Introduction

I'm a technically grounded, globally minded engineer and AI researcher with a passion for building systems that think, evolve, and empower. My dual citizenship (UK/US) and background in mechanical engineering offer a grounded, systems-oriented mindset, while my lifelong curiosity—nurtured and influenced by science fiction, early programming, and a childhood of quietly analyzing how my older siblings approached decisions—what worked, what didn't—and internalizing those patterns long before I understood the term 'reinforcement learning.

I view artificial intelligence as an Epochal Invention: one that's not just a technological leap, but a civilizational threshold. I've spent the past three years leading teams across startups and research efforts focused on agentic design patterns, multimodal AI, and recursive reasoning frameworks. Yet even in the most advanced projects, I never lose sight of the human element—the connections and collaborative spirit that bring meaning to the work.

I'm seeking opportunities to join forward-thinking teams tackling AI research problems with depth, creativity, and ethical intention. My approach blends technical leadership, a systems-engineering lens, and a commitment to lifelong learning, grounded in values of integrity, curiosity, and family.

Education

B.S Mechanical Engineering

North Carolina State University, Raleigh, NC

August 2018 – June 2022

Technical Skills

Git, Java, C++, Python, Deep Learning, Reinforcement training, PyTorch, fastai, TypeScript/Node.js/Express, Prisma, Docker, AWS, SOLIDWORKS, ANSYS, Onshape, Creo, Fusion 360, HyperX, HyperMesh, Inventor, AutoDesk, FEA, Amesim, and MATLAB.

Work Experience

Right Path AI

April 2023 - Present

Co-Founder, Chief Technology Officer, Co-Chairman of Board

  • Led development of Tutechy, an AI-driven education platform with multimodal tutoring features (voice, text-to-speech, camera input), curriculum integration, and three custom-built Unity games.
  • Developed recursive prompting frameworks, agentic design patterns, and AI driven code generation, execution, verification & regeneration, algorithms.
  • Utilized exceptional management, communication, documentation, coding, and research skills – demonstrated by running a team of 15+ engineers and scientists across multiple time zones.

TuTechy Technical Stack (Service-based architecture):

  • AI Service: Python/FastAPI, PostgreSQL/pgvector, multiple LLM providers (OpenAI, Anthropic, Groq, DeepSeek), async streaming, tooling for AI Agents.
  • API Layer: TypeScript/Node.js/Express, Prisma ORM
  • Frontend: Next.js 15+, Redux Toolkit, Tailwind CSS, Radix UI components
  • Infrastructure: Docker, AWS (AKS, Cognito, RDS, connection pooling, S3, ECS), third-party APIs (Deepgram, ElevenLabs, Mathpix)

Space Perspective

October 2022 – Present

Lead Pressure Control Systems (PCS) Engineer within the ECLSS Department

As the lead engineer for Space Perspective's spaceship pressure control system, I took full ownership of the PCS from inception to successful flight testing. I am responsible for the complete lifecycle of the pressure control system for a space capsule designed to reach the edge of space.

  • Designed, analyzed, prototyped, built, and tested the complete pressure control system that successfully maintained cabin pressure during flight.
  • Developed and successfully tested pressure control algorithms through self-created Amesim modeling and real flight hardware testing.
  • Created hardware integration designs in CAD (OnShape) for seamless PCS integration into the space capsule.
  • Led numerous design reviews with senior engineers, team leads, and the company's CEO.
  • Applied aerospace industry standards to perform critical flowrate and flow-coefficient calculations.
  • Collaborated across departments to define cabin-pressure requirements and ultimately delivered a system that passed all tests during edge-of-space flight.

Collier Aerospace, Raleigh NC

May 2022 – July 2022

Aerospace Structures Engineer

At Collier Aerospace, I conducted comprehensive structural trade studies that compared composite laminate with metallic structure designs for multiple aerospace contracts. My engineering work resulted in significant improvements to aerospace components.

  • Achieved a 60% weight reduction on the structural components of the payload while meeting all critical engineering criteria.
  • Ensured designs met frequency, buckling, stress, strain, and compression after impact requirements.
  • Utilized Nastran Knowledge Network to understand software solving methods in depth, then verified analysis results with detailed hand calculations for additional validation.

Independent AI Research Projects

For a (more) complete list of my projects, please visit the Projects Page.

MCTS-LLM-Swarm-Research

Developed an AI reasoning system combining Monte Carlo Tree Search with LLMs to systematically explore solution paths for complex problems. Implemented self-evaluating algorithms that balance exploration vs. exploitation of promising reasoning paths, with performance scaling with compute time.

RAG MCP tooling enabling retrieval from Fast AI for Coders With FastAI and PyTorch

Transformed fantastic resource about Machine Learning and Deep learning concepts, with demonstrable code examples into a vector DB to serve RAG enabled agent, accessible via MCP; theorizing significant gains in Agentic Code generation of ML/AI focused projects when utilizing it.

RayBans Meta Glasses Augmentation

Rebuild from scratch of (Harvard Students) Nguyen and Ardayfio's I-XRAY project: Setup TensorFlow enabled program to perform facial recognition on the livestream from RayBans Meta glasses. Ceased after facial detection proven; due to ethical dilemma with project.

Thanks for reading my resume! If you'd like to see more of my work, check out the links below.

View Software & AI Portfolio View Mechanical & Aerospace Engineering Projects View Undergraduate Experience