Faculty Advisor: Adjunct Associate Professor of Computer Science, UCLA

Anticipated Start Time: TBD (meetings will take place for around one hour per week)

Research Practicum Introduction

The advent of smart infrastructures, wearable devices, and Internet of Things (IoT) has enabled platforms through which large volumes of data can be easily captured and transferred over networks with no or minimum interaction from humans. Every individual nowadays can produce data in ways that were hard to imagine only a decade ago. Harnessing this data can help scientists and engineers achieve astonishing breakthroughs—from building autonomous cars to developing personalized healthcare. 

However, capturing and collating data by itself cannot be useful unless we learn how to understand them, interpret them and how to extract patterns, often implicit, from them. As data scientists and engineers, we need to tweak data to be amenable to various techniques and sciences such as Artificial Intelligence, Machine Learning, etc. In this program, we will learn important ideas behind data science,  machine learning, and statistics. We will work on a few methods and techniques that are essential in most data driven projects. 

Students will also learn general and subject-specific research and academic writing methods used in universities and scholarly publications and generate their own work products upon completion of the program.

Project Topics

• Analyzing healthcare data 

• Predicting medical conditions based on patients electronic health records

• Activity tracking using wearable devices such as smartwatches or smartphones 

• How to use activity tracking to detect frailty 

• Machine Learning Techniques

• Prediction, classification, supervised, and unsupervised learning

Program Detail

• Cohort Size: 3-5 students

• Duration: 12 weeks

• Workload: Around 4 hours per week (including class time and homework time)

• Target Students: 9-12th grade students interested in Data Science, Internet of Things (IoT), Machine Learning, Artificial Intelligence, Statistics, or Health Care topics.