Skill Set

My expertise lies in monitoring critical infrastructure through the analysis of wave data. By combining advanced techniques in machine learning, statistical modeling, data science, and wave propagation, I develop innovative solutions to complex challenges. Below are the key areas of my expertise.

Machine Learning — I have a strong foundation in deep learning, with extensive experience in frameworks like PyTorch and TensorFlow, and a solid understanding of modern model architectures, such as CNNs, VAEs, LSTMs, WaveNet, and Diffusion models, and their applications. I am also proficient in classical machine learning approaches, including decision tree models, gradient boosting techniques, and support vector machines (SVMs).

Statistical Modeling — I am experienced in statistical modeling techniques, including regression analysis, Bayesian inference, and generalized linear models, to derive make inferences from experimentally collected data.

Data Science and Analytics — I derived insights from experimental data using data science techniques and have automated data pipelines, integrated data across databases using SQL, and performed ETL operations. Additionally, I built real-time dashboards to provide timely insights and enable data-driven adjustments during experiments.