The field of Data Science (DS) has grown from a bunch of "fancy" techniques that could "also" be applied into a set of well-founded methods to solve hard problems in various fields such as engineering and technology, science, and economics. This ubiquitous applicability of Data Science/ Artificial Intelligence (DS/AI) to a wide array of problems is a direct consequence of its generality, which in turn, has been fueled by the complementary interaction between theory and application.

Theoretical foundations of DS lie in machine learning algorithms, optimization, decision theory, and statistical learning theory. This foundational base ensures the guaranteed performance of DS/AI techniques while they are scaled across various problem domains. As DS methods are applied to newer application domains, each application domain throws new challenges to theorists. Thus several aspects of DS/AI which are of current interest to theorists such as (not limited to) privacy, security, sample efficiency, transfer learning, domain adaptation, fairness, and interpretability are primarily rooted in various application domains. With the increasing complexity and computing needs of the data-heavy models and approaches novel innovations in systems are also very important. This gives the foundational knowledge in implementing the solutions efficiently.

To sum up, the successful practice of DS entails proficiency in theory, implementation, and application domains. Given the potential impact of DS/AI in solving hard problems there is a ‘DS/AI’ push across the world. In order to be able to make an impact, it is important to make inroads in theory as well as applications. This high interdisciplinary work brings expertise from several domains into this department of Data Science and Engineering at IIT Palakkad. The department hosts research and education activities around AI and DS at IIT PKD. We are going to reach far beyond the common notion of developing AI-based tools and solving DS-related problems or rather conducting educational programs. We look forward to bringing the developments closer to society and nature.