• Ph.D. in Industrial Engineering and Operations Research, University of California at Berkeley, 1999
• M.S., University of California at Berkeley, 1994
• B.S. in Applied Mathematics, Brown University, 1989

Many of the companies in the Richardson Telecom Corridor are involved in the design, development, and deployment of fiber-optic telecommunications networks. In order to meet customer demand for information services with high reliability and fast response times, these networks must be fault-tolerant. To be economically viable, they must be efficiently designed. Designing the least-cost, fault-tolerant network can be quite challenging. Many factors must be taken into consideration, such at the cost and capabilities of the available networking equipment, but the key data that drives the design process is a forecast of the demand that will placed on the network.

Unfortunately, demand in the telecom industry is notoriously difficult to predict and there is concern that a design for an erroneous forecast may prove to be inferior. If the forecast is too low, the network will not have enough capacity to handle the demand and network owner will likely lose business. Conversely, a network designed for forecast that turns out to predict more demand than is realized will be over provisioned with expensive, underutilized equipment. In our project, we are developing a design methodology that accounts for the uncertainty in the demand forecasts and provides designs that will work well over a wide range of possible demand scenarios. [Project Details ]

• Applied optimization
• Network design

• Alpha Pi Mu, University of California at Berkeley
• Academic Senate Outstanding Graduate Student Instructor,
  University of California at Berkeley, 1998
• Member Remote Interactive Optimization Testbed