Sriram Ragunathan

Sriram Ragunathan is a mechanical engineering graduate whose passion lies in Artificial Intelligence, Machine Learning, and Computer Vision. He is an Algorithmic trader actively involved in the development and testing of algorithms within the stock market. Sriram possesses strong skills in visualizing real-life problems, conducting data mining, and mathematically modeling these issues to be solved through machine learning applications. His expertise includes time series prediction, Convolutional Neural Networks (CNN), and Reinforcement Learning, with proficiency in algorithms such as Recurrent Neural Networks (RNN), CovNets, Random Forest, Support Vector Machines (SVM), K-Nearest Neighbors (KNN), and K-Means, as well as Deep Reinforcement Learning. Additionally, he has experience in deploying and maintaining scalable machine learning models as micro-services, utilizing frameworks like Flask, Falcon, Django, Spring, Tensorflow serving, and gRPC. Sriram is well-versed in modern models like Generative Adversarial Networks (GAN), Generative Query Networks (GQN), and Variational Auto Encoders. He pursued his Bachelor's in Mechanical Engineering from the College of Engineering, Guindy, and has held positions as a Senior Data Scientist at Grab and FourKites, Inc., as well as previous roles at myGate, NDOT Technologies, and as a Technical Marketing Executive at L&T Construction & Mining Business.