Developed an interpolation-based ray tracing method to optimize channel modeling in large-scale wireless simulations, reducing computational costs.

Implemented a reflection model for accurate LOS MIMO simulation, improving spherical wavefront modeling for near-field channels. 

Validated and optimized the approach using Sionna, achieving accurate channel estimates with reduced resource usage in real-world scenarios.

Improved a SSR algorithm, incorporating AMP into the EM-based SBL for the MMV problem.

Integrated this algorithm into a larger coding scheme (FASURA) for massive random access.

Implemented SBL, MSBL, AMP-MSBL & GGAMP-MSBL from scratch.

Built a neural network with Adam optimizer and early stopping, achieving 99% accuracy.

Enhanced performance through feature extraction with Librosa and hyperparameter tuning.

Developed a custom KNN distance metric, improving voter classification accuracy with incomplete data.

Enhanced model performance through feature selection, achieving over 84% test accuracy.

Analyzed a continuous-time MDP, integrating controlled actions and optimizing discrete-time observations.

Extended the framework to a multi-agent system, exploring strategic considerations in a two-player context.

Simulated a Viterbi algorithm sequence estimator, assuming knowledge of channel parameters.

Evaluated the SER of transmitted symbols for a wide range of SNR values and decoding delays.

Simulated a two-queue system with customer arrivals following a Poisson process.

Evaluated the error (< 3%) and generated time plots of the number of customers in the queues.

Evaluated the performance of naive Bayes, logistic regression, SVM & random forest classifiers.

Performed text preprocessing & word embedding (TF-IDF) on the training dataset.