Abstract

The intersection of artificial intelligence (AI) and materials science is rapidly transforming the way new materials are discovered, designed, and optimized. Traditional approaches in materials research often rely on time-consuming experimental procedures or computationally expensive simulations. AI and machine learning (ML) offer powerful alternatives by learning complex structure- property relationships directly from data, enabling accelerated prediction of material properties, identification of novel compounds, and real-time process optimization. By integrating diverse data sources—ranging from high-throughput experiments to first-principles calculations—ML models can uncover hidden patterns and guide researchers toward promising material candidates with unprecedented speed. This talk will shed light on how AI/ML methods are reshaping key areas of materials science, from predicting transformation temperatures to doing image analysis of microstructure images and thereby designing materials with target properties. The talk will also highlight the importance of materials databases & the features of the AMDAD tool developed by DYSL -SM.

Bio

KNS Pavan Kumar did his B. Tech in Metallurgical & Materials Engineering from IIT Madras in 2015 and worked in a PSU for half-decade and moved to DRDO in 2020. He pursued PG program in Artificial Intelligence (AI) & Machine Learning (ML) from IIIT Hyderabad and is a certified AI/ML professional by DIAT , Pune. His research interest include – applications of AI/ML in Materials Science (Materials Informatics), Development of shape Memory Alloys, Auxetic & Thermoelectric smart materials for defense applications. His team has developed an Integrated tool for Accelerated Materials Design & Development (AMDAD) and deployed it in DRDO.