I am an assistant professor at the University of California, Berkeley, with a joint appointment at the I School and EECS. I am part of the Data Systems & Foundations group and the Human-Computer Interaction group, and I am affiliated with the RISELab and the Berkeley Institute of Design.
My research interests are broadly in building tools for simplifying data analytics, i.e., empowering individuals and teams to leverage and make sense of their datasets more easily, efficiently, and effectively.
We are always looking for postdocs, PhD, MS, and UG students or research/development staff to join our efforts! If you are a postdoc or staff applicant, feel free to email me directly with your CV and qualifications. If you are an aspiring PhD student, please apply to the EECS or I School PhD programs. If you are an MS or UG student, feel free to fill out this form: it is rare that we will work with students outside UC Berkeley except in cases of unusually good fit.
Aditya Parameswaran is an Assistant Professor in the School of Information (I School) and Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley. Until June 2019, Aditya was an Assistant Professor in Computer Science at the University of Illinois, Urbana-Champaign. He spent a year as a PostDoc at MIT CSAIL following his PhD at Stanford University. He develops systems and algorithms for "human-in-the-loop" data analytics, synthesizing techniques from database systems, data mining, and human-computer interaction.Click here for a longer bio.
I am a Co-Chair of Workshops for SIGMOD 2020. Please send us your exciting and engaging community-building ideas! Interdisciplinary/novel workshop ideas encouraged. Here is the call for proposals.
I serve on the steering committees of HILDA (Human-in-the-loop Data Analytics) at SIGMOD and DSIA (Data Systems for Interactive Analysis) at VIS. Lots of excitement around this nascent area at the intersection of databases, data mining, and visualization/HCI - join us!
This cycle, I am serving as an Area/Associate Chair for HCOMP 2020, VLDB 2020, and SIGMOD 2020, as a Program Committee member for VLDB Demo 2019 and HILDA 2019 (phew!) I've served on the program committees of VLDB, KDD, SIGMOD, WSDM, WWW, SOCC, HCOMP, ICDE, and EDBT, many of them multiple times.
Past: I stepped down as Associate Editor for SIGMOD Record after nearly half a decade. I co-organized HILDA 2017. I was the SIGMOD 2016 Undergraduate Research Chair.
Zenvisage is a tool for effortlessly visualizing insights from very large data sets. It automates finding the right visualization for a query, significantly simplifying the laborious task of identifying appropriate visualizations.
Helix accelerates the iterative development of machine learning pipelines with a human developer "in the loop" via intelligent caching and reuse.
Project page here.
DataSpread is a tool that marries the best of databases and spreadsheets.
Project page: here
DataHub (or "GitHub for Data") is a system that enables collaborative data science by keeping track of large numbers of versions and their dependencies compactly, and allowing users to progressively clean, integrate and visualize their datasets. OrpheusDB is a component of DataHub focused on using a relational database for versioning.
Project page: here
Our work has developed a number of algorithms for gathering, processing, and understanding data obtained from humans (or crowds), while minimizing cost, latency, and error. Since 2014, our focus has been on optimizing open-ended crowdsourcing: an understudied and challenging class.
Project page: here