CV
Education
| Year | Degree | Institution |
|---|---|---|
| 2021 – 2025 | PhD, Medical Sciences | University of Cambridge, UK |
| 2016 – 2020 | BA, Neuroscience and Behaviour (Honours) | Vassar College, USA |
Current position
Postdoctoral Research Associate — 4D Lab, Department of Psychiatry, University of Cambridge (May 2025 – present)
Investigating how structural brain connectivity relates to adolescent mental health, genetic predisposition, cognitive abilities, and adverse experiences in over 9,000 participants from the Adolescent Brain Cognitive Development study.
Previous positions
- PhD Candidate, MRC Cognition and Brain Sciences Unit, Cambridge (October 2021 – April 2025). Supervised by Professor Duncan Astle, advised by Professor Joni Holmes.
- Venture Scientist, ConceptionX, London (March – November 2022)
- Volunteer Research Assistant, Professor John Duncan’s lab, University of Cambridge (August 2020 – August 2021). Supervised by Dr Daniel Mitchell.
- Research Assistant, Neuroscience Memory Lab, Vassar College (August 2017 – May 2020). Supervised by Professor Hadley Bergstrom.
- Research Intern, NeuroPoly Lab, École Polytechnique, Montreal (May – August 2019). Co-supervised by Professor Julien Cohen-Adad and Dr Gabriel Mangeat.
Honours & awards
- Gates Cambridge Scholarship (2021–2025) — approx. £201,500
- Katharine Jones Baker Fellowship, Vassar College (2020) — $3,000
- Departmental Honours in Neuroscience and Behavior, Vassar College (2020)
- General Honours, Vassar College (2020)
- Sigma Xi Scientific Research Honor Society (2020)
- Psi Chi International Honor Society in Psychology (2019)
- Internship Grant Fund, Vassar College (2018, 2019)
- Liberty League All-Academic Team, NCAA (2017–2019)
Technical skills
Programming — Python, R, MATLAB (see GitHub)
Software & tools — DSI Studio, FreeSurfer, QSIprep, Slurm Workload Manager, Open Science Framework
Methods — Tractography · Graph theory · Generative network modelling · UMAP · Factor analysis · Clustering · Support Vector Machines · PCA · LASSO · Generalised additive models · Linear mixed-effects models · Partial least squares regression · Dynamic time warping · Morphometric INverse Divergence (MIND)
Certifications — DeepLearning.AI / Stanford online courses in Advanced Learning Algorithms, Supervised Machine Learning: Regression and Classification, and Unsupervised Learning, Recommenders, and Reinforcement Learning.
Service
- Peer reviewer — Brain Communications, Computational Cognitive Neuroscience Conference
- Postdoc Committee Member, MRC Cognition and Brain Sciences Unit
- Invited attendee — CSaP Roundtable on Reframing Mental Health in Policy Making, Downing College, Cambridge (April 2026)
- Evidence brief contributor — APPG on Poverty and Inequality, NEET Inquiry
- Invited attendee — Diverse Trajectories to Good Developmental Outcomes Workshop, Global Scientific Conference on Human Flourishing, Cambridge (November 2022)