Data Scientist · AI Researcher · Machine Learning Engineer
I am a versatile Data Scientist and AI Researcher with proven expertise in bridging AI and data engineering techniques to build scalable, production-ready applications. I specialize in designing advanced machine learning algorithms, deploying robust backend microservices, and extracting actionable insights from complex datasets.
Currently, I am pursuing an M.Sc. in AI and Data Science at the Athens University of Economics and Business (AUEB), building on my B.Tech in CS (AI & ML) where I graduated from VIT Bhopal University.
| Project / Award | Description | Tech Stack |
|---|---|---|
| 🥇 1st Place - Text as Data in Economics | Won 1st place (€3,000 Award) in the AUEB university competition in partnership with Qualco Intelligent Finance. | Data Analytics, Economics |
| 🔥 Ignis-EO (Wildfire Intelligence) | ML-driven wildfire monitoring for Attica using Copernicus/NASA FIRMS data pipelines and ConvLSTM models. | Python, ConvLSTM, Docker |
| 🚶 WalkFree V2 | Production-grade urban infrastructure app with privacy-preserving OpenCV pipelines (face/plate blurring). | FastAPI, Flutter, GCP, OpenCV |
| 🧠 EmpowerMind | AI chatbot app screening mental health conditions for adolescents, utilizing optimal XGBoost architecture. | NLP, XGBoost, FastAPI |
| 🌳 Urban Green Space Enhancement | Deployed a computer vision model (>90% accuracy) to detect urban greenspaces via satellite imagery. | Computer Vision, PyTorch |
- EmpowerMind: Accessible Mental Health Support App (ICCAMS 2025): Evaluated multiple ML architectures, identifying XGBoost as the optimal classification model (76.35% accuracy) for context-aware health recommendations.
- Beyond Pixels: Tackling COVID-19 with CNN & Transfer Learning (ICAIHC 2023): Fine-tuned deep transfer learning frameworks for early detection from X-rays, identifying VGG16 as the optimal architecture (97.06% accuracy).
- CNN Detection of Malarial Parasites from Thin Blood Smears (ICCAMS 2023): Engineered a custom CNN architecture utilizing cross-validation across 18 combinations to achieve a peak classification accuracy of 96.3%.
🤖 AI / Machine Learning
🌊 Big Data & Streaming
⚙️ Backend & Application Development
☁️ Databases, Cloud & BI Tools
I believe that discipline, strategic problem-solving, and resilience under pressure matter just as much outside engineering as they do inside it.
- 🥋 Professional Karate Athlete & National Referee (Karate India Organization, 16+ years of experience)
I'm always interested in data science, machine learning, distributed systems, backend engineering, and interesting technical projects.
Thanks for stopping by! ⭐ Feel free to explore my repositories.