About

Jebastin Nadar is an accomplished Machine Learning Engineer with over 2 years of experience in the field. Currently, he is working at Drishti as an ML Engineer, where he is responsible for developing and implementing machine learning models for various applications. Jebastin has a strong background in Computer Vision and has previously worked as a Computer Vision Intern at Shunya OS. During his tenure, he designed custom architectures, training methodology, and loss functions for high-accuracy instance segmentation. Additionally, he has also worked as a Google Summer of Code Student at OpenCV, where he added 8-bit quantization support in OpenCV's DNN module, improving the latency by 1.5x - 3x and reducing memory consumption by 4x, without a significant effect on the model's accuracy. Jebastin holds a Bachelor of Science degree in Statistics from St. Xavier's College, where he graduated in 2021. He has a strong technical skill set, which includes expertise in ML, OpenCV, Computer Vision, Object detection, Image Processing, Deep Learning, Object Detection, Pytorch, Python, Tensorflow, AI, CNN, Kubernetes, Docker, and infra. In summary, Jebastin is a highly skilled and experienced Machine Learning Engineer with a strong background in Computer Vision. He has a proven track record of designing and implementing complex machine learning models and has a deep understanding of various ML technologies and frameworks. He is a quick learner, a team player, and is always striving to improve his skills and knowledge in the field.