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Motorola Corporation Project

The School developed the self-service kiosk prototype funded by a $250,000 research grant from Motorola Corporation. Graduate and undergraduate students, faculty and staff contributed to the development of a completely functional prototype that allows consumers to shop for, purchase, pay for, dispense and set-up their own wireless telephone, via artificial intelligent assistance. This prototype was demonstrated at the Motorola Tech Fair, in Schaumburg, IL.

NASA Project

Based on $99,000 NASA grant the School implemented a minority mentoring and scholarship program. The money assisted students pursuing science-based programs of study, and help the University develop a computer assisted academic counseling and student recruitment system.

NSF Project

In 2009-2011 a Trial-and-Failure Project Tutoring System (National Science Foundation, $43,000) was proposed. The main idea was to construct an interactive project tutoring tool called APOGEE and a collection of companion laboratory modules. APOGEE adopted a trial-and-failure teaching strategy. Students can submit projects multiple times to APOGEE before deadline. Each temporary submission will be graded instantly, with each project requirement evaluated fairly and consistently by APOGEE. Any failure scenario will be displayed to students interactively online, step by step. Then, students learn from failures, refine project design, and make the submission again. The cyclic improvement model can greatly enrich students' learning experience without burdening faculty in grading.

Students' Advisement

In 2012 Capstone Project was developed by students Edward Lowell, Yunfeng Zhao and advisor Simon Baev. Team solved the problem wich excisted with paper signed up advisement. The following solution was implemented on Android platform: professor specifies date and time slots and students could select one or several time slots to set up an appointment. Then professor has to approve these slots.

GA Trees

Georgia Trees

This project was developed for Forestry Commission by Jams Lamb, Yujia Wong, Tatiana Baeva lead by advisor Simon Baev in 2014. Team had to solve the problem with original data which was represented in text format. It was hard to navigate and search for specific information through exsited document. Students came out with a set of question which allowed to easily navigate and identify specific tree. Application has 2 modes: navigation and identification and was implemented on Android platform.


This Capstone Project will have the following features: development of Data collector which can combine students activities and efforts in different areas of college life including academic achievement, participation in athletic and other events, community service, etc. Project will have many participators: Office of Information Technology as experts, Simon Baev as student advisor, campus community and faculties bring ideas and give evaluation. CS will develop Web application and portable kiosk across the campus to register participation in certain activities.

Rain Racer

There is a problem which exists with highly popular courses that don't have sufficient numbers of sits - they are usually getting packed pretty fast and many students suffer from not being able to register for those course in several semesters. Dr. Simon Baev proposed a solution which allows a student to subscribe for an arbitrary number of CRNs that are associate with closed sections. In case some other student drops her registration to one of the subscribed CRNs an email is sent to subscriber to notify about vacancy. This Web application uses PHP and Java script (RAIN (Banner Web as the source of data) and was developed in 2015.

Express Decision

Express Decision Making Tool

Dr. Baev and Dr. Yemelyanov developed a tool to solve a problem of assisted decision making process. A user needs to summarize all positive and negative aspects for each of the choices. Every option can be assigned with numerical rang in terms of intensity and likelihood. Then all numerical ranges of all options are evaluated to choose the best option. Application was developed by using HTML5 in 2015. This solution was presented in Society for Risk Analysis 2015 Annual Meeting (SRA 2015 Annual Meeting), Arlington, Virginia, December 6-10, 2015.

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