Master's Graduate Pramod Connects Years of Experience with New Knowledge in AI
For Pramod Nanjundaswamy, learning has never been limited to a classroom.
As Vice President and Head of Delivery at ALTEN, located in India, he leads large-scale engineering programs, oversees AI-driven transformation initiatives, and helps organizations navigate increasingly complex technological landscapes. Yet despite years of experience in engineering, delivery, and business leadership, he saw an opportunity to deepen his understanding of the technologies shaping the future.
That desire led him to the University of Arizona, where he recently earned a Master of Science in Information Science with a specialization in Machine Learning.
“Many people asked me, ‘Why now? Why at this stage?’” Pramod said. “The answer is simple: to truly understand, holistically, what I had been implementing and practicing for years.”
Throughout his career, Pramod witnessed the shift from a hardware-centric world to one increasingly driven by software, data, artificial intelligence, and automation. While his background in Instrumentation Technology provided a strong foundation in sensors and control systems, he wanted a deeper understanding of how data is generated, stored, processed, analyzed, and ultimately transformed into intelligent systems.
The University of Arizona's Information Science program provided that opportunity.
“The program offered the right balance of technical depth and practical application,” he said. “It enabled me to connect business strategy with data-driven decision-making.”
Returning to graduate school online while balancing executive leadership responsibilities and family life required commitment and careful planning. But for Pramod, the experience reinforced a belief he has carried throughout his career: learning should never stop.
“Earning this degree was deeply meaningful,” he said. “I've always believed that learning should continue regardless of career stage or age.”
One of the most impactful experiences came through his capstone project, where his team worked to improve a Data-efficient Image Transformer (DeiT) model. Using a multi-ensemble teacher approach, the team increased model accuracy by approximately 10 percent.
The project provided hands-on experience evaluating AI systems, identifying limitations, and applying different methodologies to improve outcomes. More importantly, it changed how he views technology's role within organizations.
“I moved from seeing technology as a support function to viewing it as a strategic enabler,” he said.
The program's influence extends directly into his professional work. Today, Pramod approaches decision-making with a stronger data-driven mindset and a deeper understanding of how AI can improve operational efficiency, reduce costs, and support strategic planning.
He has already applied those lessons in real-world scenarios, including work on perception systems for autonomous and intelligent machines. By combining his background in automotive and embedded systems with new expertise in AI and computer vision, he was able to help teams identify system-level challenges, explore synthetic data generation, and improve solution robustness before deployment.
As artificial intelligence continues to evolve, Pramod sees tremendous opportunity ahead. He believes organizations that successfully adopt AI will be those that invest not only in technology, but also in helping people adapt and grow alongside it.
“The biggest challenge is the mindset shift required within organizations,” he said. “At the end of the day, AI doesn't fail. Implementation does.”
Pramod’s reflections on the people who most supported his journey.
Looking back, he is most proud of making the decision to invest in himself and following through on it. Looking ahead, he hopes to leverage his education to lead larger transformation initiatives, advance AI adoption, and mentor others navigating a rapidly changing technology landscape.
For Pramod, graduation is not the conclusion of a journey, but another step forward.
“Earlier, I knew the dots,” he said. “Now, I understand how to connect the dots, and more importantly, how to extend them by adding new dots.”
As technology continues to evolve, that curiosity and commitment to lifelong learning remain at the center of what comes next.