Analysis and Visualization of Motor Vehicle Collision Data of New York City
The project aims at exploring the motor vehicle collision data of New York City that can give insights regarding the causes of such accidents which may lead to potential remedies for preventing road accidents. Specifically, the project targets to explore the statistical relationship of road accidents with respect to the time of accident occurrence, types of injuries of the victim, vehicle types, etc. using multiple datasets containing more than 1M rows of data which are publicly available from Open Data, City government of NYC.
Matching Patients to Clinical Trials
Clinical trials are necessary for the development of novel medical treatments. The objective of this study is to address the clinical trials matching problem: given a free-text summary of a patient's health record, locate clinical trials that are appropriate for that patient.
Estimation of Public Speaking Anxiety from Bio-Behavioral data
The goal is to better understand individuals' affective responses while performing public speaking tasks. Several deep learning models, feature selection, feature transformation algorithms have been used on the Verbio Dataset.
Bringing Machine Learning into the Classroom
The project aims at developing an interactive learning tool to help learners understand algorithms by step-by-step visualization. It has two main parts. The Sketch Viz enables users to learn sketch graphs e.g. speed graphs, curvature graphs etc. for each data point. The system's ML Algo Viz let users enter data points interactively, choose algorithms and hyperparameters, run and visualize the model's training iteratively. User study results demonstrated that users found the interface easy to use & understand, it can help them learn, they will use it in the future and recommend it to others.
