📄 View CV (PDF, with psychology and language models background)
📄 View CV (PDF, machine learning & AI for Physics oriented)
Open GitHub 
Open LinkedIn 
Open Google Scholar 💌 Email Me
I am an independent researcher with graduate-level training in computer science, previous experience as a Machine Learning R&D Engineer at Deepcell Inc. (a Stanford spun-out), and previous research assistant experience at Georgetown University, KAUST (King Abdullah University of Science and Technology), and the University of Nevada, Reno. I am equally open to doctoral research positions and industry roles that support research work.
My research spans two main threads. The first is computational modeling of motivation and emotion, approached through tools from machine learning and statistical modeling grounded in psychology. Within this thread, I'm interested in extending statistical models into richly individualized, profile-style characterizations. I'm also drawn to studying user behavior on games and other rich-sensor platforms. The second is PDE inverse problems and Physics-Informed Neural Networks (PINNs), including a purely theoretical project on disentangling the functional components of PINNs (with experimental validation planned).
As an independent researcher, I have:
• Written single-authored articles across these research threads.
• Had peer-reviewed papers accepted by a psychology journal and by the AI4Physics Workshop at ICML 2026 (the latter with code released on GitHub).
• A manuscript currently under major revision for resubmission to TMLR (Transactions on Machine Learning Research), alongside multiple non-refereed research notes on Zenodo.
• A poster presented at Models of Consciousness 7, Oct 2026, at Copenhagen, Denmark (poster link)
My earlier work includes a published paper on facial recognition (computer vision), as well as research on user behavior — including detecting searcher struggle from interaction signals — contributing to quantitative UX/user-behavior modeling. I am open to collaborative opportunities and academic mentorship, and actively seeking doctoral or industry research positions in Canada, Europe, England, New Zealand, Australia, the United States, and other regions.
Research interests:
• Scientific machine learning: PINNs, PDE inverse problems, and optimization landscapes
• Information Theory
• Image Processing and Visualization
• Computational Modeling of Motivation and Emotion
(My work on PDE inversion and PINNs has given me a deeper grounding in physics and mathematics than is typical for quantitatively-minded psychology researchers — though I don't claim expertise in advanced PDE analysis or theory. Separately, I also enjoy informal, exploratory discussions drawing analogies between measurement disturbance in quantum mechanics or compositional distributional grammar and models of consciousness — these are analogical discussions, not formal research.)
Software Engineering interests:
• Web Systems
• Machine Learning Systems
My full academic CV and other links are here:
📄 View CV (PDF, with psychology and language models background)
📄 View CV (PDF, machine learning & AI for Physics oriented)
Open GitHub
Open LinkedIn
Open Google Scholar
💌 Email Me
An embedded short-version resume is below: