Lecture Previews

Brain Injury from Two Perspectives

Tuesday, Oct. 4 at 7 p.m.

Rangos 3

Carnegie Mellon professor of mathematical sciences Deborah Brandon and her neuropsychologist, Dr. William J. Hawthorne III, will discuss the path to recovery from brain injury.

Brandon is a survivor of brain injury and has had three brain surgeries; Hawthorne has aided in her rehabilitation. They will describe brain injury recovery from the perspective of patient and doctor.

Developments in Field of Electron and Related Transfers: Early and Recent

Tuesday, Oct. 4 at 4:45 p.m.

Mellon Institute Auditorium

Nobel laureate and chemist Rudolph A. Marcus will discuss the history of work in electron transfer, and the direction in which the field is headed, as part of the biennial John A. Pople Lectures in Theoretical and Computational Chemistry.

Marcus is a professor of chemistry at the California Institute of Technology; he is also a member of the International Academy of Quantum Molecular Science. Marcus received his Ph.D. from McGill University, and his research has focused on chemical reaction rate theory. In 1992, he received the Nobel Prize in chemistry.

Rethinking the Threat from Brain Scans in the Courtroom

Thursday, Oct. 6 at 4:45 p.m.

Baker Hall A53

Adina Roskies will present the arguments for and against the admission of brain scans as evidence in the courtroom, explaining the reasons that some people believe they could be misleading, and the possible implications of new arguments.

Roskies is a professor of philosophy at Dartmouth College, specializing in the philosophy of science. She has published many journal articles and book chapters on neuroscience.

Scaling Machine Learning to the Internet

Thursday, Oct. 6 at 4:30 p.m.

Gates Center 8102

Alex Smola will lecture on techniques for dealing with models of situations with both observed and unobserved variables. He will discuss computer algorithms that deal with problems such as classification, recommendation systems, topic modeling, and user profiling.

Smola’s research is focused on methods for estimation. He received his Ph.D. from the University of Technology Berlin, and has published and edited several books on machine learning.