ORIE Students Display Their Work at Research Showcase
Two ORIE projects were featured at the College of Engineering Research Showcase on September 11 in the Duffield Atrium. The student researchers used posters to describe their work to industry representatives and fellow students. They were among 71 researchers participating in the Showcase, a major annual event in the College.
Damla Ahipasaoglu, shown at right describing her work to Norman Bucknor of General Motors R&D, worked on a geometric problem with applications to data analysis, statistics, computational geometry, imaging and optimization. She improved the properties of an algorithm that computes the ellipse of minimum volume that encloses a given set of data points -- but can do so for an arbitrarily large number of dimensions (where the n-dimensional generalization of an ellipse is an ellipsoid). The algorithm also computes solutions to an important and equivalent statistical estimation problem. Damla, a Ph.D. student working with Professor Michael Todd, has shown that her algorithm runs quickly and accurately on very large problems, and has solved the largest known problem in the literature (10,000 data points in 500 dimensions) in less than 30 minutes.
Master of Engineering students Ji Hyun Kim and Lei Yao are shown discussing their project poster with Robert Williams '79, Senior Manager for Innovation and Integration at Boeing. The project describes a project the students carried out last spring, together with undergraduate Antoine Cossart and fellow Master of Engineering students Aditya Guna and James Sanders. Guna and Cossart have since graduated, while Sanders participated with the others in the Research Showcase. The project team studied inventories in the so-called clean rooms at the New York Presbyterian Hospital, the teaching hospital of Columbia University and Cornell. The clean rooms on each floor store everyday items used in the care of patients. In many such inventory cases, effective management entails a tradeoff between ordering costs and holding costs: more frequent ordering reduces the latter but increases the former. Using a combination of optimization and simulation methods, the team showed how the ordering costs for these inventories could be reduced by more than 95% while cutting the holding cost by more than half.