My research focus is currently on computer vision problems, mainly segmentation models. I have also worked on transfer learning in deep neural networks and how Bio-Inspired strategies can aid in the transfer of deep models. My doctoral research mainly involved Bio-Inspired Machine Learning, where nature-inspired techniques like evolutionary algorithms and artificial immune systems are applied to solve the problems. Thesis also comprised transfer learning in deep neural networks. Published works involve neuroevolutionary paradigms to evolve robot controllers online and onboard the robot, federated learning and also transfer learning in DNNs. My Experimental studies involve not just simulation but robots in the real world.