Bachelor of Science in Electrical Engineering

Learned how to work in virtual teams and virtual collaboration. Gained skills in virtual communication, and how to run effective virtual meetings. Learned how to speak and present in a virtual context.

Tackled real-world cases such as speech recognition, music synthesis, chatbots, machine translation, natural language processing, and more. Built network architectures such as Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers, and learned how to make them better with strategies such as Dropout, BatchNorm, and Xavier/He initialization.

Gained applied experience in major areas of Machine Learning including Prediction, Classification, Clustering, and Information Retrieval. Learned to analyze large and complex datasets, create systems that adapt and improve over time, and build intelligent applications that can make predictions from data.

Accurate placement of the needle is critical in interventions like biopsies and regional anesthesia, where incorrect needle insertion can lead to procedure failure and complications. Ultrasound guidance is widely used to improve needle placement accuracy. However, at steep and deep insertions, the visibility of the needle is lost. Computational methods for automatic needle tip localization could improve the clinical success rate in these scenarios. https://doi.org/10.1007/s11548-021-02361-w