معرفی
Dr. Alexei Vernitski is a Senior Lecturer in the School of Mathematics, Statistics and Actuarial Science (SMSAS) at the University of Essex. His research focuses on applying artificial intelligence (including reinforcement learning and deep learning) to mathematical problems in knot theory, algebra (e.g., braid theory), and universal algebra. He also explores mathematics education, particularly enhancing student motivation. Previously, he worked in the financial sector as a programmer and as a computer science lecturer.
His research interests span AI-driven knot theory, algebraic structures (semigroups, groups), and mathematics education. Notable areas include the application of neural networks to braid untangling, automated reasoning in knot diagrams, and cognitive studies on math anxiety using EEG. He has supervised PhD students in mathematics education, universal algebra, and computer science applications of mathematics.
His recent work demonstrates trends in combining machine learning with topological and algebraic problems, emphasizing practical AI solutions for abstract mathematical challenges. His articles reflect interdisciplinary approaches, merging computer science techniques with pure mathematics.
Dr. Vernitski has advised multiple PhD students, contributing to diverse fields from knot theory to educational technology. His work bridges theoretical mathematics with real-world applications, such as optimizing data transmission and enhancing learning systems through neuroadaptive methods.
