Ph.D. Student, Brandeis Universtity
Greater Boston Area
Ph.D. Student, Brandeis Universtity
Greater Boston Area
Of all the perspectives on evolution—molecular, developmental, game theoretic, etc.—the computational perspective is perhaps the least developed. Yet, it is this perspective—i.e., evolution as computation—that is most likely to unlock evolution's deepest secrets, and organize its future study. Interestingly, the front lines in the struggle to identify the computational underpinnings of evolutionary adaptation lie outside evolutionary biology, in a sub-discipline of computer science called genetic algorithmics. Genetic algorithms are search algorithms that mimic natural evolution. When applied to combinatorial optimization problems that are poorly understood or known to be hard, these algorithms frequently "evolve" solutions of high quality. Although genetic algorithms have been widely used for over three decades, the computational underpinnings of their adaptive abilities have remained mysterious. Over the past few years I have made breakthroughs that expose the essential nature of these computational underpinnings. My results have deep ramifications for the fields of genetic algorithmics, optimization, machine learning, and evolutionary biology.
I am looking to continue my research on evolutionary computation within a vibrant department/organization. If you know of one that will be supportive of my work, kindly contact me.
Genetic Algorithms, Complex Systems, Optimization, Evolutionary Biology
(Computer Software industry)
2002 — Present (6 years)
(Educational Institution; 10,001 or more employees; Higher Education industry)
August 2000 — August 2002 (2 years 1 month)
(Public Company; 10,001 or more employees; ORCL; Computer Software industry)
August 1998 — August 2000 (2 years 1 month)
Ph.D., Computer Science, 2002 — 2008
Graduate Student, Brain and Cognitive Sciences, 2000 — 2002
A.B., Computer Science, Mathematics, 1994 — 1998
evolutionary computation, genetic algorithms, machine learning, optimization, complex systems
TinyGA competition Winner, Genetic and Evolutionary Compuation Conference (2006).
Sproull Fellowship (for unusually strong potential for graduate study. The most prestegious fellowship awarded by the University of Rochester, 2000)
Mary Evelyn Wells and Gertrude Smith Prize (for excellence in the study of undergraduate mathematics, Vassar College, 1998)
General Honors, Honors in Mathematics, Honors in Computer Science, Vassar College (1998)