Computer Science and Statistics

College of Arts and Sciences

News and Announcements

MS Access Database Design for Wildlife

Research Assistant: MS Access Database Design for Wildlife Inventory Data Department of Natural Resources Science, University of Rhode Island A research assistant is needed to develop two databases in MS Access for herpetofaunal inventory data collected in national parks in New York and Virginia. This position is for 10 hours per week and is located(…)

CBA New Course Offerings

New Course Offerings Spring 2017 General business students = professional elective, all others = elective BUS 149X • Introduction to Entrepreneurship » Open to all students no pre-requisites. BUS 247X • Business of Innovation: the Design Process » Open to all students, no pre-requisites. BUS 469 Section 0003 • Special topic – Business of Innovation:(…)

REU in Data Intensive Scientific Computing (DISC)

The University of Notre Dame DISC combines big data, big science, and big computers at the University of Notre Dame. The only thing missing is you! We invite outstanding undergraduates to apply for a summer research experience in DISC at the University of Notre Dame.  Students will spend ten weeks learning how to use high performance(…)

Software Engineering Intern

Description: FarSounder is a small and growing marine sonar company located in Warwick, Rhode Island. We’ve invented and developed a new kind of sonar that shows the user a 3D image of the underwater environment in front of their vessel (similar to radar, but in 3D and underwater). We’re looking for a bright Junior or(…)

INBRE Web Developer

The Rhode Island INBRE program at the College of Pharmacy is looking for help in building a metrics tracking database for our program. Our current metrics tracking database in insufficient for our needs, so we are creating a graph-based system similar to a social network to simplify data entry, access and visualization. We are in(…)

Statistics Thesis Defense: Daven Amin

Risk Classification in High Dimensional Survival Models Date: Monday, November 21, 2016 Place: 052 Tyler Hall Time: 11:00 a.m. Sparse regression models are an actively burgeoning area of statistical learning research. A subset of these models seek to separate out significant and non-trivial main effects from noise effects within the regression framework (yielding so-called “sparse”(…)

Statistics Thesis Defense: Zidan Wu

NETWORK-BASED STATISTICAL METHODS FOR THE ANALYSIS OF STOCK RETURNS Date: Monday, November 21, 2016 Place: 049 Tyler Hall Time: 9:00 a.m. To maximize returns and diversify portfolios, the stock price market participants have always been interested in learning associations of stock price returns for different companies. Five primary goals of this thesis are: (1) to(…)

CRA-Women Graduate Student Cohort Workshop

The Computing Research Association would like to encourage graduate students from The University of Rhode Island to participate in a skill-building and mentoring workshop specifically for women in computing. All travel expenses are reimbursed for this workshop. The upcoming CRA-Women Graduate Student Cohort (Grad Cohort) will be held April 7-8, 2017 in Washington, D.C. The(…)

Crowdsourcing Deep Thoughts: Meeting the Challenges of In-depth Language Understanding Systems for Smarter Social Media

Speaker: Jamie Macbeth Speaker Affiliation: School of Engineering, Fairfield University Date: Friday, November 18, 2016 Time: 2:00 PM to 3:00 PM Location: CBLS 152 Intelligent systems driven by natural language input are well-positioned to meet the challenges of intervening against abuses of social media (such as cyberbullying) and providing resources for victims. However, the language(…)

Programming for Data Science – Spring 2017 CSC392 Sec 02

CSC392 Section 02 Dr. Lutz Hamel Programming for Data Science Spring 2017, T&Th 12:30-1:45PM Data science exists at the intersection of computer science, statistics, and machine learning. That means writing programs to access and manipulate data so that it becomes available for analysis using statistical and machine learning techniques is at the core of data(…)

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