About

Ekaterina Sirazitdinova, also known as Katja, is a highly skilled research engineer specializing in computer vision and deep learning. She holds a PhD in Medical Informatics from RWTH Aachen University and has over 4 years of relevant experience in the field. During her PhD studies, Ekaterina focused on image-based 3D reconstruction and tracking. She then went on to work on deep learning for medical image analysis, where she utilized her skills to develop algorithms for nuclei segmentation, lung segmentation, detection of abnormalities in orthopedic X-ray images, and classification of X-ray images according to body regions. Currently, Ekaterina works as a Data Scientist for Computer Vision, Video Analytics, and Deep Learning at NVIDIA. Her role involves helping customers solve their computer vision and video analytics problems, specializing in machine learning inference optimization, and deployment of AI models on data center GPUs as well as in embedded/edge devices. Prior to joining NVIDIA, Ekaterina worked as a Research Engineer in Machine Learning and Data Science at Konica Minolta Laboratory Europe. Here, she conceptualized products in the area of computational precision medicine and implemented interactive prototypes. She also developed an interactive prototype for segmentation of cancerous nodules in CT scans with a real deep learning model in the backbone. Ekaterina's past experience also includes working as a Research Intern in Computer Vision at the National Institute of Informatics, where she developed and implemented an algorithm for probabilistic 3D fusion of depth maps acquired with a Microsoft Kinect sensor. Ekaterina's technical skills include Computer Vision, Deep Learning, Research Scientist, Data Scientist, AI, ML, Javascript, Python, Pytorch, Image Processing, NodeJS, Flask, OpenCV, among others. Her passion for research and development in the field of computer vision and deep learning is evident from her work and her contributions to the community.