Past

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.

Haoxin worked in the lab during Fall 2010 as a biomedical engineering doctoral rotation student on the effect of stimulus size and receptive field size on encoding in auditory cortex neurons.

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

She went on to a career in data science.

Adhira worked in the lab during Spring 2009 as a biomedical engineering doctoral rotation student.

Elyse is working in the lab starting Spring 2022 to modernize the machine learning audiogram web site.

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

Joel worked in the lab during Summer 2010 as a biomedical engineering undergraduate working on neuronal responses to noisy vocalizations in auditory cortex.

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

Krista worked in the lab during Summer 2012 as a biomedical engineering undergraduate.

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

Sarah worked in the lab during Fall 2010 as a biomedical engineering doctoral rotation student working on infrasound detection in the auditory system.

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.

Alice worked in the lab during Spring 2013 as a computer science undergraduate.

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.

Alex worked in the lab Spring 2015 as a biomedical engineering doctoral rotation student.

Marta worked in the lab as a high school student during Summer 2010, on distributions of energy in natural dynamic sounds. She then majored in biomedical engineering at Johns Hopkins University and computational biology at University of Pittsburgh/Carnegie Mellon University.

Jesse worked in the lab during Fall 2008 as a biomedical engineering doctoral rotation student.

He went on to a career in the neurotechnology industry.

Melissa worked in the lab during Spring 2015 as a biomedical engineering undergraduate.

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

Patrick worked in the lab during Fall 2010 as a biomedical engineering doctoral rotation student on hardware designs for rewiring cortical circuits.

Brittany performed the first clinical validation of machine learning audiometry.

She went on to become an academic clinical audiologist.

Edward worked in the lab Summer 2015 as a computer science undergraduate.

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

Yunlu worked in the lab Spring 2011 as a biomedical engineering doctoral rotation student on the encoding of noisy vocalizations in auditory cortex.

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.