Vijayasarathi Balasubramanian

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Published on 22, Aug 2023

Data Scientist Vijayasarathi Balasubramanian Looks Optimistically on the World of AI

The history of artificial intelligence, or AI, goes far back than people might originally think. Scientists and engineers first broke ground with the technology back in 1943, which gave way to the neural network foundation that AI uses today. Since its inception, various technical professionals have tried their hand at shaping AI into the complicated system of interconnected subsets we now know.

One such expert, Vijayasarathi Balasubramanian, who also goes by Vijay, is a data scientist who has been using AI in a professional capacity for years. He’s been manipulating AI’s subset of machine learning (ML) to create recommender systems for e-commerce and businesses. Recommender systems use process pools of big data to suggest products or services to consumers based on transaction histories or similar behaviors and buying patterns from other users.

But e-commerce isn’t the only beneficiary of AI. The technology has overall become a dynamic tool system that’s used across a spectrum of industries, such as finance, healthcare, cybersecurity, agriculture, manufacturing, and transportation.

“I’m excited about the future of this technology,” says Vijay. “This space is growing rapidly, and I believe that artificial intelligence is only as good as the companies and individuals who use them. Companies can really benefit from its intentional utility. Once properly implemented, consumers will appreciate smoother sales processes and might even be excited about buying things in the future.”

Vijay first got his roots in AI back in 2006. He was one of the forerunners who implemented this technology to organize and create insights from multi-terabyte unstructured data for British Telecom, the largest Telecom provider in the UK, which has a massive presence in over 180 countries. It was these assignments that piqued his interest for data science, and it wasn’t long before Vijay graduated with a Masters in Data Science at the University of Notre Dame. The algorithms and techniques he learned in Notre Dame helped him create enterprise scale data products and apply advanced machine learning to solve real world problems.

After moving to the United States, his career continued to advance, and he refined his craft in the retail and telecom domains. He developed expertise in developing advanced data science solutions in a hybrid cloud environment, developing state-of-the-art machine learning models, and deriving key insights of large allocated data sets. Such key insights include breaking down customer information into demographic, geographic location, and product or service popularity. He uses these insights to hone various ML technology, such as the ones behind product recommendation algorithms.

Vijay is a firm believer of the Paulo Coelho quote, “Do one thing at a time but do it like no one has ever imagined.” Considering how passionate Vijay is about the field, and with 17 years of dedicated experience in this space, he’s been helping large corporations use machine learning at scale. Because of this, he has given companies a fresher, more dynamic understanding of the tools that are so close at hand and the endless possibilities they afford.

“I’m looking forward to the future,” Vijay says, “in regards to both data science and my own. I feel like I’m still getting started, and I have big plans for what I want to do next. For now, though, I’m very happy doing what I’m doing right now.”

ABOUT VIJAYASARATHI BALASUBRAMANIAN

Vijayasarathi Balasubramanian currently works as a Senior Data and Applied Scientist at Microsoft. Outside of what he does professionally, he contributes to the open source community like Apache Airflow, Apache Beam, and TensorFlow and mentors AI startup founders and data science professionals across various platforms. He’s also associated with technical organizations including IEEE, IET, and BCS.

To learn more about Vijay or his future pursuits, you can find him on his website.

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