MoodOS
Emotion-adaptive AI desktop interface
Reads real-time facial landmarks and reshapes UI elements to match the user's emotional state, with HCI-grounded adaptive workflows.
ReactTypeScriptThree.jsMediaPipeFramer Motion
Electronics engineering undergrad at MITS Gwalior (2023-2027) building interfaces that listen, adapt and explain themselves. I work where machine learning meets human experience: emotion-aware UIs, mental-health NLP, and music-driven learning.
Research interests
Reads real-time facial landmarks and reshapes UI elements to match the user's emotional state, with HCI-grounded adaptive workflows.
Voice conversation, journaling, mood tracking and therapeutic interventions, designed trauma-informed with privacy and emotional safety first.
Allocates patients by hospital proximity, severity and live bed availability, with EHR, ambulance routing and push alerts.
Tracks how brands appear across ChatGPT, Claude, Gemini and Perplexity with citation audits, visibility scoring and benchmarking.
Safer route planning, community hazard reports, accessibility-aware navigation and an integrated SOS flow.
Gamified, contextual vocabulary learning with adaptive pathways shaped by user testing.
Medication sentiment classification and ADR detection: label granularity, class imbalance, metrics, safety-recall trade-offs.
Evaluation of explainable models on a novel dataset.
Music-driven language learning grounded in HCI methodology.
Guest speaker at Hatch on UX/UI design and user-centered principles.
Two-time LinkedIn Top Voice for design and technology contributions.
Finalist in six hackathons, including multiple national-level events.