About Me

I am a recent graduate student of the Master of Science in Robotics program from the Robotics Institute, Carnegie Mellon University. At CMU, I worked with Prof. Maxim Likhachev at the Search Based Planning Lab. My research at CMU was focused on developing a high precision pose estimation (3D object detection) algorithm called PERCH 2.0, that can be used for robotic manipulation in complex environments. PERCH 2.0 achieves high accuracy and low training requirement through a combination of deliberative and discriminative perception techniques.

In the past 6 years, I have worked with multiple academic advisors, startup founders and managers to further the research at their labs, help turn tech ideas into products at their startups or enhance the status quo of projects being undertaken at their company. Through these engagements, I have acquired a diverse skill set that spans multiple programming languages, platforms and devices.

At present, I am a Lead Robotics Engineer at Nimble AI, a San Francisco based startup focused on warehouse automation through robotic manipulation. As a part of the robotics and perception teams, I have led projects to research, design and deploy algorithms that are accurate (for high manipulation success), fast (for a high task throughput) and scalable (for rapid deployment). On the perception front, I worked on the introduction of instance segmentation and pose estimation to the Nimble stack. On the robotics front, I led large scale projects to introduce and deploy fast environment-based motion planning across the Nimble fleet. More recently, I led a project to re-design the task creation and coordination stack for higher scalability and modularity. My projects over the last year, culminated in the successful addition of more robots at a Nimble customer site, making it Nimble’s largest deployment so far.