Devansh Gupta
Software Engineer · Full Stack Developer
Engineering scalable software, intelligent systems, and real-world products — from architecture to deployment.
React · Next.js · Node.js · TypeScript · Python · AWS · Docker · Kubernetes · AI/ML
Who I Am
Devansh Gupta
Software Engineer · Full Stack Developer
TIET · Kurukshetra, India
I'm a Software Engineer and Full Stack Developer building scalable systems, intelligent applications, and production-ready software. My work spans real-time AI for industrial automation, medical imaging pipelines for cancer detection, and full-stack platforms serving live users across markets.
I take end-to-end ownership — from system architecture and API design through to production deployment, monitoring, and iteration. My stack centers on React, Next.js, Node.js, TypeScript, Python, and AWS — with a strong focus on performance, maintainability, and engineering fundamentals.
I actively leverage AI-assisted development workflows to move faster on complex problems while maintaining high engineering standards.
What I Build
What I Care About
Currently Exploring
What I Work With
What I've Built
End-to-end systems — from architecture to production deployment.
Engineering Experience
Building scalable products, intelligent systems, and production-ready software.
Applied Research & Technical Contributions
Peer-reviewed research in AI, Computer Vision, Medical Imaging, and Intelligent Systems.
10+
Peer-Reviewed Publications
2–4
Journal Impact Factor
1
Published Patent
While my primary focus is software engineering and scalable systems, I actively contribute to applied research in AI, Computer Vision, and Medical Imaging — translating research ideas into practical engineering systems and production-ready implementations.
Selected Publications
Deep Learning-Based Toolkit Inspection: Object Detection & Segmentation in Assembly Lines
Computers, Materials & Continua
Production AI system — 96.9% segmentation accuracy in live industrial deployment.
Emulating Hyperspectral and Narrow-Band Imaging for Deep Learning-Driven GI Disorder Detection
Bioengineering
Built ML pipeline for non-invasive cancer screening — engineered end-to-end from data to inference.
Enhancing Early GI Disease Detection with Spectral Visualization and Deep Learning
Bioengineering
Designed spectral feature extraction pipeline enabling early-stage disease classification.
Novel Approach to Risk Stratification: Integrating Waist-Hip Ratio for Predicting Advanced Colorectal Neoplasia
World Journal of Clinical Oncology
Applied ML-driven risk stratification for clinical decision support systems.
Patent
Real-Time Adaptive Trust Routing for Underwater Software-Defined Networks
Engineered an SDN-based adaptive routing mechanism for secure, energy-efficient underwater acoustic sensor networks — using trust-aware routing logic to dynamically handle changing network topologies without manual reconfiguration.
“I enjoy owning systems end-to-end — from designing scalable architectures and backend workflows to deploying production-ready applications. I believe impactful software comes from balancing engineering fundamentals, business outcomes, and rapid iteration through AI-assisted workflows.”
Let's Build Something Meaningful
Open to software engineering roles, full-stack opportunities, applied AI projects, and technical collaborations.
Engineer specializing in full-stack systems, production AI, and cloud-native architecture. Currently open to full-time software engineering roles and technical collaborations. Response within 24–48 hours.