Welcome to my GitHub! I'm a machine learning engineer, AI researcher, and remote sensing specialist.
- 🎓 Master’s degrees: Artificial Intelligence & Robotics (GPA: A+) and Remote Sensing (GPA: A)
- 🛰️ PhD Candidate at University of Bremen (AI for satellite data)
- 🤖 Actively working on applied machine learning and deep learning, with projects in medical AI, satellite data, and 3D reconstruction from point clouds
- Diabetes, Heart Disease, Parkinson's, and Breast Cancer Prediction using SVM, Logistic Regression, and XGBoost
- Face Mask Detection with CNN
- Multiple Disease Classifier (combined model for Diabetes, Heart, Parkinson's)
- Credit Card Fraud Detection and Loan Status Prediction
- Customer Segmentation using K-Means Clustering
- Movie Recommendation System, Spam Mail Detection, and Calories Burnt Estimation
- Breast Cancer and Plant Disease Detection with CNN
- Classification using Transfer Learning
- Handwritten Digit Classification
- DCGAN for handwritten digits generation
- Sentiment Analysis on IMDB Reviews using LSTM
- Streamlit ML App Deployment (local + public)
- Nuclear Medicine Intake Form with LLM integration
- UI in Flet (Python)
- TinyLlama via vLLM for text-to-JSON conversion
- Dockerized, schema validation, retry logic
- AWI-ICENet1: CNN-based radar waveform retracker for CryoSat-2 over Greenland/Antarctica
- 3D Surface Reconstruction from CryoSat Point Clouds using Point Convolutional Networks
Languages: Python, Bash, SQL (basic), Git (version control)
ML/DL Frameworks: Scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, Keras
Experienced with supervised/unsupervised learning, CNNs, RNNs, GANs, and transfer learning
Data Analysis & Visualization: NumPy, Pandas, Matplotlib, Seaborn
Remote Sensing & Geospatial Tools: GDAL, Rasterio, PyProj, QGIS, SNAP
Worked with Landsat, ASTER, PALSAR, CryoSat-2, and gravity datasets
- ✉️ Email: [email protected]
- 💼 Open to industry collaborations, research partnerships, and engineering roles.
Thank you for visiting!