I am an AI Engineer and Systems Researcher, deeply focused on designing next-generation model architectures, distributed infrastructure, and state-aware intelligent systems. As a Computer Science undergraduate at LPU, my research centers on State Space Models (QU-SSM), constant O(1) inference memory manifolds, and high-throughput data backends.

My industry experience is grounded in delivering production-grade AI solutions — from architecting resilient Retrieval-Augmented Generation (RAG) systems and edge-to-server integrations at Ati Motors to streaming lakehouse pipelines with Apache Spark, Python, and SQL. I approach software and AI with a systems mindset, eliminating computational bottlenecks across memory, compute, and latency.

Key milestones in my work include QU-SSM, an isometric state-space architecture that overcomes the KV-cache scaling barrier with constant O(1) inference memory, alongside SAGUS, an adaptive graph-driven AI backend. In addition to applied research, I hold three Oracle Cloud certifications across Data Platform, Cloud, and AI Foundations.