Harsha Priya Ganapathy@Harsha123
1
Events attended
1
Submissions made
United States
3+ years of experience
About me
I am a Full-Stack Software Engineer and AI/ML Researcher with 6+ years of experience building scalable applications and intelligent systems across real-world domains. My core foundation is in full-stack development, where I have designed and delivered end-to-end applications using modern web technologies, APIs, and data-driven architectures. Alongside this, I have advanced my expertise through a Master’s degree in Computer Science (AI/ML) and research work focused on deep learning, IoT, and intelligent systems. I have built production-grade systems ranging from full-stack platforms to AI-powered applications, including government-scale GIS solutions and machine learning models for prediction and analytics. My work bridges the gap between software engineering and artificial intelligence — enabling the development of intelligent, scalable, and impactful systems. My key strengths include: • Full-Stack Engineering: React, Next.js, Python, FastAPI, Django, REST APIs, PostgreSQL • AI/ML: Deep Learning, NLP (Transformers), Computer Vision, Predictive Modeling • Data Engineering: SQL, ETL Pipelines, Data Modeling, Analytics • Geospatial Intelligence: ArcGIS, QGIS, PostGIS, Spatial Data Processing I have also contributed to research in AI/ML and IoT, with published work in deep learning and intelligent systems, including thesis-driven research and real-world applications such as trajectory prediction and AI-powered platforms. I am particularly interested in opportunities in: AI/ML Engineering | Full-Stack AI Systems | Data Engineering | Intelligent Platforms | GeoAI I am actively seeking roles where I can combine my software engineering foundation with AI/ML expertise to build scalable, intelligent systems that create real-world impact. Let’s connect if you are working on AI-driven products, data platforms, or next-generation intelligent systems.
🤓 Latest Submissions
EnvReplay: Catch the Deployment Failure CI Missed
A passing CI run does not always mean a service will work after deployment. CI may test an application at its root path while the deployed service runs behind a path prefix. Developers then face a 404 that their existing tests never exercised. EnvReplay gives developers a repeatable way to investigate that gap. Its single, concrete scenario is a health check: CI successfully serves /api/health, but deployment exposes the application under /service, where /service/api/health initially returns 404. A developer can run the replay, see the failing request and its environment context, inspect the path mismatch, and run the check again after the repair. IBM Bob is part of the repository investigation and development workflow. The project also provides executable replay checks and recorded evidence so judges can inspect what Bob contributed and independently verify the failure and result. The product experience presents the sequence clearly: CI passes, deployment fails, the cause becomes visible, and the repaired route passes the deployment check. EnvReplay is designed for developers, QA engineers, and teams troubleshooting differences between CI and deployed environments. Its value is a reproducible explanation and a checkable repair for a failure that a green CI badge missed.
27 Sep 2026
