Team

Roma Desai is a fourth year EECS student at UC Berkeley. She has taken a wide variety of advanced courses in EECS in artificial intelligence, machine learning, computer vision, algorithms, and in prototyping and fabrication at the Jacobs Institute of Design Innovation. She is also an experienced product manager with multiple product management internships at leading companies like Salesforce and Zoom. She is also a skilled programmer and software engineer highly skilled in Python, Java, and C software development. Her skills also include prototyping and fabrication using CAD (Fusion 360, Inventor) and 3D printing.

Roma’s contributions to the project include actively participating in all aspects of software development, in lab experimentation and debugging, deriving the dynamics model, as well as leading fabrication efforts of necessary props and materials. All team members contributed equally towards developing checkpoints and this final report.

Ethan Mehta is a fourth year EECS and Business Administration student at UC Berkeley. He has taken a number of advanced courses in EECS including courses in machine learning, artificial intelligence, signal processing, and algorithms. He is also an experienced software engineer with experience at both large companies like Amazon and at small startup companies. He is currently conducting machine learning research at the RISELab for his computer science senior honors thesis. Ethan has also been an avid teacher and student facilitator as a DeCal facilitator for IEEE’s micromouse decal in previous semesters and as a TA/uGSI for CS 61B. He is very comfortable with software development in Python, Java, Matlab, ROS, and C.

Ethan’s contributions to the project include actively participating in all aspects of the project including software development, deriving the dynamics of the proposed model, and in-lab experimentation and debugging. All team members contributed equally towards developing checkpoints and this final report.

Austin Patel is a third year EECS student at UC Berkeley. He has taken many advanced EECS courses including courses in signals and systems, computer vision, artificial intelligence, algorithms, probability and statistics, and optimization prior to taking EECS 106A. His previous experience includes work as a software engineering intern at Autodesk and Apple. He is currently conducting research in Microrobotics at UC Berkeley’s Berkeley Autonomous Microsystems Laboratory and in Computer Vision as an undergraduate member of Berkeley’s computer vision group in Hand/Object Detection. Besides classes, work, and research, Austin is an avid teacher and is currently on the course staff for EECS 16A. As a software engineer, he is highly comfortable with Python, Java, C, Go, and ROS.

Austin’s contributions to the project include leading software development, actively contributing to in-lab experimentation and debugging, and contributing heavily to developing/deriving the torsional spring model. All team members contributed equally towards developing checkpoints and this final report.