Alexander S. Kulikov

Alexander S. Kulikov is a research fellow at St. Petersburg Department of Steklov Mathematical Institute of the Russian Academy of Sciences and a visiting professor at University of California, San Diego. His scientific interests include algorithms for NP-hard problems and circuit complexity. In St. Petersburg, he runs Computer Science Club and Computer Science Center.

Sort options

Algorithms with Numbers (Coursera)

This course represents an introduction to algorithms with numbers, including linear algebra problems and arbitrary precision arithmetic, that appear virtually everywhere, from cryptography to audio processing. You will learn how to: implement the basic number theory algorithms like Euclidean algorithm that are basic building blocks for modern cryptography; work [...]

Computational Geometry (Coursera)

This course represents an introduction to computational geometry – a branch of algorithm theory that aims at solving problems about geometric objects. Its application areas include computer graphics, computer-aided design and geographic information systems, robotics, and many others. You will learn to apply to this end various algorithmic approaches, [...]

Competitive Programmer's Core Skills (Coursera)

During the course, you’ll learn everything needed to participate in real competitions — that’s the main goal. Along the way you’ll also gain useful skills for which competitive programmers are so highly valued by employers: ability to write efficient, reliable, and compact code, manage your time well when it’s [...]

NP-Complete Problems (edX)

Learn about NP-complete problems, known as hard problems that can’t be solved efficiently, and practice solving them using algorithmic techniques. Step into the area of more complex problems and learn advanced algorithms to help solve them.

Graph Algorithms (edX)

Learn how to use algorithms to explore graphs, compute shortest distance, min spanning tree, and connected components. If you have ever used a navigation service to find the optimal route and estimate time to destination, you've used algorithms on graphs.

Data Structures Fundamentals (edX)

Learn about data structures that are used in computational thinking – both basic and advanced. A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently.