CS professor Daniel Kang wins SIGMOD dissertation award

CS professor Daniel Kang has received the 2024 Association for Computing Machinery SIGMOD Jim Gray Doctoral Dissertation Award for “Efficient and accurate systems for querying unstructured data.” The award recognizes “excellent research by doctoral candidates in the database field.” CS professor Jiawei Han wrote a letter of recommendation on Kang’s behalf. As a winner, Kang is invited to serve on a SIGMOD evaluation committee at least once in the years to follow.

For his dissertation, Kang focused particularly on video analytics and data systems for deploying machine learning. He said, “At the time of my dissertation, we were able to use machine learning to automatically extract insights from video, images, and text via machine learning. Practitioners ranging from business analysis to social scientists could use this technology to automatically analyze data that required manual processing before. Unfortunately, it's extremely expensive to use ML to analyze large quantities of data. My dissertation created systems, algorithms, and abstractions to allow non-experts to query this data cheaply and without requiring expertise in ML and data systems.”

The ACM International Conference on Management of Data takes place in Santiago, Chile, from June 9 to 14. The conference describes itself as “a leading international forum for database researchers, practitioners, developers, and users to explore cutting-edge ideas and results.”  Kang presented his work at the conference along with the winners of the SIGMOD Innovations and Test of Time awards.