Jalpa Parmar is a Machine Learning Engineer at trinamiX GmbH since January 2022. Previously, Jalpa completed a Master thesis at the University of Erlangen-Nuremberg, focusing on "Weakly Supervised Learning for Multimodal Breast Lesion Classification in Ultrasound and Mammogram Images," collaborating with University Hospital Erlangen. This project involved developing deep learning models using Python, Tensorflow, and Keras. Jalpa has also worked on a research project at the Machine Learning and Data Analytics Lab, where application software for Microsoft Hololens was developed to assist blind individuals with touchscreens, utilizing C# and Javascript. Additionally, Jalpa served as a Research Assistant at Friedrich-Alexander-University of Erlangen-Nürnberg, involved in automatic segmentation of anatomical regions, and worked as a Quality Control Engineer at Sahajanand Laser Technology Ltd, inspecting medical devices. Educational qualifications include a Master of Science in Biomedical/Medical Engineering from FAU Erlangen-Nürnberg and a Bachelor of Engineering in Biomedical/Medical Engineering from L.D. College of Engineering.
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