Fri, 14-Oct-2022 / 2:00pm / Packard 202
https://stanford.zoom.us/j/92716427348?pwd=TlV6VHNscGxsTEdlOC8rWkMwaElldz09
General purpose compressors like Gzip and Zstandard perform well on many kinds of data and are standard tools of the computing trade. We can often do better with algorithms specialized for particular data domains, like genomic or numeric data, but the process of building new compressors is often ad hoc and requires domain expertise and compression familiarity. This talk dives into the craft of building new data compressors, focusing on examples from tabular and genomic datasets.
Dmitri Pavlichin is an applied scientist at Amazon. In an earlier life he did research in information theory and bioinformatics as a postdoc with Tsachy Weissman at Stanford and co-founded a data compression startup.
Packard Building
Electrical Engineering Department
350 Jane Stanford Way
Stanford, CA 94305-9515
