I Am Data Science | Armin Schwartzman

HDSI Faculty Feature Article Series: I Am Data Science

with Professor Armin Schwartzman

by Bobby Gordon

Armin SchwartzmanHDSI Professor Armin Schwartzman’s research encompasses theoretical and practical aspects of statistical signal and image analysis in a variety of scientific applications. These include spatio-temporal and high-dimensional data analysis, geometric statistics and smooth Gaussian random fields, with applications in biomedicine, the environment, neuroscience, genetics and cosmology.  His background includes serving as a research & development engineer at Rockwell Semiconductor and Biosense Webster, and has held faculty positions in Biostatistics at Harvard University and Statistics at North Carolina State University prior to joining the faculty in Biostatistics and at the Halıcıoğlu Data Science Institute at UC San Diego.

But how did Armin become interested in the field of data science?  “I have always been interested in both data and science. This started when I studied electrical engineering as an undergraduate, which I saw as a sum of mathematics and physics,” says Armin.  “It then continued when I studied Statistics for my doctoral degree, which provided a solid foundation on the mathematical and computational aspects of analyzing data, and at the same time opened for me the door to all of science without having to specialize in any particular field.”  Armin studied Statistics and earned his Ph.D. from Stanford University.  “I have continued this approach throughout my career and have had the fortune to work with scientists in many fields, whose problems have inspired development of analysis methodologies and deep philosophical questions. Data science embodies for me the way I always envisioned to analyze data and do science.”  In essence, he was a practicing data scientist before the field officially existed.

Armin’s approach to data science focuses on “…let[ing] science and data define the problems I work on, and in solving these problems, I like to consider the entire range from the abstract theory to the practical aspects,” he says.  “For example, I am developing probability theory and statistical methods for smooth random fields as a model for noise in images, and using them to detect signal peaks in brain activity, localized changes in climate, and celestial objects against the cosmic microwave background radiation.”

His generalist view has been showcased in Research Features magazine and interviewed by KTEP’s Science Studio, and includes his current work on developing a project to monitor mountain glaciers.  When looking to future projects, Armin says “Data Science is emerging as a big unifier of the sciences through the lens of data. I am excited about the exchange of ideas across scientific disciplines and unifying forces to solve the big problems of our time. At the same time, being in data science has revived in me the desire to explore fundamental philosophical questions about epistemology. I am excited to pursue both avenues in the future.”

What is Armin’s advice to those interested in entering the field of data science?  “Data Science is a wide field. If you like wide exploration, Data Science is for you. However, make sure to carve your own path.”  Indeed, sound advice from Armin.

Connect with Armin Schwartzman’s HDSI/UC San Diego profile: https://datascience.ucsd.edu/directory/name/armin-schwartzman/