Alun Cennyth Stokes
Finite algebraic group theory, number theory, model theory.
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About
My formal, research, and professional experiences bridge across machine learning, symbolic computing, and pure mathematics, with a focus on building tools that unite empirical data with formal reasoning systems to allow computational methods into areas of mathematics previously not possible. At the Government of Canada, I worked on applied NLP projects, while my graduate research centred on algebraic and computational number theory. More recently, my work has focused on neurosymbolic machine learning—developing systems that generate formal hypotheses or candidate theorems from fuzzy or limited data.
I've built infrastructure for symbolic regression over algebraic domains, as well as scalable training and orchestration pipelines for multi-GPU model development in computer vision. My background enables me to move between low-level performance programming and high-level mathematical abstraction, depending on what the problem demands.
Experience
Researcher; neuro-symbolic computing - Gift Horse Mouth Inspections
(2023)
Graduate Researcher - McMaster University
(2021 - 2023)
Supervisor: Dr Cameron Franc
Research Assistant - McMaster University
(2021 - 2021)
Supervisor: Dr Cameron Franc
Data Scientist (Economics) - Statistics Canada
(2020 - 2020)
Supervisor: Serge Goussev
Research Assistant - McMaster University
(2020 - 2023)
Grants from McMaster University, NSERC. Supervisors: Drs George Dragomir, Andy Nicas
Research Assistant - McMaster University
(2019 - 2020)
Supervisor: Dr Ned Nedialkov
Tutor (mathematics, computer science) - Private
(2015 - 2024)
Education
Master of Science - Computational investigations into dessins d'enfants - McMaster University (2023)
Bachelor of Integrated Science - On self-contained numbers - McMaster University (2016 - 2020)
