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Besides building analytical solutions for a large-scale organization, Sree Hari Subhash, an international IT expert, has researched the application of artificial intelligence in pre diagnosis of neurodegenerative diseases.
Data Analytics, Machine Learning, and Big Data become parts of digital transformation; they are not just add-on tools. Microsoft has announced plans to train one million people in Artificial Intelligence and Cybersecurity skills by 2026. Experts predict a skyrocketing need for data analytics and AI acumen by mid-decade, not only among tech pros but also in finance, health care, and many more industries.
To skillfully transition with these changes, honing data analytics and Machine Learning expertise becomes imperative. Senior data engineer at KPMG, Sree Hari Subhash, specializes in both implementing AI and creating neural network solutions for diagnosing Alzheimer's disease. His work exemplifies ways that data analytics can fuel professional growth globally, which is what this article is about.
One of the expert's major investments in Artificial Intelligence was his research on using Machine Learning to diagnose Alzheimer's disease. Subhash's research has significantly impacted the field of digital diagnostics of neurodegenerative disorders, demonstrating the potential of AI-powered data analysis as a powerful tool for early detection of these conditions.
The work used the DARWIN dataset, which contains information about 174 participants, including more than 450 characteristics obtained when performing tasks on a graphics tablet. Subhash's main objective was to determine whether it is possible to distinguish a healthy person from an Alzheimer's patient by writing features.
“This research focused on how to determine the presence of Alzheimer's disease by a person's handwriting. We take into account such characteristics as the time when the hand is in the air, the appearance of writing, the presence of shaking, cross lines, average accuracy, and other related factors,” Subhash wrote in his paper.
The author applied the support vector machine (SVM) method and used the dimensionality reduction technique. This is a principal component analysis (PCA) to improve the model's accuracy and avoid overfitting. Subhash tested various machine learning algorithms and showed that SVM with radial basis function provides the best balance between accuracy and specificity. This is especially important in medical tasks because it reduces the risk of false negative diagnoses. The study proved that the model is effective, which makes it valuable for clinical use.
In addition to implementing artificial intelligence, Sree Hari Subhash is a senior data engineer with KPMG. This company is one of the four largest audit and consulting companies in the world, often referred to as the “Big Four”. Subhash works at KPMG Dallas' Data and AI division, which is responsible for creating solutions in data engineering, analytics, and artificial intelligence.
He is responsible for designing data flow architecture, managing teams in a distributed manner, executing agile processes, and driving various initiatives for digitalization. Ultimately, his role is to transform disparate data into strategically significant information for the customer and help them be better positioned for success.
Aside from the technical side of the solutions, the professional facilitates the connection of development and business. They work with the customer to understand their need or challenge and then formulate the need for actionable objectives for the development team.
In this capacity, Subhash customizes data processing solutions to meet the specific needs of the customer's business. Also, he works with both offshore and onshore teams so that they can implement viable action plans.
Subhash also manages dispersed expert teams across different time zones, which adds more complexity, as he assigns some team members specific duties based on their expertise. All of this is balanced with regard to the agile processes. The team can meet every day and plan for a sprint on a weekly basis. The use of retro reviews improves accountability, visibility, and progress.
“It is crucial for me that every team member feels accountable and perceives the impact of their contributions. My approach involves not merely delegating tasks but also imbuing trust, which fosters growth and engagement,” Subhash comments.
Earlier in his career, during his work for American Express via Tata Consultancy Services (TCS), the engineer was engaged in developing microservices and APIs. American Express is one of the world's largest players in the field of financial technology. Working for such a client level required high reliability, responsibility, and the ability to solve problems on a global scale. This included the Colleague 360 project, where he integrated with enterprise platforms like Cisco Webex and Slack and operated where user experience met infrastructure to create systems that enhanced visibility and connectivity in a corporate environment.
“At TCS, we implemented real-time data streaming using Kafka, sending the data to Cornerstone's DataLake for analysis. At the same time, I also upgraded the accounting API by transferring logging to a new system that provided full tracing and alerting. This was a valuable experience for me both in terms of my engineering skills and in terms of interacting with a large financial technology company,” Subhash commented.
Most recently, while at Yum Brands Inc., in corporate human resources data and reporting, they used Oracle BI Publisher and Oracle Business Intelligence tools (OTBI). He also contributed to implementing an Artificial Intelligence digital assistant and dedicated systems to enhance the company's unique requirements. This professional helped automate employee interactions with the system using AI systems.
“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. Additionally, we automated reporting using IBM DataStage, significantly simplifying our daily operations.”
Some of Subhash's most substantial impacts on the digital world were implementing scalable models using both Microsoft Fabric and Databricks. Furthermore, he has applied data analytics techniques in corporate environments.
The fundamental principle of Subhash's professional approach is pairing technical capabilities with a deep understanding of business functions. In his capacity as a data engineer, Subhash has delved into a diverse array of technologies and platforms.
His repertoire encompasses the likes of Azure AI Studio, PySpark, SQL, Tableau, and Oracle BI, among others. A particular focus of his work lies in the development of solutions that leverage the power of the Microsoft Fabric framework.
As a result, Subhash was chosen to serve as a juror on the Global Awards for Artificial Intelligence in 2025, an honor that reflects not only his own expertise but the professional community's confidence in his ability. Further, he is a member of Raptors Dev and holds certifications as a Microsoft Fabric Analytics and Azure AI engineer.
Currently, Sree Hari Subhash works as a senior data engineer at KPMG, where he is involved in designing data flow architectures and implementing analytic solutions for KPMG’s corporate clients. He is also involved in some research.
“I intend to actively continue my research in artificial intelligence and machine learning, with the focus of building expertise in these areas and developing some applications,” he commented.
Subhash is thinking about developing open-source projects in ethical analytics and artificial intelligence. He hopes to work more in international professional activities, ultimately creating solutions that have both enterprise and social value.
