M.Tech (Data Science) | AI Researcher | Deep Learning & Spatio-Temporal Modeling
Working at the intersection of satellite data, medical imaging, and real-world AI systems.
I am an AI and Data Science researcher with hands-on experience in satellite imagery analysis, geospatial data processing, and deep learning for spatio-temporal and medical imaging problems. I enjoy building reproducible pipelines — from data preprocessing to model evaluation — and translating complex model behavior into clear insights.
- 🎓 M.Tech in Data Science — Gold Medalist, Pandit Deendayal Energy University
- 🔬 Junior Research Fellow — Sustainability Lab, IIT Gandhinagar
- 🛰️ Former Research Intern — Space Applications Centre (ISRO)
- Deep learning models for numerical weather models (WRF)
- Spatio-temporal representation learning on geophysical data
- Satellite imagery analysis for extreme weather events
Languages & Data: Python, SQL, NumPy, Pandas, xarray
ML / DL: PyTorch, PyTorch Lightning, TensorFlow/Keras, Scikit-learn
Computer Vision: CNNs (ResNet, VGG, DenseNet), YOLO, ConvLSTM
NLP: BERT-based models, Hugging Face Transformers, NLTK
Scientific & Geospatial: NetCDF, HDF5, GeoPandas, WRF
Deployment & Tools: Flask, FastAPI, Git, Docker, GCP
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Thoracic Disease Detection (Pediatric Chest X-rays)
Multi-label detection using YOLO on DICOM imagery with benchmarking across CNN architectures. -
Cyclone Intensity Estimation & Forecasting
CNN and ConvLSTM models trained on multi-year satellite data with robust preprocessing pipelines. -
Spatio-Temporal Modeling of WRF Outputs
Deep learning–based emulation and evaluation using spatial and temporal diagnostics.
🔧 Repositories are currently being cleaned, documented, and prepared for public release.
I am open to:
- Research collaborations
- AI/ML engineering roles
- Open-source and applied ML projects
📫 Email: deenalad06@gmail.com
🔗 LinkedIn: https://www.linkedin.com/in/deena-lad
Interested in reproducible research, ML for Earth & Health, or collaboration? Let’s talk.