Use Cases of Reinforcement learning

About the speaker

Dr. Subarna Roy, a PhD holder in Applications of Econometrics and Game Theory, is currently an Associate Partner and Chief Data Scientist at IBM. She is recognised as one of the top 10 data scientists in India. She has over 14 years of experience in various domains such as banking, retail, and manufacturing. She has worked with TCS, HSBC, and ANZ before joining IBM. At IBM, she leads the data science division, delivering solutions in machine learning and deep learning. She has developed methodologies and delivered models on a wide range of topics, from credit scoring and fraud analytics to supply chain analytics and predictive maintenance. Dr. Roy has also published papers in international journals. Her work is instrumental in advancing the field of data science.

Synopsis

Dr. Subarna Roy shares her journey in the field of data science, tracing the evolution of the industry over the years. With a PhD in econometrics and game theory applications, Dr. Roy discusses leading data science initiatives at major companies like TCS, HSBC, and is currently serving as an Associate Partner and Chief Data Scientist at IBM.

The discussion then shifts to real-world applications of reinforcement learning. Dr Roy provides examples in banking, retail, manufacturing, utilities and more, where systems can learn optimised decision policies from continual interaction with their environment. Use cases may include dynamic pricing, logistics, predictive maintenance, and financial trading strategies.

Finally, Dr. Roy opens up the floor for audience questions about her background in economics, key differences between machine learning approaches, the future of AI regulation and ethics, skill sets needed for aspiring data scientists, and advice for transitioning careers into the industry. With over 14 years of solving complex analytics challenges, she provides unique perspectives on this rapidly evolving field.