CV
PhD candidate in computational neuroscience & applied ML/AI.
Summary
PhD candidate in Computational Neuroscience at UCLA (exp. August 2026) with over 12 years of experience spanning academic research, clinical settings, and industry startups across the US, UK, and Singapore. Trained across psychology, cognitive neuroscience, artificial intelligence, and neurogenetics (UC Berkeley, UCL, NUS, UCLA), with deep expertise in multimodal neuroimaging (MRI, fMRI, DWI, EEG), ML/DL, and statistical modelling applied to brain health and psychiatric conditions. Track record of bridging rigorous science with real-world impact — from large-scale neuroimaging pipelines and clinical ML systems to agentic AI tools, startup consulting, and regulatory strategy. Equally comfortable in research, engineering, and cross-functional roles. Open to applied research, AI/ML engineering, computational psychiatry, product science, consulting, or postdoctoral positions at the intersection of AI and health.
Experience
- Led 5 independent first-authored projects applying ML and normative modelling to multimodal neuroimaging data (sMRI, fMRI, DWI) to characterise how rare genetic variants influence brain development (N > 500); first paper published in Biological Psychiatry: Global Open Science.
- Collaborated on neuroimaging research resulting in 4 co-authored publications in Molecular Psychiatry, Biological Psychiatry, and Neuropsychopharmacology.
- Built lab automation tools including a Slack-to-Notion pipeline for literature tracking; maintained lab servers and GitHub repositories.
- Supervised undergraduate researchers and contributed to teaching at UCLA's Department of Psychiatry.
- Designed EEG, HRV, and wearable-based study protocols for physiological validation and efficacy testing of neurostimulation devices.
- Synthesized scientific evidence into product strategy and investor materials; liaised with FDA consultants to develop a regulatory roadmap.
- Analysed clinical trial fMRI data (FAST-MAS, N=64) using individualized brain parcellation to identify precision biomarkers for treatment response in transdiagnostic anhedonia; published in Neuropsychopharmacology (2025).
- Bridged clinical and engineering teams — scoping medical imaging requirements, translating them into technical specifications, and communicating AI/ML concepts to non-technical stakeholders.
- Produced technical documentation and tutorials supporting client onboarding in neuroimaging and medical imaging workflows.
- Defined feature prioritization and clinical assessment design for a digital therapeutic app for early cognitive decline, deployed through hospital partners across the US.
- Synthesized Alzheimer's and BCI literature and analysed user engagement data to drive product improvements and clinical relevance.
- Analysed large-scale pediatric neuroimaging data (ABCD study, N > 10,000) using ML and statistical modelling to study associations between 24-hour movement behaviours and brain structure in children; published in Journal of Adolescent Health (2023).
- Provided quantitative MRI data analysis support to clinical researchers across multiple studies; initiated development of a U-Net segmentation pipeline for automated brain lesion detection in stroke patients.
- Developed and open-sourced a Python tool for 3D NIfTI brain image midsagittal flipping enabling lateralisation analyses — available on GitHub.
- Led a multimodal neuroimaging study (N > 100, healthy and ADHD populations) from experimental design through data collection and manuscript preparation; standardised lab preprocessing pipelines.
- Conducted clinical recruitment at the Institute of Mental Health, coordinating participant screening and MRI scanning sessions.
- Co-authored a publication on fMRI investigation of hot and cool executive functions in reward and competition; published in Sensors (2025).
- Designed and conducted an fMRI study with healthy participants to decode neural representations of self- and other-directed intentions using MVPA; published in NeuroImage (2018).
- Transcribed videos and coded behavioral responses from children and adults across age groups for a study on cognitive flexibility and causal inference; co-authored publication in PNAS (2017).
Education
Skills
Awards
NEURO2024 Travel Award for Foreign Scientists, JSBP (2024)
Graduate Dean’s Scholar Award, UCLA (2022–2024)
Top Consumer AI Product, SLINGSHOT / EnterpriseSG (2019)
Winner, Data Innovation Challenge, Rolls-Royce (2019)
Departmental Honors, Psychology — UC Berkeley (2015)
Publications
See the Publications page for the full list with DOIs.