AI Researcher, Machine Learning, Deep Learning, Deep fake, Medical Imaging

1. Conducting research in the field of deep learning, specifically focusing on wound image segmentation and classification.
2. Implementing machine learning and deep learning algorithms to process and analyze medical imaging data, contributing to advancements in automated wound diagnostic systems.
3. Developing deep learning models such as convolutional neural networks (CNN) and recurrent neural networks (RNN) to improve the accuracy of segmentation and classification tasks in medical images.
4. Utilizing machine learning tools and frameworks, including Python, TensorFlow, NumPy, Pandas, and Theano to build and optimize models.
5. Running experiments on real-world data, integrating algorithms as software components in a complex development environment.
6. Collaborating with a multidisciplinary team of researchers to address challenges in medical imaging, particularly for chronic diabetic wound segmentation.