Machine learning research in vision, language, and robotics. Mountain View, California.
Everyday Robots spun out of X in November 2021. Mountain View, California.
Early ML engineer at The Everyday Robot Project. Mountain View, California.
Worked on perception for human-robot interaction. Mountain View, California.
Worked on experimental augmented reality. Created environmental lighting system allowing more photorealistic lighting and reflections in augmented reality for Tango SDK. Published Google Developer Blog post with tutorial for usage. Also experimented with video stabilization. Experience in computer vision, computer graphics, and computational photography. Worked with C++, Unity, and Java. Mountain View, California.
Served as an intern on tools and infrastructure for Chrome for Android. All code is open source as part of Chromium. Wrote test infrastructure for sign-in authentication test. Also created parametrizable testing framework. All my code is open source as part of Chromium! Worked with Java, Python, and C++. Mountain View, California.
Used machine learning for health care data analytics. Clustered co-morbidity for several sets of patients. Experience in data visualization. Worked with R, Python, and D3.js. Austin, Texas.
In the proceedings of Robotics: Science and Systems (RSS), 2023.
In the proceedings of International Conference on Robotics and Automation (ICRA), 2023.
In the proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018.
In the proceedings of IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 2018.
Honors Thesis: Deep Reinforcement Learning for Aerial Obstacle Avoidance using Monocular RGB Images
Worked on semantic mapping and social navigation for non-anthropomorphic robots with Building-wide Intelligence (BWI) project. Austin, Texas.
Research in human robot interaction in the Personal Autonomous Robotics Lab (PeARL) and Socially Intelligent Machines (SiM) Lab. Experience in behavior architectures, perception, manipulation, and machine learning. Austin, Texas.
Selected by Professor Joydeep Ghosh in the University of Texas Electrical and Computer Engineering department in the Intelligent Data Exploration and Analysis Laboratory (IDEAL). Lab focuses on machine learning and data mining. Research on making self-driving cars a safe reality using distributed machine learning through wireless mmWave communication in collaboration with Dr. Robert Heath. [In the news] Austin, Texas.
Mentor for FIRST Robotics Competition for team 1700. Palo Alto, CA.