Dear faculty members and fellow students,

You are cordially invited to my thesis defense on April 14th.

Title: Multi-resolution Analysis of High-dimensional Streaming Data for Anomaly Detection with Applications in Green Energy and Additive Manufacturing

Date: April 14th 2023

Time: 9am-11am EDT

Location: Remote, meeting link:  https://gatech.zoom.us/j/91846940343?pwd=YmFLSWRrUzdtZkpyZnlzZENrWGloQT09

Wei Yang

Machine Learning PhD Candidate

School of Industrial and Systems Engineering (ISyE)
Georgia Institute of Technology

Committee

1 Dr. Kamran Paynabar (Advisor, ISyE)

2 Dr. Jianjun Shi (ISyE)

3 Dr. Jing Li (ISyE)

4 Dr. Chuck Zhang (ISyE)

5 Dr. Bianca M. Colosimo (Department of Mechanical Engineering, Politecnico di Milano)

Abstract

Anomaly detection is critical in many fields, such as manufacturing and electrical power systems, to improve manufacturing or system productivity. In the era of industrial 4.0, there is a digital and twin transition of advanced manufacturing thanks to the availability of varieties of sensors measuring different physical quantities or parameters of machines and equipment. Analyzing high-dimensional data from sensor measurements makes it possible to detect examples or patterns that stand out from the norm through statistical and machine learning means. My thesis focuses on the multi-resolution analysis of high-dimensional streaming data for anomaly detection with applications in green energy and additive manufacturing.