Notes

The scent of chai lingered in the air as the train rattled toward my hometown, but I barely noticed. Across from me, a second-year IIT student sketched algorithms on a napkin, his eyes alight as he described a blockchain project that could secure medical records for rural clinics. “Imagine,” he said, “a world where AI doesn’t just predict diseases but democratizes healthcare.” In that moment, something clicked. I didn’t just want to code—I wanted to build AI systems that *mean* something. That conversation became my compass, steering me toward a singular mission: to harness AI as a force for equitable progress.

This mission took shape during my undergraduate studies in Computer Science, where I gravitated toward projects that fused technical rigor with human impact. Leading the development of an **AI-powered HR Solution**, I trained natural language processing (NLP) models to analyze employee sentiment across thousands of unstructured survey responses. The challenge? Ensuring the algorithm avoided bias against regional dialects in India. Spending nights tweaking transformer models and collaborating with HR teams taught me that AI’s true power lies not in replacing humans but in amplifying their insights. When the system reduced hiring bias by 22% for a client, I realized AI could be a bridge—not a barrier—to opportunity.

My internships deepened this resolve. At JKMK Solutions, I built a predictive maintenance model for manufacturing clients, using gradient-boosted trees to forecast equipment failures. But the “aha” moment came when the model identified a pattern linking machine downtime to worker safety incidents—a connection humans had overlooked. Suddenly, AI wasn’t just optimizing profits; it was protecting lives. Later, as a DevOps/MLOps intern, I deployed these models on AWS SageMaker, ensuring they scaled across factories in real time. Yet, I kept returning to that train ride: How could I design AI systems that are both *powerful* and *accessible*?

This question drives my pursuit of a Master’s at San Jose State University. SJSU’s focus on applied AI in Silicon Valley’s innovation ecosystem offers the perfect crucible to explore answers. Courses like *Deep Learning for Natural Language Processing* will sharpen my technical toolkit, while the *Silicon Valley Innovation & Entrepreneurship Center*’s industry partnerships could let me test ideas like my current passion project: an AI tool that decodes regional languages in India to improve accessibility for government welfare platforms. With 22 official languages and hundreds of dialects, millions are excluded from digital services due to language barriers. I want to change that.

Long-term, I aim to lead AI initiatives that tackle such systemic inequities. At SJSU, I’ll seek research opportunities in Professor XYZ’s lab on multilingual NLP or collaborate with peers at hackathons to prototype low-resource language models. Beyond academia, I’ll leverage the university’s ties to companies like Adobe and Cisco to explore how enterprise-scale AI can uplift underserved communities—whether through adaptive education platforms or healthcare diagnostics tailored for low-bandwidth rural areas.

To the admissions committee: My journey from that train conversation to leading AI projects has been guided by a belief that technology should *serve*, not stratify. At SJSU, I’ll refine this vision into expertise. I’ll bring not just my experience with PyTorch or Kubernetes, but my commitment to ensuring AI’s benefits reach those who need them most. Together, let’s build algorithms with empathy.