Operations Research (OR) Methodologies:
- Mathematical Optimization:
- Linear and integer programming
- Stochastic programming
- Non-linear programming
- Dynamic programming
- Neuro-dynamic programming (reinforcement learning) and machine learning
- Heuristic optimization
Statistics:
-
- Multiple imputation
- Bootstrapping
Parallel Computing (PC) techniques to efficiently solve large-scale OR problems
-
- GPU computing
- OpenMP
- MPI
Applications researched in OR and PC:
-
- Renewable energy planning considering multiple stochastic parameters
- Supply Chain Optimization under uncertainty (food supply chains, recycling supply chains)
- Cybersecurity of cyber-physical systems
- Stochastic and dynamic facility layout problems
- Quadratic assignment problem https://claranovoa.github.io/
- Stochastic and dynamic vehicle routing
- Design of electronic supply chains
Applications researched in Statistics:
-
- Design and analysis of experiments with missing values
- Bootstrapping for time studies
Additive Manufacturing
-
- Design of experiments
- Optimization
- Materials science
Applications researched in Additive Manufacturing:
-
- Optimizing the tensile strength of parts fabricated using Additive Manufacturing
Engineering Education Research Areas:
-
- Improving the recruitment and retention of female in Engineering and Computer Science
- Improving retention of first-year undergraduate students, especially underrepresented minorities, through (a) multi-disciplinary orientations (b) training workshops to refine students’ Spatial Visualization and Computational Thinking Skills (c) use of 3D printing.
Applications researched in Engineering Education
-
- Identifying critical activities that promote the success of female cohorts in engineering and computer science
- Identifying major motivators for freshman students to pursue STEM careers
- Assessing the benefits of Lego robotics activities, spatial skills training, and 3D printing experiences to develop students’ spatial and computational thinking skills