Chris Powers

Chris Powers has a diverse work experience in the field of machine learning and robotics. Chris is currently working as a Machine Learning Engineer at Cobalt Robotics, where they apply deep learning, unsupervised learning, and computer vision techniques to enhance security functions. Chris has designed a tracking system to filter duplicates, reducing operator workload, and automated the detection of security risks using unsupervised learning and edge detection.

Prior to that, Chris served as the Machine Learning Systems Lead at a Stealth Startup from 2020 to 2021. In this role, they designed the microservice architecture for an end-to-end learning pipeline and created a real-time analytics dashboard for users. Chris utilized MongoDB, Amazon S3, Redis, GRPC, and HTTP for storage and communication.

From 2018 to 2020, Chris worked as a Researcher at Berkeley DeepDrive, collaborating with Professor Trevor Darrell and Postdoc Fisher Yu on research related to self-driving cars. Chris also led a team in revamping an open-source image annotation tool with real-time collaboration and interactive model-assisted labeling.

Chris gained industry experience as a Yelp Software Engineering Intern in 2018, and as an Undergraduate Researcher at UC Berkeley AUTOLab from 2016 to 2018. At AUTOLab, they worked with Professor Ken Goldberg on applying learning to robotics and achieved notable success in projects such as developing a robotic decluttering algorithm.

In addition to their professional roles, Chris has actively contributed to the academic community. Chris served as EE16B Course Staff at UC Berkeley College of Engineering in 2017 and volunteered as a ULAB Mentor, mentoring freshman students on their research project to design an automated weed-killing robot.

Overall, Chris Powers has a strong background in machine learning, robotics, and software engineering, with valuable experiences in research, industry, and mentoring.

Chris Powers attended the University of California, Berkeley from 2015 to 2019, where they earned a Bachelor's degree in Electrical Engineering and Computer Science. Chris then continued their education at the same institution from 2019 to 2020, obtaining a Master's degree in the same field.