Physiological Data Analysis and Credibility Assessment

The subject of assessing credibility is not new. What we are proposing in this project, on the other hand, is novel. It has been shown in various context that assessing credibility is extremely difficulty. In this project, we take a data-driven approach, relying on fundamental knowledge of neural physiology and data collected by NuraLogix, our industrial partner. The idea is simple, lying is stressful and it triggers uncontrollable neural activities that lead to subtle changes in physiological processes, which can be measured and analysed. Working with scientists at NuraLogix, we aim to address the following question: How to improve the performance of current analytic methodologies and detection methods by using newly developed techniques such as machine learning? The outcome of this project could lead to the development reliable algorithms that can be integrated into existing tools developed by NuraLogix but also new insights into this fascinating area.

Faculty Supervisor:

Huaxiong Huang;Arvind Gupta

Student:

Kian-Chuan Ong

Partner:

NuraLogix Corporation

Discipline:

Statistics / Actuarial sciences

Sector:

Professional, scientific and technical services

University:

Program: