Tewele Weletnsea TAREKE. PhD.

Introduction

Specialized in Deep Learning, Medical Image Computing, and Computer Vision, with expertise in Generative AI and Large Language Models (LLMs). I develop multimodal fusion and radiomics solutions to enhance diagnostic accuracy within precision healthcare systems. Proficient in Python, C++, PyTorch, and TensorFlow, I design robust algorithms intended for integration into clinical and research workflows. I have worked with multimodal medical imaging data for breast cancer, including mammography, PET/CT, MRI sequences, ultrasound, patient demographics, and whole slide images (WSI), applying advanced imaging and learning techniques to extract meaningful insights. Moreover, I have applied LLMs to integrate clinical knowledge into AI pipelines, improving interpretability and decision support. My work has been presented at international venues, including medical image segmentation challenges at MICCAI 2025, IEEE EMBC, and related workshops. Currently, my focus is on developing machine and deep learning-driven solutions, combining medical imaging, computer vision, and natural language processing, and I am seeking opportunities to apply these advanced AI techniques to solve real-world problems.

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