Terrence Fine, Cornell professor of electrical engineering and statistical science, has been named director of Cornell's Center for Applied Mathematics.

The center has a membership of approximately 80 faculty and 40 graduate students with interests in the applications of mathematical and computational methods to a wide variety of problems arising in the biological, physical and social sciences and in engineering.

Fine has been honored for his excellence as a teacher at Cornell, being awarded the College of Engineering's Fiona Ip Li and Donald Li Teaching Prize for 1996 and the School of Electrical Engineering's Ruth and Joel Spira Excellence in Teaching Award for 1998-1999. The new director received his doctoral degree at Harvard University in 1963 and the following year became a lecturer and research fellow in Harvard's Division of Engineering and Applied Physics. That same year he was awarded a Miller Institute Junior Research Fellowship at the University of California at Berkeley.

Fine joined the Cornell School of Electrical Engineering faculty in 1966. He is a member of Cornell's graduate fields of applied mathematics, electrical engineering, history and philosophy of science and technology, and statistics.

He has been a visiting professor of electrical engineering at Stanford University, and he is a fellow of the Institute of Electrical and Electronics Engineers (IEEE) and a member of the Institute of Mathematical Statistics. He has been awarded a patent for statistical delta modulation.

Fine shared in the outstanding paper awards given by the IEEE Control Systems Society in 1978-79 for his paper with W. Hwang, "Consistent Estimation of System Order," published in IEEE Transactions on Automatic Control. He has been an associate editor for book reviews and for detection and estimation of IEEE Transactions on Information Theory. Most recently, he is the author of Feedforward Neural Network Methodology (Springer, 1999).

In 1988 Fine was elected president of the board of governors of the IEEE Information Theory Society, and he has been a member of the governing board of the IEEE Neural Networks Council.

His current research centers on physical layer issues in sensor-assisted wireless mobile communications and on the performance capabilities, training algorithms and applications of feedforward neural networks to problems of wireless mobile communications and to signal processing. This work is an outgrowth of his research efforts since 1989 that have examined statistical and algorithmic issues arising in the design and analysis of feedforward neural networks and in the development of neural network methodology.

The long-term focus of his research has been the foundations of probability, particularly the alternative concepts of comparative and complexity-based probabilities and upper- and lower- or interval-valued probability. These ideas are now being considered for use in management systems for future generations of wireless mobile communications.

Related World Wide Web sites:

• Center for Applied Mathematics: http://www.cam.cornell.edu.