Dr. Shubham Saini | Faculty Mathematics

Dr. Shubham Saini 
Assistant Professor

He is a highly skilled and accomplished researcher with a strong background in mathematics, applied statistics, and reliability and life testing. He holds a PhD in Reliability and Life Testing and has published numerous research papers in prestigious SCI journals. His passion for learning and research has been recognized through awards such as the Inspire Scholarship and Senior Research Fellowship. With a solid foundation in mathematics and applied statistics, He has been able to apply his expertise to cutting-edge areas of research, particularly in the field of Artificial Intelligence (AI) and machine learning. He worked as a Research Associate at the prestigious Indian Institute of Technology (IIT) Roorkee, in the Department of Computer Science, where he contributed to the development of an AI-driven trading platform that involves applying machine learning algorithms and statistical techniques to analyze market trends, predict trading patterns, and optimize trading strategies. He has also worked as an assistant professor at the University of Delhi, teaching statistical courses to undergraduate students. Throughout his academic and professional career, He has demonstrated a keen ability to leverage his mathematical and statistical expertise to solve complex problems and make meaningful contributions to the field of AI and machine learning. He is driven by a curiosity to explore new frontiers in machine learning and continually seeks to expand his knowledge and skills in this exciting and rapidly evolving field. He is enthusiastic about collaborating with other researchers, exploring new methodologies, and contributing to the advancement of machine learning and AI. He is committed to pushing the boundaries of what is possible through his research and making a positive impact on the field. With his strong academic foundation, research experience, and passion for machine learning, He is poised to make significant contributions to the field and drive innovation in the intersection of mathematics, statistics, and artificial intelligence.

RESEARCH DETAILS

ORCID ID: 0000-0003-2541-6267
Scopus ID: 57221787558
Vidwan ID: 255720
Google Scholar ID: https://scholar.google.co.in/citations?user=rM7tA08AAAAJ&hl=en