My name is Maxim Lisnic and I am a Ph.D. student in Human-Centered Computing at the University of Utah’s Kahlert School of Computing. I am advised by Marina Kogan and Alexander Lex. This summer, I’m interning with Tableau Research.
I am broadly interested in human-data interaction and data visualization. My research focuses on how people interpret, misinterpret, reframe, communicate with, and even spread misinformation with data and charts.
You can access my CV here.
Peer-reviewed publications
“Yeah, this graph doesn’t show that”: Analysis of Online Engagement with Misleading Data Visualizations
Maxim Lisnic, Alexander Lex, Marina Kogan
Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems (CHI ’24)
Paper doi: 10.1145/3613904.3642448
Misleading Beyond Visual Tricks: How People Actually Lie With Charts
Maxim Lisnic, Cole Polychronis, Alexander Lex, Marina Kogan
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ’23)
Paper doi: 10.1145/3544548.3580910
Preprints
Visualization Guardrails: Designing Interventions Against Cherry-Picking in Interactive Data Explorer
Maxim Lisnic, Zach Cutler, Marina Kogan, Alexander Lex
Preprint doi: 10.31219/osf.io/4j9nr
Here’s what you need to know about my data: Exploring Expert Knowledge’s Role in Data Analysis
Haihan Lin, Maxim Lisnic, Derya Akbaba, Miriah Meyer, Alexander Lex
Preprint doi: 10.31219/osf.io/dn32z
Presentations
“Yeah, this graph doesn’t show that”: Analysis of Online Engagement with Misleading Data Visualizations
CHI Conference on Human Factors in Computing Systems, Hamburg, Germany (May 2024)
Designing Insightful Data Visualizations
MarketDial, Salt Lake City, UT (April 2024)
Misleading Beyond Visual Tricks: How People Actually Lie With Charts
CHI Conference on Human Factors in Computing Systems, Hamburg, Germany (April 2023)
Teaching
Teaching assistant & guest lecture for COMP5960: Applied Data Visualization (Fall 2023)
Guest lecture for CS6630: Visualization for Data Science (Fall 2022)
Teaching assistant & guest lecture for DS2500: Data Wrangling (Spring 2022)
