Ken Wachter

K.W.W.
Professor
Primary Research Area: 
Applied & Theoretical Statistics
Sub-Focus: 
Statistics in Social Sciences
Phone: 
(510) 642-1578
Email: 
wachter [at] demog [dot] berkeley [dot] edu
Office Hours: 
Tuesdays 1:00 P.M. by appointment

Ken Wachter has held a joint appointment in Demography and Statistics at Berkeley since 1979. He received his B.A. from Harvard in 1968 and his Ph.D. in Statistics from Cambridge in 1974, completing a thesis on random matrix eigenvalues under the supervision of David Kendall and John Kingman.     

After time at Bell Laboratories, at St. Catherine's College, Oxford, and teaching at Harvard, he came to Berkeley originally as a Miller Fellow. His books include Statistical Studies of Historical Social Structure (1978), Height, Health, and History (1990), and the collection Between Zeus and the Salmon (1997). ``A Mutation-Selection Model for General Genotypes with Recombination'', written with Steve Evans and David Steinsaltz,  has just been published (2013) as a Memoir of the American Mathematical Society.    

A member of the National Academy of Sciences since 1999, he serves on the Editorial Board of PNAS handling social sciences. His wife is a CAL alumna and his poodle Ambrose an enthusiastic CAL fan.

Research Interests: 

Mathematical demography, models for the evolution of aging, simulation.

As a mathematical demographer and statistician, I study systematic constraints and random influences that shape the structure of human populations. I helped develop methods of computer simulation to understand the rarity of coresident family members in pre-industrial English households. With these methods, I am now forecasting the kin and family support available to new generations of elderly in the Twentyfirst century. Working in "non-linear" demography, I have identified mechanisms that give rise to specific kinds of cycles in fertility and population growth. I am currently interested in patterns of mortality at extreme ages shared between humans and other species, trying to reconcile them with statistical models for long-term processes of evolutionary change.