I am a student in Master of Science in Computer Vision (MSCV) at Carnegie Mellon University.
I have experience working on Object Detection, Pose Estimation and Action Recognition. I have collaborated with Torr Vision Group and NVIDIA in the past.
I am a graduate student (MSCV) at CMU (Robotics Institute, School of Computer Science). I worked at Apple for the Summer’21 internship (AI/ML)- Siri Visual Intelligence Team.
I did my undergrad at IIT Roorkee (India). I have around 3 years of industrial work experience in AI. I like to research and explore the latest techniques pertaining to AI. My goal is to continue developing AI-based solutions for multiple domains.
We explored the various datasets together – KITTI, nuScenes. Shubham primarily worked setting up the distance-based evaluation framework including dataset preparation, metrics, while Jeet worked on trying various Fusion methods – NMS, AdaNMS etc.
I am currently a principal scientist at Argo AI and the director of the CMU Argo AI Center for Autonomous Vehicle Research.
My research focuses on computer vision, often motivated by the task of understanding people from visual data. My work tends to make heavy use of machine learning techniques, often using the human visual system as inspiration. For example, temporal processing is a key component of human perception, but is still relatively unexploited in current visual recognition systems. Machine learning from big (visual) data allows systems to learn subtle statistical regularities of the visual world. But humans have the ability to learn from very few examples