Data Science Artificial Intelligence

I have been engaged in the development of artificial intelligence since 2014, beginning with the advent of word2vec. Over the years, my research has evolved alongside the field, encompassing work on autoencoders, pruning techniques, graph neural networks, and topic modeling, eventually leading to modern transformer-based architectures. More recently, my focus has shifted toward the application of large language models (LLMs) in education, where I am developing tools to enhance classroom engagement and learning outcomes using frontier AI capabilities. I am also exploring the integration of agentic systems to streamline operations within the Department of Scientific Computing, with the dual goals of reducing administrative workload and improving visibility to prospective students.