TLDR: Data engineer Sree Hari Subhash is pioneering the development of advanced AI tools that function as ‘professional employees’ across various sectors, including human resources and healthcare. His work at Yum! Brands Inc. involved integrating an AI-based digital assistant into HR and payroll systems, significantly improving efficiency and employee support. Furthermore, his research in healthcare has led to the development of an ‘artificial doctor’ capable of predicting Alzheimer’s disease with high accuracy through handwriting analysis, marking a significant advancement in AI’s medical applications.
In a groundbreaking development, data engineer Sree Hari Subhash is transforming traditional work processes by creating sophisticated Artificial Intelligence tools designed to operate as ‘professional employees’ in diverse industries. His innovative approach is already making a significant impact in sectors like human resources and healthcare, demonstrating AI’s profound potential beyond mere automation.
At Yum! Brands Inc., a leader in the restaurant industry, Subhash spearheaded a project to integrate an AI-based digital assistant into the company’s human resources and payroll systems. This initiative aimed to provide employees with immediate and personalized support, eliminating the need to wait for human HR specialists. Subhash detailed the challenges and successes of this implementation, stating, ‘One of the most interesting challenges we faced was the introduction of a digital assistant based on AI in Oracle Cloud. This allowed our employees to receive support more quickly and without the need for HR involvement. We have automated the processes related to personnel management, from calculating 401K to integrating payroll systems. I have been creating data models and reports to ensure timely and accurate analytics.’ The system facilitates two-way data exchange, enabling the AI assistant to retrieve up-to-date employee information and even make system changes with appropriate access rights. This led to the rapid resolution of tasks such as requesting information, updating banking details, checking bonus statuses, and booking vacations, which were previously handled manually. The integration also included Oracle Business Intelligence for analytics, recording communication sessions to identify bottlenecks and continuously improve HR processes. Subhash also automated reporting using IBM DataStage for real-time performance monitoring and script updates.
Beyond corporate applications, Subhash has extended his expertise to healthcare, investigating how machine learning systems can enhance medical processes. His project focused on developing an ‘artificial doctor,’ a more complex endeavor given the vast and intricate nature of medical knowledge. A significant area of his research involves predicting Alzheimer’s disease using machine learning methods, specifically through the analysis of handwriting. This research aims to identify early signs of the disease by analyzing complex data sets, including cognitive tests and medical indicators. Utilizing the UCI Machine Learning Repository’s DARWIN dataset, which contains handwriting characteristics of 174 individuals (89 with Alzheimer’s and 85 healthy), Subhash employed the RapidMiner platform to compare various machine learning algorithms, including SVM, decision trees, and logistic regression. The objective was to predict Alzheimer’s patients with precision while minimizing false positives.
Remarkably, the AI achieved an 86% success rate in detecting Alzheimer’s patients and 77% in identifying healthy individuals. Subhash commented on this achievement, saying, ‘In this study, we examined various SVM variants and modeled each of them on a dataset, both using feature extraction and without it, and proved that the SVM with the rbf variant is the best among all of them. I am glad that the research was successful and it turned out to achieve results and even show other experts how Artificial Intelligence can be used.’ The findings were presented at the National Conference on Information and Communication Technology in India, and Subhash is currently preparing a scientific article for an international journal. He views this as a crucial step towards broader AI application in medicine and other social domains.
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Subhash’s accomplishments have earned him recognition in the data engineering community, including a fellowship with Hackathon Raptors, an association of engineers from leading technology companies. His expertise has also led him to a Senior Data Engineer role at KPMG, one of the world’s largest financial firms, where he translates customer requirements into development strategies and designs data flow architectures for reliable analytical results. His successful completion of Microsoft Azure artificial intelligence exams further underscores his profound impact on AI development, as he continues to explore new avenues for AI and machine learning tools.
