About

Shashank Vasisht is a highly skilled Computer Vision Engineer with a passion for Artificial Intelligence (AI). He has over 5 years of experience in the field of Advanced Driving Assistance Systems (ADAS) and Medical Image Analysis. Currently working at Fynd, Shashank provides deep learning and computer vision-based solutions for projects such as Parking Assistance systems. Shashank's expertise lies in state-of-the-art Object detection, Semantic segmentation techniques, Object Tracking, 3D Monocular Object Detection, and Classical Computer Vision-based techniques. He has worked with TBs of data and actively participated in strategy development for GT marking. He has also researched and implemented the latest developments in efficient Single shot object detection systems. Prior to Fynd, Shashank worked at Mando as a Deep Learning Engineer where he developed a 3D-Object detection algorithm using Deep Learning-Computer Vision which requires only Monocular Camera Input and Camera Intrinsic info to run in real-time on GPU. He also worked on State of the art tracking algorithms like Kalman Filter based SORT and developed a Deep Learning-Computer Vision based Object detection system for Parking Assist (General Object Detection) systems and Lane Keep Assist (Road Markings detection) systems on Fish-eye camera Images. Shashank also developed a novel real-time Pedestrian Detection system which works at 60+ FPS on a 2080Ti GPU and 32fps on Qualcomm 6155 board. Shashank has a Bachelor of Technology in Electronics and Communications Engineering from Bharati Vidyapeeth's College of Engineering. He has a TechStack that includes Computer Vision, Deep Learning, Object detection, Image Processing, Object Detection, Research Scientist, ML, AI, Python, TensorFlow, Pytorch, SVM, Keras, Perceptron, OpenCV, and Pandas. Shashank is an AI enthusiast who is passionate about developing innovative solutions using AI and Computer Vision. He is always looking for opportunities to learn and grow in his field.