I am an AI/ML researcher and research software engineer working at the intersection of computer vision, healthcare AI, and biomedical computing, with a supporting focus on robotics, embedded intelligence, and space science. My work runs the full research lifecycle — dataset curation, experiment design, manuscript preparation, and the software infrastructure that keeps it reproducible.
I hold a published patent on an AI-integrated blood group testing device, have released a curated biomedical imaging dataset and a research productivity framework as open-source software, and am currently preparing a confidence-aware classification pipeline for Scopus Q1 submission. Alongside this, I founded Sayon Institute of Innovation (SII), building learning and research-management infrastructure for student researchers.
Currently: B.Tech Computer Science, Chandigarh University.
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Core Domains
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Supporting Interests
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I build AI systems where the reported confidence means something — models that know when to defer to a human instead of forcing a guess. My current work applies this directly to low-cost diagnostic screening, where a wrong automated call carries real clinical cost. The same principle — instrumented, reproducible, honestly-calibrated research — carries into everything from a biometric authentication pipeline to a lunar subsurface mapping model. 🚀
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In preparation — Scopus Q1 Frozen CNN backbone → calibrated tabular classifiers → asymmetric clinical review policy. Macro-F1 0.7411 at threshold 0.340, reliability asymmetry replicated across 5 seeds. Every reported figure is traceable to a source notebook cell. |
MobileNetV2 feature extraction + AutoGluon tabular prediction for mobile-optimized ABO/Rh(D) screening. Concept covered by a published patent for a biodegradable dual-mode testing device. |
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Zenodo · 10.5281/zenodo.21384197 Quality-controlled, binary-labeled image dataset published to support reproducible research in low-cost hematology imaging. |
Open-source Python framework for research automation, experiment tracking, and reproducibility — extending the SII research ecosystem into public tooling. |
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Gait Energy Image (GEI) methodology for person authentication from walking video, deployed as a full Flask application with public inference. |
Next.js / TypeScript / Firebase platform with role-based access control, an authenticated committee portal, and automated dual-logo certificate generation. |
| Title | Venue | Domain | Link |
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| Automated Blood Group Detection Using Computer Vision and Transfer Learning on Mobile-Optimized Deep Neural Networks | Zenodo Research Repository | AI · ML · CV · Healthcare | 10.5281/zenodo.20224963 |
| Blood Agglutination Curated Dataset (V1) [Data set] | Zenodo | Biomedical Dataset · CV | 10.5281/zenodo.21384197 |
| SayonLab: A Scientific Research Productivity Framework v0.1.0 [Software] | GitHub | Open-Source Scientific Computing | SayonLab |
Patent — Dual-Mode Blood Group Testing Device Featuring Biodegradable Design and AI Analytics · App. No. 202511125188 · Filed 11 Dec 2025 · Published
- 🏆 First Runner-Up — CSIR-IITR Innovation Award
- 🥇 First Prize — Aarvi & Airo Robotics Innovation
- 🥉 Third Prize — Inter-School Website Development Competition
