Alexandra S.

I am a ML engineer with a Master’s degree in Applied Mathematics, a strong technical background and extensive experience in deep learning, computer vision, and medical imaging. I have experience developing ML pipelines in Python using PyTorch and TensorFlow, previously working with high-dimensional image data and protein sequences. As part of my Master’s thesis, I developed a deep learning pipeline for breast cancer diagnostics using histopathology images, training models to predict molecular disease status directly from image data. I have also contributed to research on brain tumour segmentation using 3D MRI scans through an external collaborative project, which focused on fine-tuning segmentation models on low-quality data. My team’s work on 3D brain tumour segmentation was presented at MICCAI 2023 and published in the Lecture Notes in Computer Science series. I also have exposure to NLP and working with transformers and large language models. My work in NLP includes developing a pipeline in PyTorch for training and fine-tuning large protein language models from HuggingFace. I am passionate about applying machine learning to real-world problems and delivering clean, well-documented, reliable, and impactful solutions.