• I am a Research Engineer at Applied Intuition where I am helping build the on-road autonomy stack of the future. Before this, I was a Research Scientist at Cruise.
• My research interests span computer vision and machine learning with a focus on object detection and tracking, human activity recognition, driver behavior analysis, and driver safety systems in general. I am also particularly interested in sensor fusion and multi-modal approaches for real time algorithms.
• I received my Master’s and PhD in Electrical Engineering at UC San Diego where I was advised by Prof. Mohan M. Trivedi. As part of the Laboratory for Intelligent & Safe Automobiles (LISA), I developed unique models/algorithms to enhance driver and vehicle safety. I also oversaw the design, calibration and operation of heavily sensorized vehicular testbeds, as well as real-world data collection and labelling.

Updates

• September 2021: My doctoral dissertation titled Intelligent Human-in-the-Loop Vehicular Automation with Real-Time Vision Models was awarded the third prize in the annual IEEE ITS Best Dissertation Award.
• June 2021: I will be a keynote speaker at the Data Driven Intelligent Vehicle Applications workshop at IEEE IV 2021. More details to follow.
• May 2021: Our team at LISA has been hard at work with the Amazon ML Solutions Lab to create a unique video dataset to enable the next generation of automotive computer vision models. We plan to provide high-quality video data, fine-grained vehicle and roadway attributes, high accuracy localization and much more! You can read more about our progress so far in this blog post.