Kamyar Zeinalipour

The University of Siena, founded in 1240 in Siena, Italy, is one of the world's oldest universities. It offers diverse undergraduate, postgraduate, and doctoral programs in fields like humanities, sciences, medicine, and engineering. Renowned for academic excellence and situated in a historic city, it attracts global students. The university is also notable for its research activities and international partnerships.

I began my Ph.D. in AI at the SAILab (Siena Artificial Intelligence Lab) at the University of Siena. Initially, my research concentrated on Physics-Informed Neural Networks. Subsequently, I focused on crossword generation for educational purposes. I developed a crossword generator based on NLP techniques and large language models (LLMs), supporting multiple languages including English, Italian, Arabic, and Turkish. Currently, my research is dedicated to knowledge graph generation from text. Throughout my Ph.D., I have collaborated with various companies such as Baker Hughes, Expert.ai, and Leonardo S.p.A.

The University of Siena, founded in 1240 in Siena, Italy, is one of the world's oldest universities. It offers diverse undergraduate, postgraduate, and doctoral programs in fields like humanities, sciences, medicine, and engineering. Renowned for academic excellence and situated in a historic city, it attracts global students. The university is also notable for its research activities and international partnerships.

During my Master’s degree in Applied Mathematics at the University of Siena, I had the opportunity to delve deeply into mathematical concepts as well as Artificial Intelligence (AI) and Machine Learning (ML) principles, which are closely aligned. I chose the Data Science track, where half of the courses focused on AI-related subjects such as Machine Learning, Big Data, and Artificial Intelligence. Additionally, the curriculum included advanced mathematics courses like Advanced Algebra, Advanced Calculus, Advanced Analysis, and Advanced Statistics, which significantly bolstered my foundational understanding of AI and ML.

For my thesis, I concentrated on Graph Neural Networks, and titled my research “ECG Signal Classification by Topological Feature Extraction and Utilizing Graph Isomorphism Networks.”

University Of Hormozgan is a public higher education institution located in Bandar Abbas, Iran. Established in 1991, the university offers a range of undergraduate, graduate, and doctoral programs across various fields of study. These fields often include engineering, humanities, basic sciences, marine sciences, and social sciences, among others. The university aims to provide quality education and foster research and development in the region. It typically collaborates with other academic institutions, industry, and government to contribute to the socio-economic development of Hormozgan Province and beyond.

During my bachelor’s degree in Applied Statistics, I had the valuable opportunity to delve deeply into the concepts of statistics and probability, which constitute the foundational elements of many AI and ML algorithms. My thesis focused on “The Effect of Economic Indicators on the First and Second Markets of the Tehran Stock Exchange.”

I specialized in creating crossword puzzles for educational use and developed a sophisticated crossword generator utilizing NLP techniques and large language models (LLMs). This generator supports multiple languages, including English, Italian, Arabic, and Turkish. Currently, my research is centered on generating knowledge graphs from text. During my Ph.D. journey, I have collaborated with notable companies such as Baker Hughes, Expert.ai, and Leonardo S.p.A.

As a Machine Learning course Teaching Assistant at the University of Siena, I had the opportunity to work closely with the course instructor to create a dynamic and engaging learning environment. My responsibilities included guiding students through course material and assisting them with assignments, projects, and lab exercises. I focused on fostering a collaborative learning atmosphere by encouraging student interaction and participation. In addition to providing one-on-one assistance and conducting small group sessions, I helped develop and refine educational materials to enhance the learning experience. Monitoring student progress and offering constructive feedback were key parts of my role, all while contributing to a positive and inclusive classroom atmosphere. This position allowed me to leverage my expertise in machine learning and strengthen my communication and interpersonal skills.

As a machine learning specialist, I applied machine learning and artificial intelligence to real-world scenarios, developing and deploying advanced algorithms to solve complex problems. I focused on creating physically-informed neural networks that adhered to underlying physical laws, bridging the gap between theoretical research and practical application. I collaborated with cross-functional teams to integrate these solutions into existing processes, provided insights for decision-making, and continuously improved model performance through rigorous testing and validation.

During my tenure, I collaborated with Baker Hughes to develop machine learning models aimed at predicting the pollution output generated by gas turbines. We created various shallow and deep learning models to achieve this objective.

As a Demographic and Statistical Analyst, I performed comprehensive demographic and statistical analyses using Excel, SPSS, and R. My role involved gathering and managing datasets from various sources, ensuring their accuracy and relevance, as well as cleaning and preprocessing data for in-depth analysis. Utilizing advanced statistical methods, I conducted descriptive, inferential, and regression analyses to identify trends, patterns, and insights. Additionally, I analyzed population demographics to provide insights into current trends and forecast future changes, ultimately supporting strategic decision-making and research initiatives.

As a dedicated statistician, I leveraged SPSS, Python, and R to conduct comprehensive statistical analyses for surveys, providing accurate and actionable insights. My expertise included designing, implementing, and interpreting complex survey data with a variety of techniques such as descriptive and inferential statistics, and predictive modeling. I ensured data integrity through meticulous cleaning and validation while creating clear visualizations and reports to communicate findings effectively. Committed to methodological rigor, I continuously enhanced my skills and stayed updated with the latest advancements in statistical methodologies and software.