CV

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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)