About

Vikramank Singh is an accomplished ML Scientist with a keen interest in complex, real-world, partially-observable dynamical systems. He has honed his skills in decision making under uncertainty using offline reinforcement learning. Currently, he is employed as an Applied Scientist II at AWS AI Labs, where he conducts research on Reinforcement Learning for Systems. Vikramank has a Master's degree in Artificial Intelligence from the University of California, Berkeley, where he also worked as a Graduate Student Researcher. During this time, he conducted research in Bayesian Inference, HMMs, Probabilistic Graphical Models, Variational Inference, Particle Filters, POMDPs, Model-based/Model-free Reinforcement Learning, Eligibility Traces, and Decision making under uncertainty. Prior to his current role, Vikramank worked as a Machine Learning Scientist at Ericsson, where he worked on several projects in Inverse Reinforcement learning, Optimal Control, Recommendation engines, and Secure Federated learning in large scale real-time network systems. Vikramank's educational background includes a Bachelor's degree in Computer Engineering from the University of Mumbai and a Higher Secondary degree in Electronics and Tele-Communication from St. Mary's Junior College. Vikramank is proficient in several technologies, including AWS, Research Scientist, AI, Reinforcement Learning, and ML, and has relevant experience of 5.02 years.