In this work, we explore the utility of the three main types of neural networks: feed forward, convolutional, and recurrent. While using these networks, we develop a new way to model multiagent trajectory data, explore the use of multiple activation functions for neurons at each layer of a neural network,...
A central question in neuroscience is how the brain plans movements. Here, I apply neural data analysis and machine learning methods to better understand both eye and arm movement planning, in particular focusing on naturalistic settings. First, I built encoding models to investigate the factors that led to neural activity...
Social media such as Twitter has risen as a powerful new communication medium for disseminating information on news, personal interests, experiences, and opinions. On social media, people talk about their lifestyle, health conditions and symptoms, search information on treatment options, and connect with people who have been through similar medical...
The impacts of many important technologies are limited by the availability of better-performing materials. One factor limiting the ability of engineers to develop better materials is the speed at which they can search through possible formulations and processing schemes. Recently, machine learning algorithms have emerged as a possible route to...
Pattern recognition algorithms have been proposed as a way to control powered lower limb prostheses, specifically for transitioning between the different pre-programmed locomotion modes of the prosthesis (e.g., level ground walking, stair ascent, etc.). However, these algorithms cannot track changes in the statistical characteristics of input signals, and do not...