Ivona Bezáková

Ivona Bezáková is a Professor in the Department of Computer Science at the B. Thomas Golisano College of Computing and Information Sciences, Rochester Institute of Technology. With a research career spanning nearly two decades, she has established herself as a prominent figure in theoretical computer science and computer science education, with over 70 publications from 2005 to 2025.

Her academic journey shows progression from foundational work in theoretical algorithms to broader educational applications. Early research focused on sampling methods and counting problems in graphs, while recent work emphasizes innovative educational approaches using pencil puzzles and board games as teaching contexts.

Bezáková's research spans algorithms, graph theory, and computational complexity, with particular contributions to sampling methods and counting problems. Her educational work has significantly influenced computer science pedagogy, especially through puzzle-based learning approaches. The evolution of her publications shows a strategic integration of theoretical foundations with practical educational applications.

Her publication record demonstrates consistent productivity across top venues including SIAM Journal of Computing, ACM Transactions, and leading conferences such as STOC and SIGCSE. Recent work shows increasing focus on the intersection of theoretical computer science with educational applications and AI-enhanced learning tools.

• Over 20 publications in SIGCSE (computer science education conference)
• Multiple publications in top theoretical venues (SIAM, STOC, SODA)
• Long-standing collaborations with researchers like Daniel Stefankovic (19 papers), Leslie Ann Goldberg (13 papers), and Zack Butler (10 papers)

As an educator and mentor, Bezáková has guided several students including Angelina Brilliantova, Hannah Miller, and Wenbo Sun. Her work on feedback tools for theoretical CS courses demonstrates commitment to improving student learning experiences. She leads research at the intersection of theoretical computer science and educational innovation, developing methods that help students grasp complex concepts through engaging activities.