• Interval arithmetic: we explore ways to make interval computations more efficient and how to integrate them in current solver frameworks. This work is primarily carried out by Paden Portillo.
• Symbolic-numeric algorithms for solving continuous non-linear constraints. This work is carried out with Mario Bencomo.
• Applications of constraint solving techniques are also explored. Shubhra Datta works on using constraints to model and solve verification of program problems. Xiaojing Wang works on determining fuzzy measures and she is researching on how optimization and constraint techniques can help.
• All of our work is to be implemented in Matlab. This task is taken over by George Moreno.

CAREER Project Objectives:

• Discover new and more efficient constraint solving algorithms for reliable solutions for large problems and/or conflicting constraints and/or distributed problems
• Attract more women and minority students to computer science
• Promote the constraint solving community
• Material from NSF CAREER project
• Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Additional Group Objectives:

• Explore applications of constraints, such as verification of programs, determination of fuzzy measures
• Multi-criteria decision making:
  • design new solving techniques that can scale to address even reasonably sized problems
  • explore applications
  • explore the impact of subjectivity and possibly biases in decision making and in modeling its process.