Computing

Gordon worked on updating and evaluating Distributional Active LEarning estimators for cognitive functions.

Steven deployed the final cloud-based machine learning audiogram.

He went on to a career in software development.

Jake worked on updating and evaluating machine learning contrast sensitivity function estimators.

David worked in the lab from Spring 2008 through Spring 2009 as a biomedical engineering undergraduate student.

Bryan worked on commercializing early speech perception brain training games.

He went on to pursue an MBA at the Wharton School.

Carrie worked to acquire behavioral data in children engaged in Minecraft cognitive games.

Hanqi worked to support and extend the ability to acquire real-time cognitive data with active machine learning.

Jeff created simulations that helped confirm the properties of machine learning audiogram estimators.

He then established a career as a management consultant.

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.

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

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

He went on to a career in software engineering.

Álvaro created and maintained the back-end machine learning server to support real-time cognitive modeling from tablet data.

Álvaro went on to pursue a doctoral candidate in Computer Science at the College of William & Mary.

Michael worked to add Bayesian active learning to our newest cognitive tests.

Bradley worked on modernizing the machine learning audiogram web site form and function.

Jeff worked in the lab Summer 2013 as a computer science undergraduate.

Cate worked on identifying predictors of outcomes in pediatric brain tumor patients.

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

Trevor evaluated the efficiency of Bayesian active model selection for audiometric diagnoses.

He went on to a career in healthcare data science.

Xiaoteng (Adam) worked in the lab during Summer 2010 as a neuroscience / computer science undergraduate on the role of neuronal correlation in intensity coding in auditory cortex.

Qihan coded for our brain training video games.

He went on to a career as a software developer.

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

Rogan worked in the lab during Summer 2012 as a C-SURE student.

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

Danny worked in the lab Spring 2014 as a computer science undergraduate.

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

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

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.

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.

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.

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

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

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

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

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

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.