cv

Independent Consultant (part-time)

Paradromics Inc., Austin TX, USA

Developing and refining experiment designs for speech and language neural prosthesis and developing material to describe neural prosthesis to technical and non-technical audiences.

Postdoctoral Fellow

The University of Texas at Austin, Austin TX, USA

Using feature extraction and sustem identification techniques (linear encoding and decoding models) to investigate acoustic, phonetic, and visual processing of speech, audiovisual information, and other natural sounds in the brains of children and adults with drug resistant epilepsy using intracranial recordings.

• Speech, audiovisual processing, computational neuroscience, machine learning

Research Intern, Hearing Science and Auditory Perception

Meta Inc., Redmond WA, USA

Led the first human neuroscience electrophysiology task and system development and implemented linear classification methods and other machine learning techniques for auditory attention decoding.

• Resulted in 1 patent application

Graduate Research Assistant (PhD Student)

The University of Texas at Austin, Austin TX, USA

Executed experimental design, data collection, and analyzed brain responses of scalp EEG and intracranial electrophysiology data using statistical analysis and machine learning.

• Published 4 journal papers, 10 conference presentations, 3 research talks, and managed 6 undergraduates

Clinical Research Coordinator

University of California, San Francisco, San Francisco CA, USA

Collaborated in multiple projects concerning EEG, ECoG, and deep-brain stimulation data (in hospital settings and at patient homes), preprocessed neural data, organized large datasets, and conducted preliminary analysis on multiple projects concerning the physiology and neural networks of mesolimbic brain stucture of learning-related mechaniams in anxiety, depression, and chronic neuropathic pain.

• Resulted in 5 published journal articles

MA

The University of Texas at Austin, Austin TX, USA

Auditory and Computational Neuroscience - Dept. of Communication Sciences and Disorders

PhD

The University of Texas at Austin, Austin TX, USA

Auditory and Computational Neuroscience - Dept. of Speech, Language and Hearing Sciences

MA

University of California, Santa Barbara, Santa Barbara CA, USA

Piano Performance - Department of Music

A comparison of EEG encoding models using audiovisual stimuli and their unimodal counterparts

bioRxiv - Cold Spring Harbor Laboratory

Investigated encoding of auditory, visual, and audiovisual information using naturalistic movie trailers in scalp EEG

First-in-human prediction of chronic pain state using intracranial neural biomarkers

Nature neuroscience

Used deep-brain stimulation from chronic pain patients to decode elevated pain states from the anterior cingulate cortex and orbiofrontal cortex.

Dataset size considerations for robust acoustic and phonetic speech encoding models in EEG

Frontiers in Human Neuroscience

Assessed the amount of data needed for building encoding models using a variety of natural speech stimuli. Identifying the amount of data required for robust and generalizable results may be fruitful when time is limited for data collection, particularly when working children or clinical populations.

Decoding naturalistic affective behaviour from spectro-spatial features in multiday human iEEG

Nature Human Behaviour

Decoded positive and negative mood states from neural data linked with behavioral annotated information from patients in the EMU.

Generalizable EEG encoding models with naturalistic audiovisual stimuli

Journal of Neuroscience

Investigated speech encoding of acoustic and phonetic information using naturalistically audiovisual movie trailer stimuli in scalp EEG participants. The motivation of this study was to assess if it was possible to replace more controlled experimental paradigms such as sentence listening with more engaging and naturalistic stimuli.

Keyword-spotting and speech onset detection in EEG-based Brain Computer Interfaces

IEEE

Utilized deep learning models to design and examine the onset of phoneme and silence information in naturalistic speech sentence listening from scalp EEG data.

Musical hallucinations in chronic pain: the anterior cingulate cortex regulates internally generated percepts

Frontiers in Neurology

Case study examining musical hallucinations in the anterior cingulate cortex in two patients undergoing a clinical trial on deep-brain stimulation for chronic neuropathic pain.

Brain Stimulation Can Help Us Understand Music and Language

Frontiers for Young Minds

Paper geared towards children to explain cortical stimulation, speech, language and music. This paper is based off of Cognitive Neuropsychology paper published in 2019.

Direct cortical stimulation of inferior frontal cortex disrupts both speech and music production in highly trained musicians

Cognitive Neuropsychology

This paper examined the neural correlates of speech and music production in two epilepsy patients who underwent cortical stimulation mapping.

Decoding Natural Positive Emotional Behaviors from Human Fronto-Temporal Mesolimbic Structures

IEEE

Investigated the correlation between annotated affective behavior from patients in the EMU linked with the corresponding neural data to decode mood and provide objective measurements for future diagnosis and clinical treatments.

Generalizable EEG responses using naturalistic audiovisual stimuli

Utilized linear encoding models and statistical analysis to validate the use of naturalistic audiovisual movie clips as an experimental paradigm to model speech and multisensory information using scalp- EEG and stereo-electroencephalography (sEEG). Results published in the Journal of Neuroscience.

• Naturalistic stimuli
• EEG
• Encoding models
• audiovisual

Dataset size considerations for natural speech experiments using EEG

Used Monte-Carlo cross-validation analysis and linear encoding model to assess the amount of testing and training data needed for different types of natural speech experiments for electrophysiological recordings. Results published in Frontiers for Human Neuroscience.

• Naturalistic speech stimuli
• EEG
• linear encoding models
• Monte-Carlo cross-validation