June Grad Student Highlight | Tommy Ciardi

June 9, 2022 | By Ylan Phan and Jenna Ross

Tommy Ciardi completed his undergraduate degree with majors in Computer Science and Cognitive Science and minors in Philosophy and Artificial Intelligence at Case Western University. Tommy finds that doing things like visiting friends who studied abroad, working as a tour guide at the art museum, and being a counselor for Camp Kesem are rewarding highlights of his time at Case Western University. He feels that Case Western has a student body that is large enough to be able to always meet new people, but small enough to not feel drowned out. He had a really positive experience visiting the school and loved the niche parts of it from the ThinkBox (a public creation space with all the machinery/tools one could ever need) to the Cleveland Museum of Art being next door. Tommy also admits that there were bound to be some lowlights while being at Case Western, such as the COVID-19 pandemic taking a toll on his college endeavors, or simply not doing good on his first calculus exam.

“Case, for me, sat at the perfect intersection of what I sought in a college. Strong academics with a collaborative, supportive environment.”
– Tommy Ciardi

Tommy is currently pursuing a Master’s degree in Computer Science with a focus in Artificial Intelligence/Machine Learning. Tommy believed that the combination of Computer Science and Cognitive Science satisfied both his interest in technology/mathematical thinking and his interest in understanding how humans and social structures function. He is fascinated by how things work and by how these various sides shape society today.

Tommy enjoys hiking, the outdoors, and travel in his spare time. So far this year, he has visited Rocky Mountain National Park, Peru, and Iceland. He also enjoys running, having recently completed the Grayson Highlands Trail Half Marathon, and has recently begun rock climbing. Cooking was his quarantine hobby, and he enjoys attempting recipes from various cuisines. His other interests include reading, videography, and tennis.

Research Overview

Tommy’s MS thesis is a project in collaboration with Dr. John Lewandowski and Dr. Roger French. The title is, “Spatiotemporal Feature Extraction and Full-Scale Analysis of Material Degradation in X-Ray Computed Tomography Scans using Computer Vision and Graph-based Machine Learning”.

Al-Mg alloy is a popular material used in the construction of various domains, such as naval ships. Like any material in variable, extreme environmental conditions, however, it degrades over time. Tommy, along with his team, are working to observe how these materials degrade at a microstructural level over time and why they degrade in the patterns they do.

Al-Mg alloy plates from a decommissioned Navy destroyer

Using Al-Mg samples from a retired Navy destroyer, the team collaborated with Diamond Light Source to collect a series of 3D X-Ray Computed Tomography (XCT) scans to observe stress corrosion cracking (SCC). 3D volumetric XCT images were taken throughout the experiment to capture extreme high quality images of the microstructures.

Images taken using X-ray Computed Tomography (XCT)

The mass quantity of image information obtained during these experiments (over 250,000) made it impossible to process the information without the help of machine learning. The goal was to develop a fully scalable, automated pipeline to produce spatiotemporal scene graphs that explain how the degradation is occurring:

Pre-process images and metadata
Identify and label unique features within the images such as cracks, inclusions, and other defects
Features are translated into summary graphs
Multiple summary graphs can be stacked to represent the material over time. Graph-based machine learning can then be applied to provide spatiotemporal scene graphs which are effectively summaries of what is occurring, what factors influence others, etc.

The steps above detail an analysis pipeline that will be used to analyze the experiment and as well as be generalized into a package for other scientists to use to analyze XCT scans of their own data and materials.

Career Goals

Tommy had originally planned to work in technology consulting, but his perspective has shifted since deciding to enter his graduate program rather than accept a job offer. He does not yet have a job title, but after graduation, he would like to work at the intersection of data science/machine learning and social systems. This could be a job such as a data scientist/ML engineer in industry or further his education in a PhD program.