I have several ongoing projects in the areas of distributed systems, cybersecurity, and computer science education. I will get to update their descriptions here to welcome additional students in the Fall 2020.
For now, I am accepting applications for participation in an online, unfunded REU (research experience for undergraduate) program for the projected below.
The application form (only available to TAMU students) is available at https://forms.gle/3h82hhRKGRy7UD5M9
The required experience varies by project.
Summer (online) REU 2020 projects
I will be offering Research Experience for Undergraduate this summer with online participation only.
There are three main themes (stream computing, data analytics, data-driven tools for computer science education).
Within each theme, there are projects and activities for all experience levels, as long as the student has the programming experience at the CSCE 121 or higher.
The REU program will start around May 18 and it is expected to last 10 weeks.
I do not have approvals to use existing funding on online REUs, so I expect that I won’t be paying any REU student this summer. Funding for continuing in the Fall may be feasible.
- Theme: Stream Computing
Required: Data structures (e.g., CSCE 221).
Very helpful: Some sub-projects require CSCE 313 (but not all)
Overall description:
Our society increasingly relies on applications that process streaming data across geo-distributed sites, such as making business decisions from marketing data, identifying spam campaigns in social network streams, and analyzing genome datasets in different labs and countries to track the sources of potential epidemics. State-of-art solutions for these needs are centered around stateless stream processing. The overall goal of this line of research is to advance stream processing to enable next-generation streaming applications to store and update state along with computation; therefore, processing live data streams in a timely fashion from massive and geo-distributed datasets. This project builds a next-generation geo-distributed scalable stateful stream processing system that will significantly improve the scalability of stream processing systems.
We have sub-projects that advance the distributes system infrastructure and subprojects that build new applications for experimental evaluation. - Theme: Data Analytics
Required: Python programming or experience with Java/C++ and desire to learn Python
Very helpful: Data science course
Students will get experience with data analytics by applying to datasets from several domains: autonomous driving, food production, and computer logs for cybersecurity analysis. - Theme: Data-driven tools for Computer Science Education
Required: Python programming or desire to learn Python
Very helpful: data structures (CSCE 221), databases
The goal of this research project is to leverage the analysis of programs submitted by students to identify points of struggles for students taking introductory programming courses. Our approach leverages the datasets available from autograding systems to capture student coding behavior. This project will develop tools for instructors to extract insights about their students’ progress by analyzing the successive attempts students take to solve a problem.