Human-Centric AI Guidance for Visual Analytics

Speaker:             Arpit Narechania

Time:                  10:00, Jan. 17th.

Location:            SIST 1A-200

Host:                   Prof. Quan Li

Abstract:

Given the scale and complexity of today's datasets, people face a critical challenge during visual data analysis: an overwhelming number of decisions. These decisions—about what, where, when, and how to visualize data—directly influence the quality of the analysis process and outcomes. For example, a user must decide what attributes to visualize, whether to apply filters, or which chart type best represents the data. WhileAI-powered tools are increasingly available to assist with these decisions, current support often lacks the human-centric adaptability and transparency that users need, leading to biased interpretations, missed insights, and flawed conclusions. In this talk, I will showcase guidance-enriched visual analytics tools where AI-powered systems and human users “guide” each other during analysis. Specifically, I will demonstrate how guidance can (1) help data analysts increase awareness of (un)biased analytic behaviors during visual data analysis, (2) support mapmakers in creating accurate and trustworthy maps, (3) help people author and style data visualizations using natural language, and (4) help everyday web users shop online. I will conclude with some of my thoughts on how a Human-centric AI (unlike today's AI-centric User) enhances human decision-making as well as system learning, championing the vital and inevitable collaboration between humans and AI.      

Bio:

Arpit Narechania is an Assistant Professor in the Department of Computer Science and Engineering (CSE) at the Hong Kong University of Science and Technology (HKUST). He received his PhD in Computer Science from Georgia Institute of Technology, USA, and BS (B.Tech.) in Mechanical Engineering from Indian Institute of Technology (IIT) Mandi, India. His doctoral dissertation, “Designing, Developing, and Democratizing Guidance for Visual Analytics,” received the 2025 IEEE VGTC Visualization Dissertation Award.Arpit's main research interests are in visual analytics, human-computer interaction (HCI), and artificial intelligence (AI), with a particular focus on catalyzing human-AI collaboration—as part of which he builds interactive tools and fosters conducive environments that actively enhance the way humans and AI work together. He has collaborated with industry leaders such as Adobe, Microsoft, Ford Motor Company, and Alibaba, leading interdisciplinary projects that have resulted in multiple patents, publications, product integrations, and open-source releases. For details, check out his homepage at.