encoding
• Built LC3VM — Complete LC3 virtual machine

Language Design:

• Formal grammar specification (BNF/EBNF)
• Type system design and implementation
• Built Logo4J — Logo language interpreter

💬 Let's Connect

Interested in neurosymbolic AI, reasoning systems, compiler theory, or the intersection of computation and cognition?