Senior Full-Stack Software Engineer with 3 + years of experience designing and shipping AI-integrated, scalable web & cloud applications. Former Samsung R&D engineer with a proven track record of building production-grade systems that serve real users at scale.
🔬 IEEE-published researcher in deep learning — combining academic rigor with hands-on engineering to create intelligent software solutions.
| 🏢 Ex-Samsung R&D — Production-grade engineering | 📄 IEEE Published — Deep Learning for Computer Vision |
| 🏆 LeetCode Top 10 % — 700 + problems solved | 🎯 Top 10 Finalist — OctaHacks 3.0 National Hackathon |
| 🎓 B.Tech — VIT Vellore (2019 – 2023) | 🌏 Languages — English · Hindi · Odia · Japanese |
|
🤖 AI-Powered Agents Intelligent automation workflows with LLMs, LangChain & RAG pipelines |
☁️ Cloud-Native Architectures Scalable microservices on AWS & Azure |
|
🧠 Full-Stack AI Products End-to-end web apps integrating real-time ML inference |
📊 DSA Mastery Continuously sharpening problem-solving on LeetCode (Top 10 %) |
🗣️ Languages
🎨 Frontend
⚙️ Backend & APIs
🗄️ Databases & Message Brokers
☁️ Cloud & DevOps
🤖 AI / ML
📊 Data Science & Visualization
🧪 Testing
🎯 Design & Tools
|
Consistent problem-solver with strong DSA foundations across 700 + problems. |
"Identification of blurred objects in real-time video using deep learning neural networks" |
|
OctaHacks 3.0 Hackathon — Built HEALTHINIC, a smart healthcare assistant with symptom-based disease prediction & real-time doctor chat. |
Generative AI · ML Masters · LangChain · FastAPI · IoT (UC Irvine) · Python for DS (IBM) · React · Node.js & more |
🎓 Click to expand — 13 + Professional Certifications
| # | Certificate | Issuer | Link |
|---|---|---|---|
| 1 | ❄️ SnowPro Associate: Platform | Snowflake | Credential ↗ |
| 2 | 🤖 Generative AI Fundamentals | Databricks Academy | Credential ↗ |
| 3 | 🦜 LangChain — LLM Powered Apps | Udemy | Credential ↗ |
| 4 | ⚡ FastAPI — Beginner + Advanced | Udemy | Credential ↗ |
| 5 | 🧠 Machine Learning Masters | iNeuron.ai | Credential ↗ |
| 6 | 📡 IoT Specialization | UC Irvine — Coursera | Credential ↗ |
| 7 | 🐍 Python for Data Science | IBM | Credential ↗ |
| 8 | ⚛️ React Front To Back | Udemy | Credential ↗ |
| 9 | 🟢 Complete Node.js Developer | Udemy | Credential ↗ |
| 10 | 📊 Excel: Business Intelligence | Codebasics | Credential ↗ |
| 11 | 🐧 Command Line in Linux | Coursera | Credential ↗ |
| 12 | 📐 Business Mathematics | VIT (VITOL) | Credential ↗ |
| 13 | 💻 Intro to Computer Application | VIT (VITOL) | Credential ↗ |
|
Published in IEEE • December 2022 Our blur detection method utilizes an innovative approach, dividing the algorithm into two distinct stages. In the initial stage, we leverage the YOLO object detection algorithm to identify the largest object within the image. Simultaneously, we train a Convolutional Neural Network (CNN) model using an external dataset tailored specifically for blur detection. By applying this approach to real-time video streams, our trained CNN model effectively detects whether individual frames exhibit blurriness or maintain clarity. |
Made with ❤️ by Ayush Senapati — ⭐ Star my repos if you find them useful!