Democratizing Data Science
Despite great strides in the generation, collection, and processing of data at scale, data science is still extremely inconvenient for the vast majority of the population. The driving goal of our research is to make it easy for individuals and teams — regardless of programming or analysis expertise — manage, analyze, make sense of, and draw insights from large datasets.
In my talk, I will describe a comprehensive suite of tools that we’ve been building to empower everyone to perform data science more efficiently and effortlessly, including DataSpread, a “big data” spreadsheet tool that combines the benefits of spreadsheets and databases, and Zenvisage, a visual exploration tool that accelerates the discovery of trends or patterns. Our tools have been developed in collaboration with experts in neuroscience, battery science, genomics, astrophysics, marketing analytics, and ad analytics.
I will discuss some of the key technical challenges underlying the development of these tools, and how we addressed them, drawing from ideas in multiple disciplines. I will finally outline a future research agenda for tool development to empower everyone to tap into the hidden potential in their datasets at scale.
Aditya Parameswaran is an assistant professor in computer science at the University of Illinois (UIUC), with affiliate appointments at the Illinois Informatics Institute, the Institute for Genomic Biology, and the interdisciplinary Beckman Institute. He spent a year as a postdoc at MIT CSAIL following his Ph.D. at Stanford University (2013), before starting at Illinois in August 2014. He develops systems and algorithms for "human-in-the-loop" data analytics, synthesizing techniques from databases, data mining, and human-computer interaction. Aditya received the ARO YIP (2018), the NSF CAREER (2017), the IEEE TCDE Rising Star award (2017), the Dean's Excellence in Research award (2018) and the C. W. Gear junior faculty award from Illinois (2017), doctoral dissertation awards from SIGMOD, SIGKDD, and Stanford (2014), "Excellent" instructor awards from Illinois (2015, 2017), a Google Faculty award (2015), and six best-of-conference citations (including VLDB, KDD, and ICDE, 2010-17). He is an associate editor of SIGMOD Record and serves on the steering committee of the HILDA (Human-In-the-Loop Data Analytics) workshop at SIGMOD and the DSIA (Data Systems for Interactive Analysis) workshop at VIS. His research group is supported with funding from the NSF, the ARO, the NIH, Adobe, Toyota, the Siebel Energy Institute, and Google.