Although science and management are two distinct fields of study, scientific discoveries and inventions have affected business, disrupted markets, and created new trends. Data Science is one such technology that is transforming the way we do business. Machine learning algorithms are helping to predict the stock market trends, credit risks, hire new employees, automate manufacturing plants, etc. This intersection of science and management is what entices Anusha Kumar, a young Data Science researcher who is currently doing her PhD from IIT Madras and working at this interface.

Always interested in mathematics and logic, Anusha’s journey in research was inspired by her brother, who is also in research. Born and brought up in Chennai, she pursued engineering in Computer Science from Sri Venkateswara College of Engineering in Tamil Nadu. Her love for machine learning blossomed in the final year of her B.E while doing a research project on smart parking systems. The project was aimed at building an application to find a vacant parking spot in a given area and perform dynamic pricing to maximize profit using machine learning technology. The scope of machine learning excited Anusha, and she decided to study more to know about the field.

For further studies, she got enrolled in a dual degree program at IIT Madras. Here at IIT Madras, she took courses such as operations research, data analytics, machine learning, stochastic modeling, multivariate statistical methods, etc., which gave her exposure to management and more expertise in Data Science. During her masters, she did a project on the automated categorization of attributes from online ratings based on the Kano model with Dr Nandan Sudarsanam. The work got accepted at a prestigious international conference which gave her confidence to think about continuing research. Pursuing a PhD, she remembers, was a tough decision for her but motivation from parents and her supervisor Dr Sudarsanam helped her to take this leap of faith.

Anusha is currently working on resource optimization in live experimental settings that are non-stationary. With rapid interdisciplinary growth in experimentation and multi-armed bandit frameworks, her research draws attention to various idiosyncrasies in live experiments such as temporal changes, interventions, and human interactions. Anusha has also been part of a collaborative research on quantifying the optimal response that can be discovered in a design space. She aims to build a framework that models the cost-benefit tradeoff in real-world applications and is also actively exploring international collaborative opportunities. While her PhD is on the problem of optimizing resources in a live setting, she is working on several other research projects in the lab to expand her skill set. One of these projects is with the Dvara trust, where machine learning is being used to detect household over-indebtedness. 

Anusha believes that the scope of Data Science is immense in the business, marketing, and finance sectors, and these sectors can maximize their return on investment by adding this layer of complexity to their existing framework. When not working on her research problem, she loves to do artwork and play carrom and badminton.