Invited Talks

Title: Beyond Data: Emerging Frontiers in Artificial Intelligence, Machine Learning, and Data Science

Abstract:

Artificial Intelligence (AI), Machine Learning (ML), and Data Science are moving beyond conventional predictive analytics towards adaptive, generative, and increasingly autonomous computational systems. This invited talk examines the technical frontiers driving this transition, with emphasis on deep neural networks, transformer architectures, foundation models, generative AI, representation learning, and data-centric machine learning. It explores how self-supervised and transfer learning, multimodal modelling, and retrieval-augmented generation are reshaping modern AI pipelines and enabling systems to operate on complex, heterogeneous, and high-dimensional data. The talk also considers the engineering challenges that determine whether advanced models can move reliably from experimentation to deployment. Key issues include generalisation, explainability, uncertainty quantification, robustness, model drift, privacy, computational efficiency, lifecycle monitoring, and human-in-the-loop validation. These considerations are particularly important as AI becomes integrated with intelligent manufacturing, semiconductor systems, digital twins, autonomous platforms, and edge-cloud computing. Finally, the presentation discusses emerging research directions at the convergence of foundation models, multimodal intelligence, domain-specific AI, and data-driven optimisation. The objective is to provide an engineering perspective on the evolution from extracting patterns from data to building trustworthy systems capable of contextual learning, reasoning, adaptation, and decision support, while highlighting the architectural, data, evaluation, and governance challenges that must be addressed for scalable real-world adoption.

Bio:

Padmaja Pulivarthy is a specialist in enterprise data systems and AI/ML engineering with a proven track record of building scalable technology solutions for the banking, pharmaceutical, and semiconductor sectors. A two-time DBMS Star Award winner, her expertise spans AWS, Hadoop, Spark, Kafka, and advanced database management. Padmaja bridges the gap between theory and practice as an independent researcher with 20+ publications and 260+ citations in the fields of predictive analytics and intelligent database systems. She holds an MCA with Distinction from Periyar University.

Currently Working as a Enterprise Data Systems Sr Engineer in Samsung Austin Semiconductors in Austin Texas USA.