DATA SCIENCE RESEARCH GROUP

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The Data Science Research Group at IIIT Kottayam focuses on both fundamental research in the field of data science and applied research in areas where data science can provide valuable insights that can be used for decision making. The primary focus of the group is on the creation of algorithmic approaches and methodological workflows for the purpose of achieving scalable solutions in major social, scientific and societal application domains. Additionally, the group is dedicated to the resolution of challenges in implementing data science projects in industry/realtime. Our techniques and solutions are influenced both directly and indirectly by real-world applications and use cases.

Research Areas Covered

Business Analytics

Business analytics has existed for a very long time and has evolved as newer and better technology have been available. Business analytics has numerous applications and functions. It can be used for descriptive analysis, in which data is used to comprehend past and present circumstances.


This type of descriptive analysis is used to evaluate a company's present market position and the efficacy of its previous business decisions.Some of the usecases of Business analytics include Improving Productivity and Collaboration, Enhancing Customer Support, Forecasting Orders and Recipes, Targeting Consumers.

Machine Learning

Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks.[1] It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so.[2] Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks

Deep Learning

Models that utilise deep learning can attain state-of-the-art precision, sometimes surpassing human performance. Using a vast amount of labelled data and neural network topologies with multiple layers, models are trained. Many artificial intelligence (AI) apps and services that enhance automation by executing analytical and physical activities without human intervention are driven by deep learning. Deep learning technology underpins both common and upcoming products and services (such as digital assistants, voice-enabled TV remotes, and credit card fraud detection) (such as self-driving cars).

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