About

Brungi Vishwa Sourab is a seasoned data scientist with almost 5 years of experience in building and deploying Deep Learning pipelines and solutions on edge and cloud. He has a strong background in devising data-driven solutions for complex business problems and communicating effectively with a wide range of audiences. Brungi has hands-on expertise in developing and deploying AI solutions in the healthcare and financial industries. Brungi's technical skills include proficiency in languages and frameworks such as Python, Keras, Scikit-learn, Pytorch, TorchScript, TensorFlow, TensorFlow Lite, Flask, Streamlit, and SQL. He is also skilled in machine learning techniques such as linear and logistic regression, decision trees, support vector machines (SVM), ensemble methods, principal component analysis (PCA), independent component analysis (ICA), and clustering methods. Brungi has deep learning expertise in deep neural networks, convolutional neural networks (CNN), recurrent neural networks (RNN), autoencoders, GANs, and deployment on edge and cloud - NVIDIA Jetson, Intel Neural Compute Stick. He is skilled in model optimization techniques such as quantization, pruning, TensorRT, ONNX, ONNX Runtime, and TVM. Brungi is also proficient in cloud technologies such as Azure ML and AWS Sagemaker. In addition, he has experience in reinforcement learning techniques such as Monte Carlo methods, deep-Q-learning, policy-based, and actor-critic methods. Currently working as an independent consultant at Udacity, Brungi provides project reviews and other student support services utilizing his specialized knowledge in the field of machine learning and strong communication skills. In his past roles, he has worked as a consultant in data science at Tapchief and as a data scientist at Innominds. In these roles, he has worked on projects involving healthcare and financial services providers, utilizing advanced computer vision techniques to build and deploy solutions on edge devices, and developing models to forecast the risk of client portfolios using advanced deep learning methods. Brungi holds an Engineer's degree in Computer Engineering from Lovely Professional University and a Nanodegree in Machine Learning from Udacity. His relevant experience in the field of data science is almost 5 years, during which he has gained expertise in deep learning, reinforcement learning, computer vision, and AI.