ML/AI HT-DEMUCS for Interference Mitigation Master’s Thesis in Machine Learning: On the Generalization of Deep Neural Network-Based Interference Rejection to Unseen Signal Constellations WWII Fact-Checking RAG System Development of a Retrieval-Augmented Generation (RAG) system to verify the veracity of World War II-related statements using a specific corpus and large language models. Visual Object Tracking Using Particle Filter Optimizing a particle filter for visual object tracking using advanced color, texture, and shape descriptors to improve accuracy in complex scenarios. Sentiment Analysis Using RNNs with and without Attention Comparing two RNN architectures for sentiment analysis on financial news data. Analysis of Research Projects with NLP techniques Developing a robust pipeline for data preprocessing and text vectorization for classification tasks. Deep Autoencoder for Denoising Noisy Images Development of a deep autoencoder model to reconstruct clean images from noisy inputs, improving image quality in datasets like MNIST and FMNIST. Calibration of Convolutional Neural Networks (CNNs) using Temperature Scaling Exploring the calibration of CNNs through temperature scaling to improve model reliability in binary classification tasks. RF HT-DEMUCS for Interference Mitigation Master’s Thesis in Machine Learning: On the Generalization of Deep Neural Network-Based Interference Rejection to Unseen Signal Constellations Dielectric Lens Design for Collimation of RF Horn Antennas Bachelor's Thesis in Telecommunications Engineering A Data-Driven Framework for Wireless Communications Master’s Thesis in Telecommunications Engineering
