profile pic

Michael S

- Research Program Mentor

PhD candidate at University of Pennsylvania (UPenn)


Robotics, Mechanical Engineering, Mechanical Design, Product Development


I am a PhD candidate at the University of Pennsylvania studying how we can use social robotics and computer vision to improve access to rehabilitation over telepresence. I am interested in how robots can interact with and measure people. I previously focused on designing and manufacturing medical devices and spent a while working on computer vision and collaborative robots for manufacturing.

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.

Designing a Robot to Elicit Emotional Responses

In this project you will design a robot from the neck up to convey emotions to people. Robotics is growing rapidly, but most people don't really know how to understand them. You will begin by surveying the state of the art in robotic design, looking at both research papers and robotics out in the wild. With the help of methods proposed in the literature, you will develop an understanding of what components would allow a robot to convey its emotions. Perhaps you will find that a screen with faces displayed and a neck that can look side to side is best. Maybe eyebrows are really important. Your reading will guide you. Once you understand what is important, you will sketch out a robot head and neck. You will use cardstock, bristol board, hobby servos, screens, arduino, etc. to put together a prototype. You will then program your new robot to express a few different emotions. You will test your robot's ability to convey emotions with a few friends and family. Finally you will report on your findings in a short paper, presenting the literature that you found, your approach to design, test methods, final design, results, and directions for future work.

Understanding Human Motion from Video

In this project you will apply off the shelf machine learning based systems to track people moving and say something about the quality of their motion. As people age, recover from injury, and develop new skills, the way they move changes. Understanding these changes can allow tracking of progress. You will identify a motion/series of motions that you are particularly interested in, you will record yourself and a few friends doing that motion both normally and with a simulated injury (by adding weight to your arm). You will briefly read up on a set of pose tracking algorithms and pick one to use, which will give you joint positions over time. You will then turn to the literature to identify a few key measurements that you can make that will indicate quality of motion (ex: max speed of motion, smoothness of motion). You will implement these features to calculate them across your dataset. You will then segment your data into both a training and test set. You will choose a simple machine learning classification algorithm to classify motions into normal or impaired. You will present your findings in a short report outlining the state of the art, your goals, approach, results, and how you could extend the project further.

Coding skills

python, R, typescript, bash

Teaching experience

Throughout the course of my PhD research I have directly mentored over a dozen students working in rehab robotics. I have guided them through the process of learning about a research space from the literature, finding interesting questions to ask, building and testing hypotheses, and presenting results. I have also spent two semesters teaching the freshman mechanics lab at the University of Pennsylvania and a semester as a TA for undergraduate dynamics. I have mentored and taught students with a wide range of backgrounds and skill levels and am excited to meet you!


Work experience

University of Pennsylvania (2016 - Current)
PhD Student / Graduate Researcher
Georgia Institute of Technology (2015 - 2016)
Research Technician II
Eli Lilly and Company (2015 - 2015)
Automation Intern
Georgia Institute of Technology (2014 - 2015)
Machine Shop Supervisor


Georgia Institute of Technology
BS Bachelor of Science (2015)
Biomedical Engineering
University of Pennsylvania (UPenn)
MS Master of Science (2019)
University of Pennsylvania (UPenn)
PhD Doctor of Philosophy candidate
Mechanical Engineering

Interested in working with expert mentors like Michael?

Apply now