Work
Morning OS
Productivity plugin with 200 active daily users — generates a personalized AI briefing each morning from your notes, tasks, and goals.
- 200 active daily users; iterated on features through a live Discord community
- Multi-provider LLM support with graceful degradation and full mobile compatibility
Deep Research Agent
Autonomous agent that searches, reads, cross-references, and synthesizes any topic end-to-end without human input — shipped in 5 days.
- 51 tools across 10 namespaces with subagent orchestration and an LLM-based eval harness
- Composable tool chains validated across 20+ tool call sequences; shipped from scratch in 5 days
Serverless Clinical AWQ Llama Engine (SCALE)
Medical AI assistant that answers clinical questions from 10,000 documents in under 0.5 seconds — deployed on serverless A10G GPUs.
- 0.529s TTFT and ~60 tok/s on A10G — fast enough for real clinical use
- 14% USMLE accuracy gain from AWQ fused kernels over NF4 baseline
Lunar GCN — ISRO / IEEE WHISPERS 2023
Graph Convolutional Network that classified lunar surface types from Chandrayaan hyperspectral data, beating CNN baselines by 13.5%.
- +13.5% accuracy over CNN baseline on Chandrayaan-1; 91% accuracy on Chandrayaan-2 data
- Published at IEEE WHISPERS 2023 and presented as a NASA NESF 2023 poster
CoCo: Neuro-Symbolic Desktop Companion
Desktop AI agent that watches your activity in real time and adapts to your emotional state — fast reactive layer and slow reasoning running in parallel.
- <16ms UI latency at 60Hz — imperceptibly fast reactive loop
- Runs fully on-device; zero data leaves the machine
Experience
Graduate Teaching Assistant
Boston UniversityCS 365: Foundations of Data Science
- Led technical labs on Python optimization and statistical modeling, mentoring 50+ students in data science fundamentals including Pandas, NumPy, and algorithmic best practices.
- Facilitated weekly code reviews to enforce production-standard coding styles and debugging techniques.
Machine Learning Engineer
Aaizel International TechInternship
- Architected a multimodal fusion pipeline (IFCNN) merging IR+RGB satellite imagery and constructed the domain's first remote sensing scene graph dataset.
- Fine-tuned a RelTR Transformer for geospatial relationship extraction and deployed the inference engine to Microsoft Azure, enabling real-time semantic visualization.
Computer Vision Engineer
Terrafic IncInternship
- Integrated the Segment Anything Model (SAM) and OpenCV to automate maritime feature extraction; delivered a production-ready MVP that secured initial client pilots.
- Implemented Super-Resolution (SR) algorithms (4x/6x) to enhance object detection performance on low-resolution defense mapping data.
Skills
Daily use
Projects & research
Background
Efficient Graph Formulation and Latent Space Integration for Lunar Hyperspectral Image Classification
2023IEEE WHISPERS 2023
GCN-based pipeline for Chandrayaan-1 hyperspectral data, achieving 90.1% accuracy on lunar surface classification via adaptive graph construction and spectral-spatial fusion.
Enhancing Hyperspectral Classification through GCNs with Adaptive Graph Construction
2023NASA NESF 2023 (Poster)
Adaptive graph construction method for Chandrayaan-2 IIRS hyperspectral data, reducing false positive rates by 13.5% through improved spectral neighbor modeling.
Education
M.S. in Artificial Intelligence
Boston University
GPA: 3.7 / 4.0
B.Tech. in Computer Science
IIIT Sri City
GPA: 3.5 / 4.0