Dr. Charalambos Theodorou

AI Researcher / Engineer | Machine Learning Expert | Entrepreneur | Investor

Pioneering advances in artificial intelligence and machine learning, from large language models and neural networks to intelligent agents that shape the future.

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Dr. Charalambos Theodorou

About Me

As a researcher and practitioner in artificial intelligence and machine learning, I focus on developing intelligent systems that push the boundaries of what's possible—from large language models to autonomous agents and deep reinforcement learning architectures.

AI Research & Development

Conducting cutting-edge research in deep learning, neural network architectures, and reinforcement learning to advance the state of artificial intelligence.

LLMs & AI Agents

Specializing in large language models and intelligent agent systems that can reason, learn, and adapt to complex real-world scenarios.

Applied Machine Learning

Translating theoretical advances into practical solutions that solve challenging problems across industries using state-of-the-art ML techniques.

Core Expertise

Python & LLM Engineering

  • Python (Expert Level - Primary Language)
  • LLM Fine-tuning & RLHF
  • Prompt Engineering & Chain-of-Thought
  • RAG (Retrieval-Augmented Generation)
  • LangChain, LlamaIndex, Hugging Face
  • GPT-4, Claude, LLaMA, Mistral

AI Agents & Autonomous Systems

  • Autonomous AI Agent Development
  • Multi-Agent Systems & Coordination
  • Agentic Workflows & Tool Use
  • Agent Evaluation & Benchmarking
  • AutoGPT, BabyAGI, CrewAI Patterns
  • Function Calling & API Integration

AI Safety & Research

  • Red-Teaming & Adversarial Testing
  • Model Alignment & Constitutional AI
  • Safety Evaluation Frameworks
  • Jailbreak Detection & Mitigation
  • AI Governance & Policy Compliance
  • Research Publication & Patent Development

ML/DL Frameworks & Infrastructure

  • PyTorch, TensorFlow, JAX
  • Transformer Architectures (BERT, GPT, T5)
  • Deep Reinforcement Learning (PPO, DQN)
  • MLOps & Model Deployment
  • AWS SageMaker, Azure ML, GCP Vertex AI
  • Docker, Kubernetes, CI/CD for ML

NLP & Generative AI

  • Natural Language Processing
  • Text Generation & Summarization
  • Sentiment Analysis & Classification
  • Named Entity Recognition (NER)
  • Semantic Search & Embeddings
  • Multimodal AI (Vision + Language)

Data Science & Engineering

  • SQL, NoSQL, Vector Databases
  • Data Pipeline Engineering (ETL/ELT)
  • Feature Engineering & Selection
  • A/B Testing & Experimentation
  • Statistical Analysis & Modeling
  • Data Visualization (Plotly, Matplotlib)

Work Experience

Lead AI Researcher / Engineer

Sept 2024 - Present

Fountech AI

  • Led cross-functional teams of 31 engineers/researchers delivering production AI systems from scratch
  • Developed LLM/Transformer solutions for generative AI, multimodal models, and agentic workflows
  • Executed red-teaming and adversarial evaluation to identify jailbreaks and policy bypasses
  • Improved model alignment via preference tuning, prompt optimization, and safety-first engineering
  • Built evaluation harnesses for safety, robustness, and quality metrics supporting release governance

Tech: Python, LLMs/Transformers, RAG, AI Safety & Alignment, Prompting

Machine Learning Engineer - CTO

Feb 2021 - 2024

Briteyellow

  • Led ML + LLM systems from prototype to production, saving $500K+ while improving outcomes
  • Built NLP/LLM solutions (LLaMA, GPT-3) with structured prompting and model optimization
  • Owned AI safety workstreams: red-teaming, policy-aligned prompting, automated evaluation
  • Deployed scalable inference pipelines on AWS & Azure, cutting deployment time 30%
  • Shipped recommender systems increasing engagement 20% and sales 25%
  • Developed novel vSLAM framework; published 4 papers and contributed to 5 patents

Tech: Python, PyTorch, TensorFlow, LLMs (LLaMA, GPT-3), AWS, Azure, Docker/Kubernetes

Machine Learning Engineer - NLP

Sept 2017 - Aug 2018

ImpacTech

  • Built end-to-end NLP pipeline for call analytics with sentiment analysis and keyword spotting
  • Deployed sentiment classification models for real-time insights across customer interactions
  • Improved model accuracy +8% through feature engineering and iterative optimization
  • Developed compliance flagging model for AI safety and policy violation detection

Tech: Python, NLP (spaCy, NLTK), scikit-learn, Speech-to-Text

Education

Doctorate (Ph.D.) in Artificial Intelligence & Machine Learning

University of Bedfordshire

Advanced research in deep learning architectures, reinforcement learning algorithms, and intelligent agent systems. Contributed novel approaches to neural network optimization and multi-agent coordination.

Master's Degree in Data Science & Machine Learning

University of Bath

Specialized in statistical learning theory, neural networks, and computational intelligence. Developed expertise in deep learning frameworks and large-scale model training.

Bachelor's Degree in Computer Science & Mathematics

University of Kingston London

Strong foundation in algorithms, data structures, mathematics, and artificial intelligence fundamentals with honors distinction.

Key Achievements

🧠

Xybern Reasoning 7B Model

Built End-to-End From Scratch

Personally designed, trained, and deployed a proprietary 7-billion parameter verified reasoning model from the ground up. Achieved 99.8% fact retrieval accuracy and <0.1% hallucination rate through custom architecture, zero-hallucination inference, and original logic reconciliation algorithms, all developed independently.

🏢

Founded Xybern

Complete Platform Built From Scratch

Founded and built Xybern as the sole technical architect, from the foundational AI model to the enterprise infrastructure. Every component including the Provenance Vault, cryptographic security layer, and reasoning engine engineered end-to-end without external codebases or pre-trained models.

🛡️

Enterprise Deployment

SOC 2 Type II Certified Platform

Architected and deployed production-ready AI systems serving regulated industries in law, finance, and compliance. Achieved SOC 2 Type II certification for a platform built entirely from first principles, delivering verifiable chains of thought and evidence-based decision-making.