Thesis

Jenna helped validate the first mutually conjoint bilateral machine learning audiogram.

She went on to become a clinical audiologist.

Yasaman investigated the best procedure to embed informative behavioral tasks within standard Minecraft gameplay.

Scott researched artificially-induced neuronal plasticity using implantable brain-computer interfaces.

He went on to a career in imaging research and software engineering.

Jonathan researched how to generalize a Bayesian probabilistic classifier with a 4-parameter linking function and binomial likelihood.

He went on to doctoral training in computer science at UCLA.

Thomas researched the biases in functional neuronal recording for various methods depending on the topographical arrangements of various response types.

He went on to medical school at Tulane University and a career in internal medicine.

James developed the first conjoint psychometric test: the bilateral audiogram.

He went on to a career in software engineering.

Jeff characterized neural networks made from a particular neuronal cell line for use as a spinal cord injury treatment.

He went on to a career in healthcare entrepreneurship.

Katherine generalized machine learning audiometry to extended models with wider application.

She went on to a career in aviation research.

Rebecca validated the first web-based machine learning audiogram.

She went on to become a clinical audiologist.

Robert is working to implement Distributional Active LEarning for tests of cognition.

Mark is building out the behavioral task dictionary to enable behavioral quantification in interactive virtual worlds.

Dom is working to enable any behavioral task sequence within interactive virtual worlds to be informative about underlying cognitive processes.

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.

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.

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

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.

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

She went on to a career in data science.

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

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.

Brittany performed the first clinical validation of machine learning audiometry.

She went on to become an academic clinical audiologist.