profile picture

Ryan S

- Research Program Mentor

MEng at Massachusetts Institute of Technology


Deep Reinforcement Learning, Computer Vision, Machine Learning, Neural Networks, Perception


I recently finished my Master's at MIT, where I studied artificial intelligence and conducted research in MIT CSAIL's Distributed Robotics Laboratory under Professor Daniela Rus and Professor Sertac Karaman. I completed my undergrad in electrical engineering and computer science and mathematical economics at MIT in 2020. My main Master's research was at the intersection of deep reinforcement learning, computer vision, and robotics. Specifically, I worked on improving the sample efficiency of deep reinforcement learning algorithms for autonomous driving applications. I am also interested in the fields of optimization, game theory, and electromagnetics. Outside of MIT, I now work as an image scientist, and I enjoy Krav Maga, weightlifting, biking, and dark roast coffee. I have recently discovered my passion for teaching and mentorship, as well as technical writing. Finally, I would not be who I am without my favorite playlists on Spotify!

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.

Training a Deep Reinforcement Learning Agent with TensorFlow Agents and OpenAI Gym!

Deep Reinforcement Learning is a rapidly growing field at the intersection of machine learning and robotics, and through this project, you will have the chance to implement deep reinforcement learning agents yourself! We will implement this project using TensorFlow-Agents, a powerful library for training agents to solve tasks such as getting a Half-Cheetah to walk, balancing an Inverted Pendulum, or teaching a car to race autonomously (all in simulation).

Fingerprint Classification and Pattern Recognition in Keras

Ever wondered how fingerprint scanners work? In this project, we will study and implement some ways in which fingerprints can be detected and identified using deep learning (implemented through Keras in Python) and classical computer vision techniques Iimplemented through OpenCV in Python).

Computer Vision for Autonomous Driving!

Fast and accurate vision is a crucial component for the successful adoption of autonomous vehicles as a widespread technology. In this project, we will use Python and PyTorch, a deep learning library, to segment different objects using RGB cameras and lidar sensors!

Coding skills

python, PyTorch, TensorFlow, NumPy, Scikit-Learn, AWS, Ubuntu, ROS, C++, Stata, Matlab, SLURM

Teaching experience

AT MIT, I have worked as a Graduate Teaching Assistant for 6.s191 (Introduction to Deep Learning) and 6.801/6.866 (Machine Vision). Additionally, I collaboratively taught a data science and machine learning workshop in Montevideo, Uruguay during January 2020 with the MIT Global Startup Labs (GSL) team. In my free time, I tutor students of all ages and backgrounds in machine learning, computer vision, python, and econometrics, with over 450 hours of one-on-one tutoring experience. I enjoy working with my students to help them take ownership of their learning while gaining the skills and confidence to succeed in whatever they set their mind to.


Work experience

MIT Computer Science and Artificial Intelligence Laboratory (2019 - 2021)
Research Assistant
Nasdaq (2020 - 2020)
Data Science and Machine Learning Intern
Spacemaker AI (2019 - 2019)
Data Science Intern
United States Department of Defense (2018 - Current)
Image Scientist


Massachusetts Institute of Technology
BS Bachelor of Science
Electrical Engineering and Computer Science, Mathematical Economics
Massachusetts Institute of Technology
MEng Master of Engineering (2021)
Artificial Intelligence

Interested in working with expert mentors like Ryan?

Apply now