Profile

My fascination with systems started early with GCSE Product Design Systems, where I first explored how individual components fit together to create functional, human-centred solutions. That early exposure to design thinking and integration sparked a habit of analysing problems not just in isolation, but as part of larger, interconnected systems.

At UCL, I strengthened this foundation through Chemistry, where I was trained to analyse complex molecular systems, extract data-driven insights, and approach problems with scientific rigour. This experience refined my analytical mindset, research skills, and appreciation for the constant dialogue between theory and experiment that defines the sciences.

Now, as an MSc candidate in Robotics & AI at Queen Mary University of London, I draw on a dual specialisation in the sciences and engineering—bringing the rigour of Chemistry together with the technical depth of Robotics & AI to treat robotics as a discipline where scientific thinking meets real-world embodiment.

My work sits at the intersection of reinforcement learning, control, perception, and Sim2Real transfer. I’m especially motivated by the challenge of taking intelligence out of simulation and into embodied agents that interact with the messy, unpredictable physical world.

Goals

• Build embodied AI on UAVs, humanoids, assistive robots, and the next Baymax
• Develop RL/control pipelines in simulation (Isaac Gym, MuJoCo) and validate them on hardware
• Share progress through research‑style posts, blogs, and open‑source experiments

Research & Technical Interests

• Embodied agents and multimodal learning
• Reinforcement learning for control and locomotion
• Soft robotics for adaptive, compliant interaction
• Humanoid systems as platforms for general embodied intelligence

Current Projects

• AI Water Polo Simulation – designing a reinforcement learning environment to simulate gameplay, strategy, and decision-making in water polo
• AI Investment Analysis Tool – building a FastAPI platform that scrapes listed companies and generates AI-based insights for investment research
• AI Chatbot for My Mum – created for a university talk, this project demonstrated how conversational AI can be customized for personal use cases and accessibility
• Research blogging — documenting experiments and reflections in a format inspired by academic outputs

Foundations

Before pivoting into Robotics & AI, I studied Chemistry at UCL (BSc, 2022–2025). That training gave me:

• A strong foundation in mathematics, data analysis, and computational modelling
• Experience with scientific research methods and systematic problem‑solving
• An interdisciplinary perspective — seeing connections between molecules, machines, and models

Beyond the Lab

Outside of research, I enjoy creating content that makes science and technology more accessible. From Instagram reels to blog posts, I aim to share the reality of studying, building, and iterating through robotics projects.

I also value teamwork and leadership, including service as President of UCL Water Polo, where I learned to build communities, motivate teams, and balance ambition with collaboration.

Connect

I’m always open to conversations about robotics, AI, or interdisciplinary projects. Feel free to reach out for collaborations, discussions, or just to exchange ideas.