Kabir Chhabra has recently graduated with a Masters in Computer Science from the University of Southern California. He is passionate about Machine Learning, Deep Learning and Statistical Modelling, and their applications to Computer Vision, Healthcare and other fields.

Kabir has an extensive background, having interned at GE Healthcare, where he was responsible for designing and coding an end-to-end framework for automating Neural Network compression for image segmentation tasks, based on a reinforcement learning approach. At Qeexo, he was responsible for making the AutoML platform memory efficient by proposing and implementing architectural code changes to remove redundant memory utilization. He also had the opportunity to intern at the Salisbury Robotics lab at Stanford, where he leveraged Deep Learning with Attention to automate the recognition of materials by a robotic arm, and at Amazon Machine Learning, Bangalore, where he worked on defining and measuring the downstream impact of a customer’s first purchase on future interactions with the Amazon marketplace. During his undergraduate study at IIT Delhi, he worked on Machine Learning projects in a variety of fields, and for his thesis he built a statistical model for the functional connectivity of a healthy human brain, to be used for contrasting with diseased human brains to learn the unique characteristics of various brain diseases.

Kabir says “Having grown up and trained in India, I feel it is now appropriate to give back the society, especially to the underserved section. The Spine Wellness Care Foundation is an appropriate opportunity for me to do so. I am confident that my research experience in multiple domains, spanning both academia and industry, strong functional expertise, involvement in multi-functional teams and professional qualities will help me deliver in this regard.”