Persistant

Nikki worked in the lab Summer 2016 through Summer 2017 as a biomedical engineering undergraduate on validating machine learning audiometry against standard psychometric curve estimation.

Danish explored automated methods of hearing assessments.

He went on to become a healthcare entrepreneur.

Ruiye investigated the encoding of vocalizations in the auditory system.

She went on to a career in data science.

Nikki investigated the effects of dialysis on hearing thresholds in patients with kidney failure.

Randolph worked in the lab from Fall 2014 through Spring 2015 as a biomedical engineering undergraduate.

Kristy worked in the lab from Summer 2009 through Summer 2010 as a lab technician on establishing stable neurotrophin concentrations in vitro and decoding human electrocorticography signals.

She went on to a career in medicine.

Lyla explored how to ensure the machine learning tools the lab is developing are deployed equitably.

Mariluz is working on discerning trends in population executive function tests to construct prior beliefs for Bayesian active learning tests of cognition.

As of Fall, 2023 Mariluz is a doctoral candidate in biomedical engineering at the University of California, San Diego.

Brittany worked in the lab Fall 2012 through Spring 2014 as a biomedical engineering undergraduate on auditory perceptual training.

She went on to pursue a doctorate in biomedical engineering at the University of Pennsylvania.

Shohaib worked to bring Bayesian active learning to visual contrast sensitivity functions.

Drew researched the implications of artificial correlations in non-random neural networks.

He went on to pursue an MD/PhD at Washington University.

Braham deployed our modern cloud-based machine learning audiogram an implemented multiplexed psychometric testing.

He went on to pursue a PhD in computer science at The University of Texas at Austin.

Metasebya worked in the lab from Summer 2007 through Summer 2008 as a biomedical engineering doctoral student.

She went on to complete her doctoral degree and become a biomedical scientist in industry.

David studied how to optimize the diagnosis and treatment of auditory processing disorders using distributed computing.

He went on to a career in serious game design, medical informatics and data analytics.

Julia investigated audiovisual integration useful for improving recognition of speech in noise.

She went on to become a professor in Psychology at Carleton College.

Kiron was instrumental in the application of simulations to confirm the properties of machine learning audiometric tests.

He went on to a career in machine learning software development.

Dan analyzed data from pediatric brain tumor patients to construct better predictors of clinical outcomes.

She went on to a career of machine learning software development.

Wensheng characterized the population encoding of sound in auditory cortex using machine learning analytic methods.

She went on to a career in data science.

Chris investigated how best to extract behavioral data from Minecraft gameplay logs in order to design richer cognitive tests.

John worked in the lab as a Medical/Masters student from Summer 2008 through Fall 2008.

Trisha worked in the lab during Fall 2005 as a biomedical engineering undergraduate.

Alex helped clinically validate the first dynamically masked machine learning audiogram.

Edgar developed the math behind discrete controlled release, which induces structured neurite outgrowth to interface with a therapeutic brain computer interface.

He went on to pursue an MD/PhD in computational neuroscience in Baylor and establish a research career in computational neuroscience.

Huihao worked on visualization of complex latent variable models.

Will helped configure a cloud-based machine learning server to build cognitive models from behavioral data.

Paul worked on understanding the nature of dynamic range encoding of auditory cortex neurons.

He went on to a career in academic neuroscience research and software design.

Ken worked to evaluate and extend the capabilities of machine learning contrast sensitivity function estimators.

Chris is the mastermind behind many Minecraft gameplay elements that have been developed for human behavioral testing.

Quinn Wai worked to evaluate the lab's machine learning contrast sensitivity function estimator.

Brittany performed the first clinical validation of machine learning audiometry.

She went on to become an academic clinical audiologist.

Kevin worked in the lab from Summer 2018 to Spring 2020 as a biomedical engineering undergraduate and computer science master's student to implement semantic auditory search apps and analyze the resulting data.

He went on to pursue a PhD in Bioengineering at University of Pennsylvania

Zeyang worked in the lab from Spring 2012 to Spring 2013 as a biomedical engineering undergraduate.

Eric worked on characterizing the network behavior of cultured neurons.

He went on to pursue a PhD in biomedical engineering at University of Washington.

Xiaochen worked on developing Python-based active learning code for cognitive testing.

He went on to pursue a PhD in computer science at Purdue University.

Zhiting worked to extend the machine learning contrast sensitivity estimator to include other related data streams.