About

Aman Sharma is a highly motivated and creative individual who is currently building chatbots at Oracle as a Senior Member of Technical Staff. With a passion for making data sing, Aman is intrigued by the patterns, causality, and correlations that run through the fibres of our existence. He is constantly learning to quantify these patterns into models and leverage them to make our lives more efficient and simpler. Aman has 3.11 years of relevant experience in the field of software engineering and research science. He is currently working as a Professional Assistant for the software development and educational technology unit at BITS Pilani, where he is responsible for the development and maintenance of software/applications used in-house for various purposes. Prior to this, Aman worked as an Instructor at the Centre for Software Development at BITS Pilani, where he taught a course on Introduction to Machine Learning to a class of students from various disciplines. Aman has also worked as an Applied Scientist at Amazon, where he collaborated with the platform development team to develop a hybrid demand forecasting algorithm for high-dimensional sparse timeseries. He proposed and trained a novel two-phase network consisting of a global neural matrix factorisation model and a local Temporal Convolutional Network on available products' demand history with their co-variates to overcome the problem of cold start and to make the demand forecast for newly added/unseen products. Aman holds a Master of Engineering in Computer Science from Birla Institute of Technology and Science, Pilani, and a Bachelor of Technology in Computer Science from J.K. Institute of Applied Physics and Technology. He also completed his 12th standard from Kendriya Vidyalaya, where he studied Mathematics, Physics, Chemistry & Computer Science, and his 10th standard from the same school, where he studied Science. Aman's tech stack includes expertise in software engineering and research science. He is a highly motivated and creative individual with a passion for making data sing and is always looking for ways to leverage patterns, causality, and correlations to make our lives simpler and more efficient.