Yana Kortsarts

Teaching the power of randomization using a simple game

Any deterministic algorithm can be viewed as a game between the algorithm player and the input player. A randomized algorithm can be viewed as a mixed strategy for the first player, used to minimize the disadvantage of being the first to reveal its move. We suggest a simple and accessible guessing game that can serve as both a way to explain notions in algorithms (like worst case input) to students and also to illustrate the power of randomization, presented in an intuitive way.

Dynamic programming across the CS curriculum (abstract only)

Dynamic programming is one of the important algorithmic techniques often not appropriately covered in the core undergraduate CS courses, and there is no sufficient emphasize on application of advanced techniques to practical problems. As a result, students are not becoming fully familiar with this extremely important concept. We present our experience in integrating dynamic programming algorithmic technique in various core and elective undergraduate computer science courses, such as introductory programming, cryptography and bioinformatics. Examples are based on the real world scenarios and motivate students to learn in order to solve practical problems. The reported work was partially funded by the National Science Foundation, NSF CPATH award #0939120 and NSF I3 award #0930242

Developing Computer Forensics Minor -- Challenges and Opportunities: (Abstract Only)

This lightning talk will discuss our experience of developing and managing a new Computer Forensics Minor. The Computer Forensics minor is an interdisciplinary program that integrates criminal justice and computer science and combines both theoretical concepts and practical skills to prepare students for a career in computer forensics-related fields. Students will be prepared for a career in law enforcement or corporate security as a digital investigator and evidence examiner as well as pursue graduate education in the area of information security, digital forensics, or law. The lighting talk will describe the various stages in developing the minor including an analysis of competitive academic programs, evaluation of the current resources, qualifications and faculty considerations, the process of developing the program objectives and learning outcomes, and assessment strategies. The program will be run jointly by Criminal Justice and Computer Science departments, and faculty will communicate regularly to track the number of students in the minor and their progress through the curriculum. Both departments will ensure that the minor provides appropriate course content and learning experiences for graduates seeking employment. In our discussion, we will focus on challenges of designing the balanced curriculum to make it accessible for criminal justice and other non-computer science/computer information systems majors, the need of designing new courses and renovating existing courses to answer growing need to address this new emerging field. Lightning talk will also discuss the anticipated cost of the program, required resources, recruitment strategies, and the administrative approval mechanism.

Work in progress — Women in Computing Honors course

We present our experience in teaching Honors course Women in Computing that was offered for the first time in Fall 2009. The course is cross listed with Womens Studies and provides Honors students with interdisciplinary experience. This course provides an opportunity for students to learn about pioneering women of computing and their contribution into computing field, as well as modern trends and modern gender issues in computer science. The course also introduces students to the world of computing by linking various computer science concepts to the specific contribution. This course brings together undergraduate Honors students from different majors and creates opportunities for interdisciplinary collaboration through the in-class laboratory assignments and team projects. Part of the value of the course experience is in the blending of student expertise in the formation of teams.

Approximation algorithm for directed multicuts

The Directed Multicut (DM) problem is: given a simple directed graph G = (V,E) with positive capacities ue on the edges, and a set K ⊆ V × V of ordered pairs of nodes of G, find a minimum capacity K-multicut; C ⊆ E is a K-multicut if in G – C there is no (s,t)-path for every (s,t) ∈ K. In the uncapacitated case (UDM) the goal is to find a minimum size K-multicut. The best approximation ratio known for DM is min

Greedy approximation algorithms for directed multicuts

{\{O({\sqrt n}), opt\}}

Writing intensive and writing extensive: a continuum for advancing writing in computer science education: panel discussion

by Anupam Gupta [5], where n = |V|, and opt is the optimal solution value. All known non-trivial approximation algorithms for the problem solve large linear programs. We give the first combinatorial approximation algorithms for the problem. Our main result is a

Developing Oral and Written Communication Skills in Undergraduate Computer Science and Information Systems Curriculum.

\tilde O (n^{2/3}/opt^{1/3})

Teaching an Introductory Programming Course For Non-Majors Using Python

-approximation algorithm for UDM, which improves the

Enriching undergraduate computer science curriculum with steganography examples

{\sqrt n}