I am a senior Data Scientist with an academic background and industry experience. Armed with a PhD in Computer Science, my expertise lies in harnessing the hidden and latent variables concealed within intricate datasets by employing cutting-edge deep learning models. My work centers around unearthing profound insights from data, with a specific focus on pioneering research in domains such as graphs, trees, large language models, and the realm of Natural Language Processing (NLP). I had the privilege of being mentored by Dr. Ioannis Koutis, a prominent figure in the field. My doctoral research was rooted in graph theory, linear algebra, data and network embedding, machine learning, particularly clustering, and algorithm development in computational systems biology. This endeavor culminated in the creation of a groundbreaking pipeline capable of generating highly meaningful clusters, offering innovative solutions to intricate problems in data science. My academic background and teaching experience have not only enriched my knowledge but also equipped me with the ability to effectively convey complex concepts as an Adjunct Professor, where I teach Discrete Mathematics and Machine Learning. Additionally, I gained valuable experience as an intern at two well-known companies in the United States, CVS Health , and Seagate Technology. These internships provided me with a unique perspective on industry practices and enhanced my skills in real-world data science applications.

Prior to embarking on my doctoral journey, I honed my skills in statistical modeling, and pattern recognition in computational systems biology at the Biotechnology department of the University of Tehran. My master's degree in Computer Engineering, with a minor in Algorithms and Computation, provided a solid foundation. During my master's studies, my focus was primarily on machine learning, specializing in classification, algorithm design, and statistical analysis and modeling in computational systems biology within the research group of the Laboratory of Systems Biology and Bioinformatics (LBB) at the Institute of Biochemistry and Biophysics (IBB) at the University of Tehran. My work involved developing a new two-level nonlinear model for hierarchical classification of junk DNA using Machine Learning Algorithms, specifically self-organized maps. My diverse background in Computer Science, Probability and Statistics, Mathematics, and Biology allows me to effectively communicate with a wide audience and immediately contribute to any team or project.

In addition to my corporate role, I have a rich history of teaching and leadership. I have served as an instructor and lecturer at various universities in Tehran, Iran. Furthermore, I took on the role of Head of a research team at one of Iran's most esteemed institutions. During my tenure, I managed substantial classes, oversaw research projects, and supervised undergraduate final theses. My ability to efficiently manage and organize teams, combined with my strong supervisory skills, played a pivotal role in our numerous successes. Simultaneously, I worked in different institutes and universities, teaching several courses. Notably, I headed the research team for Data Structures and Algorithm Design at Parseh Institute, where I taught classes with 50+ students. This experience enhanced my leadership, supervisory, management, and problem-solving skills. Our efforts resulted in the publication of three books on Data Structures and Algorithm Design and the presentation of novel algorithms. As a result of my contributions to Parseh, we published three journal papers primarily related to binary trees. This experience has instilled in me the ability to swiftly learn and adapt to new disciplines, areas, or environments, ensuring that I can deliver tangible results quickly.