Guidance-Enriched User Interfaces that Enhance Visual Data Analysis

Speaker: Arpit Narechania
         Georgia Institute of Technology

Title:  "Guidance-Enriched User Interfaces that Enhance Visual Data

Date:    Thursday, 11 April 2024

Time:    11:00am - 12 noon

Venue:   Rm 4580 (via lift no. 27 or 28), HKUST


We live in an era of unprecedented availability of data and computational
resources, wherein humans (users) and computers (systems) often work
together to perform analytic tasks. However, automated computations by
systems may often be premature or flawed as their interpretation of the
user's intents might be incomplete or incorrect. In addition, the computed
outputs may still need to be appropriately explained to the user to
instill trust and also seek feedback, implying the need for continuous
"guidance" from each other to minimize their relative 'knowledge gap'. My
research contributes guidance-enriched user interfaces that facilitate
appropriate and timely guidance to help users ensure proper analytic
progress. In this talk, I will describe some of my systems that enhance
users' visual data analysis experiences by (a) increasing awareness of
their analytic behaviors ("Lumos"), (b) understanding users' preferences
to receive guidance ("ProvenanceLens"), (c) utilizing haptic feedback as
an alternate guidance modality ("BiasBuzz"), (d) adapting the amount and
type of guidance to the users' needs ("Lighthouse"), and (e) democratizing
access to build custom guidance tools ("ProvenanceWidgets"). I will
conclude the talk by describing my ongoing and future directions for
guidance-enriched user interfaces and their applications.


Arpit Narechania is a computer science PhD student at the Georgia
Institute of Technology in the U.S., where he studies mixed-initiative,
guidance-enriched user interfaces that enhance visual data analysis
experiences. These interfaces facilitate appropriate and timely guidance
to help users accomplish analysis tasks. Arpit has also led multiple
interdisciplinary collaborations with automobile engineers, database
engineers, data scientists, data analysts, and cartographers and
geographic information system experts. His work has been published in IEEE
(VIS, TVCG, CGA, BigData), ACM (CHI, IUI, SIGMOD), PVLDB, GIScience, and
has also resulted in multiple patent filings, product integrations, and
open-source tools. He is an overall finalist (winner in computer science)
of the Foley Scholar award and the recipient of a Graduate Teaching
Fellowship and a Graduate Teaching Assistant of the Year award. To learn
more about Arpit and his work, please visit