Intelligent Networks Laboratory

AI and graph-based systems.

Menu

Student Research Opportunities.

The UWB CSS Intelligent Networks Laboratory is interested in the intersection of network-based AI, biology, and computing. This includes building simulators and simulations of graph-based systems, developing computational solutions for biology, analyzing simulation or experimental data, using knowledge learned from the study of biological systems in engineering, creating related educational tools, and developing all of the infrastructure necessary to do these things and disseminate our results. This means that we have a wide range of opportunities for students to help, from new CSSE/Applied Computing/IMD majors to graduate students searching for a thesis topic. It also means that our work intersects with a number of CSS faculty members' interests, as well as colleagues in other UWB programs and at other campuses. If you're interested, you can begin working in the lab early in your career here at UWB doing general tasks and learning about the specifics of our work, and later start on more ambitious projects. This is an excellent way to build a portfolio of work and to build professional connections with faculty and other students.

Open Projects.

  • Core simulator software development, including improving simulator capabilities, improving simulator code base, and CPU and GPU performance.
  • Simulator software engineering, including architecture and development process maturity.
  • Experiment management software development, including software and data provenance, data management, and user interface design.
  • Computational neuroscience research, including simulation of development and learning in nervous systems and analysis of network behavior and architecture
  • Next-Generation 911 systems simulation, including performing and analyzing simulations and working with external stakeholders to develop tools for decision-makers.
  • Development of data analysis and visualization tools for the behaviors and architectures of graphs composed of tens to hundreds of thousands of vertices and hundreds of thousands to millions of edges over long periods of time.
  • Building educational tools for classes that teach lab-related topics.

Any of these areas could be used for an undergraduate capstone, undergraduate research, or a Masters thesis or project. If you are interested, first read through the project descriptions on this site and then contact Prof. Stiber.