Final-year CS student at LPU. AI Evaluation Specialist at Scaler AI Labs. Building systems that think, interfaces that resonate, and pipelines that scale. Harmonizing technical complexity with intuitive design.
Developing SFT "Golden Responses" for LLM reasoning benchmarks and architecting automated annotation pipelines that ensure frontier-model alignment at scale.
CurrentBridging technical product capabilities with market-driven user needs — translating complex AI features into compelling value propositions.
CurrentAligning frontier LLMs via RLHF and performing adversarial red-teaming for algorithmic reasoning — shaping how the next generation of AI systems behave.
CompletedPublished "Novel Users in Specific Domains" — an exploration of specialized user behaviour patterns in OS environments, bridging HCI theory with practical systems design.
PublishedPredictive air-quality model trained on 420,000+ geospatial records with full explainability via SHAP values. Production API with real-time inference.
Adaptive bitrate streaming service supporting high-density video delivery and real-time transcoding workflows. Handles concurrent session scaling gracefully.
Anomaly detection prototype that identifies browsing-based threats and zero-day attack patterns using behavioural signals rather than signature matching.
I'm a final-year Computer Science student at Lovely Professional University, currently working as an AI Evaluation Specialist at Scaler AI Labs — where I shape how frontier language models reason, align, and behave.
My work sits at the intersection of machine learning, systems engineering, and product intuition. Whether it's crafting SFT golden responses, building XAI pipelines, or architecting adaptive media systems — I'm drawn to problems where elegance and rigor have to coexist.
I believe the best engineers are also designers — people who obsess over how something feels as much as how it works.