About Me
I am a Research Fellow in Artificial Intelligence at the University of Southampton, having recently completed my Ph.D. in emergent communication. I’m currently applying machine learning techniques to maritime engineering challenges, working with industry partners on optimizing car carrier designs through neural networks that estimate wave-induced power requirements. My doctoral research investigated how autonomous agents develop language from scratch. I focused on temporal dynamics in agent communication, designing architectures that enable temporal referencing and improve strategy development. My research examining spatio-temporal relationships in interpretable emergent communication has been published in venues such as NeurIPS and ICLR.
- Artificial Intelligence
- Computational Linguistics
- Emergent Communication
- Reinforcement Learning
- Data-Centric Engineering
PhD in Artificial Intelligence, 2020–2025
University of Southampton
BSc in Computer Science, 2016–2020
University of Liverpool
Skills
PhD in Artificial Intelligence.
All publications and side projects coded in Python.
Worked with SLURM, Linux and HPC both during PhD and at Intel.
Automation pipeline, CI/CD testing.
Most of my work is in PyTorch (Lightning ⚡️).
Homelab cluster with Nextcloud, GitLab, IoT, email and others!
Made prototype-level PCBs.
Recently experimenting with sourdough bakes (focaccia 🍞!).
Experience
- Working with industry partners on car carrier design optimization through ML.
- Implementing neural networks to estimate wave-induced power requirements.
- Building custom loss functions for maritime experimental data analysis.
- Initial models accelerate added power predictions for car carrier hulls by 100x vs semi-empirical methods.
- Expertise: AI/ML, Python, PyTorch, MLOps (MLflow), Scientific ML
- Thesis: Temporal Dynamics in Emergent Communication
- Supervised by Prof. Timothy Norman, Prof. Adam Sobey, and Prof. Federico Cerutti.
- Investigated the effect of time on communication protocols, improving agents’ strategy development, and convergence speed by up to 50%.
- Designed an architecture necessary for the emergence of temporal referencing in agent communication, enabling efficient communication.
- Developed human-interpretability measures for an emergent language containing local spatio-temporal relationships.
- Built end-to-end ML pipelines for agent training and evaluation.
- PhD defended with no corrections.
- Expertise: AI/ML, Python, PyTorch (Lightning), Ray (RLLib).
- Professional Skills: Research impact, research communication, academic collaboration.
- Managed client-facing HPC and Cloud facilities, ensuring optimal performance.
- Collaborated on pre-production hardware projects, developing technical solutions.
- Created deployment documentation and automation scripts to improve system efficiency.
- Expertise: HPC, Cloud, Bash, Linux, Server Hardware.
- Developed Bash and SQL scripts for customer data analysis using AWS services.
- Progressed from intern to part-time role across multiple projects.
- Expertise: Big Data, Amazon AWS (EC2, S3, Redshift), SQL, Bash.
