Machine Learning Engineer and Research Aspirant interested in developing intelligent systems for scientific and real-world applications.
- Reinforcement Learning
- Multi-Agent Reinforcement Learning (MARL)
- Machine Unlearning
- Computer Vision
- Deep Learning
- Semantic Segmentation
- Scientific Machine Learning
- Remote Sensing and Image Analysis
Working on reinforcement learning systems focused on selective knowledge removal, adaptive policy behavior, and information forgetting mechanisms in multi-agent environments.
Developing deep learning pipelines for multiclass terrain segmentation and classification using Mars orbital imagery with architectures such as U-Net and CBAM-U-Net.
- Bayesian Neural Networks for uncertainty estimation
- Few-shot learning for low-data image classification
- Texture-based image analysis and segmentation
- AI systems for agricultural disease surveillance
- Lightweight neural networks for edge deployment
Languages:
Python, C++, SQL
Frameworks and Libraries:
PyTorch, TensorFlow, Scikit-learn, OpenCV
Domains:
Computer Vision
Deep Learning
Reinforcement Learning
Multi-Agent Systems
Machine Unlearning
Scientific AI
Remote Sensing
- Email: [email protected]
- LinkedIn: linkedin.com/in/anoushkaacc
The most personal is most creative.
