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Doug S

- Research Program Mentor

PhD at University of Texas Austin (UT Austin)


Mechanical Engineering, Statics, Dynamics, 3D Printing, Materials Science


I grew up in Pennsylvania in the US, and spent most of my youth riding bicycles, motorcycles, and generally just spending time outside. I did my undergraduate degree at Alfred University in central New York, and obtained a BS in mechanical engineering and a minor in business administration. After undergrad., I worked for 2 years at Bartell Machinery designing large industrial equipment for the tire industry. I started graduate school at the University of Texas at Austin in the Fall of 2016, and obtained on a PhD in mechanical engineering in 2021. I'm currently a postdoctoral fellow with The University of Texas and a company called re:3D. We're working on a 3D printer that prints from recycled water bottles.

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

Predicting structure from chaos in additive manufacturing

There is great interest in increasing the number of materials which can be used for additive manufacturing (AM). Unfortunately, it is difficult and expensive to develop and test new materials, especially without the proper equipment. This project aims to develop a simple approach to predict if a material will or will not work for AM. In this project, you will use simple machine learning algorithms to predict if a certain material will work in AM. The algorithms will be tested experimentally by the project mentor. This project will also introduce students to concepts of scale-invariance and fractal surfaces.

Design for additive manufacturing

In this project, you will design a part in CAD in a traditional sense (i.e. the part could be manufactured by traditional methods, like machining). Then, you will create design constraints (e.g. the part needs to hold a certain amount of weight), and use a generative design tool like Autodesk Fusion 360 to optimize the part. The intent of this project is to hint at the future of engineering design, with inputs from both humans and machine learning algorithms.

Engineering the perfect sauna

There is a growing body of literature which suggests hot and cold therapy (i.e. sauna and ice baths) are beneficial. The problem is that there one cannot avoid the 2nd law of thermodynamics, so although these therapies are beneficial to humans, they are less beneficial to our environment. In this theoretical project, you will design the world's most energy efficient hot/cold therapy device for home use. This project will introduce, or reinforce, concepts of thermodynamics, engineering design, and sustainable materials. This project will also introduce the concept of engineering (or computational) optimization, and students will become familiar with optimization techniques such as Genetic Algorithms (GA).

Coding skills

Python, Matlab

Teaching experience

I've taught in STEM-related classrooms to 7th grade students through UT's Scientists in Residence Program. I've tutored CAD and other engineering courses through online platforms. I've been a teaching assistant for both undergraduate and graduate courses in engineering (e.g. statics, dynamics, intro to engineering, etc.). The most current, and relevant, teaching experience is being a teaching assistant for a "freshman introduction to research in engineering" course - which employs a teach from behind approach to mentor freshman undergraduate students through a graduate-level research project.


Work experience

Bartell Machinery (2014 - 2016)
Design Engineer
re:3D Inc (2023 - Current)
Research Engineer


State University of New York College of Technology at Alfred
BS Bachelor of Science (2014)
Mechanical Engineering
University of Texas Austin (UT Austin)
PhD Doctor of Philosophy (2021)
Mechanical Engineering

Completed Projects

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