Selected highlights

• Vesuvius Challenge 2023 Grand Prize Runner-Up ($50,000) for deep-learning ink detection that helped read ancient, unopened Herculaneum scrolls.
• Led an Allen Institute for Brain Science collaboration to open-source the largest calcium-imaging dataset of mouse primary visual cortex to date.
• Pioneered computational methods for high-density diffuse optical tomography (HD-DOT), including the first comprehensive motion-artifact analysis for the field.
• First-author research in eLife on how the brain supports speech perception in listeners with cochlear implants.
• Scientific & AI advisor to early-stage neurotech and digital-health startups, from research strategy to NIH SBIR/STTR proposals and fundraising narratives.
• Community builder and mentor, leading journal clubs and workshops and mentoring students worldwide in neuroscience, physics, and AI.

Experience

• Develop optical neuroimaging methods to study brain function in children with serious and complex conditions.
• Design novel data-acquisition and analysis pipelines to improve signal quality and clinical relevance.
• Collaborate across multidisciplinary teams to integrate optical neuroimaging into clinical studies.

• Advise early-stage digital-health and neurotechnology startups on scientific strategy, AI product development, and data-driven validation.
• Help founders turn complex research into fundable roadmaps, NIH SBIR/STTR proposals, and persuasive fundraising narratives.

• Mentor college and high-school students one-on-one in neuroscience, physics, and computer-science research, guiding several to their first publications.

• Contributed to deep-learning ink detection for Herculaneum papyri; awarded 2023 Grand Prize Runner-Up ($50k) and a 2024 Progress Prize.
• Designed experiments for model understanding and error analysis, and refined patch-sampling and aggregation strategies.

• Led a project with the Allen Institute to release the largest mouse V1 calcium-imaging dataset to date.
• Built a Python toolbox for statistical analysis of neural responses; characterized spatial and motion selectivity with ML.

• Developed data-processing tools and machine-learning pipelines for HD-DOT clinical and cognitive neuroimaging.
• Led teams handling HD-DOT/fMRI data and mentored a postdoc, three graduate students, and several research assistants.

• Conducted doctoral research in the Culver Lab, advised by Prof. Joseph Culver.
• Published the first comprehensive motion-artifact analysis for HD-DOT and developed a novel motion-detection metric.
• Led clinical protocol development for cochlear-implant and deep-brain-stimulation patients; contributed to NIH R01 grants and projects funded by the Gates Foundation and Meta.

Full work history, including teaching and earlier research roles, is available in the downloadable PDF.

Selected publications

• Dorsolateral prefrontal cortex supports speech perception in listeners with cochlear implants. eLife. Read
• fNIRS reproducibility varies with data quality, analysis pipelines, and researcher experience. Communications Biology. Read
• Global motion detection and censoring in high-density diffuse optical tomography. Human Brain Mapping. Read
• Mapping cortical activations underlying covert and overt language production. NeuroImage. Read
• Mapping brain function in adults and young children during naturalistic viewing. Human Brain Mapping. Read
• Mapping neural correlates of biological motion perception in autistic children. Molecular Autism. Read
• A high-density diffuse optical tomography dataset of naturalistic viewing. Scientific Data. Read
• Decoding visual information from high-density diffuse optical tomography. NeuroImage. Read
• Portable, field-based neuroimaging. NeuroImage. Read

Full publication list, including all co-authored work, is available in the PDF and on Google Scholar.

Education

Thesis: Separating Signal from Noise in High-Density Diffuse Optical Tomography · Advisor: Prof. Joseph Culver

Thesis: Cosmological Tests in Non-Linear Massive Gravity

Awards & honors

• Vesuvius Challenge 2023 Grand Prize Runner-Up ($50,000) and 2024 Progress Prize
• 1st Place, SPIE Optics Outreach Games, Optics + Photonics 2016
• 1st Place, Annual Graduate Research Symposium in Sciences, 2016
• SPIE Travel Grant for Leadership Workshop
• Hughes Summer Fellowship; Graduate Teaching Fellowship; University Fellow, WashU Physics

Leadership, teaching & service

• Peer reviewer for NeuroImage, Nature Scientific Reports, Neurophotonics, Psychophysiology, and OpenReview.
• Founded and led a weekly HD-DOT data-quality workshop and an ML-in-brain-signal-processing journal club (30+ members).
• Contributed to the Deep Learning course (CIS-522) at the University of Pennsylvania.
• Vice President, SPECTRA (OSA/SPIE student chapter); taught undergraduate physics, quantum mechanics, and astrophysics.
• Active in Women in Physics and graduate peer mentoring.

Selected invited talks

• Separating signal from noise in high-density diffuse optical tomography. Computational Imaging Group, WashU, 2022.
• Mapping the impact of deep brain stimulation on brain function in Parkinson disease. Psychiatry Grand Rounds, WashU School of Medicine, 2020.
• Developing diffuse optical tomography for patients with implants. fNIRS Seminar Series, Ohio State University, 2019.

A full list of invited talks and 50+ conference presentations is available in the PDF.