We aim to develop intelligent visualization systems that can learn about the task and the user herself to better support the decision-making process. Below we summarize our resaerch interests. If you are a current WashU student, you can find a list of our open projects here.
We leverage machine learning and AI algorithms to learn from users' interaction. We develop intelligent visual analytics systems that predict intentions and proactively provide support during analytical tasks.
We develop visualization tools for comminicating complex health statistics to patients. We also use this problem space to explore the benefits and tradeoffs of combining text and visualization.
We identify personality traits that impact strategy during data exploration. We also apply machine learning to predict individual characteristics (e.g. personality traits and cognitive abilities) from interaction logs.
Dr. Alvitta Ottley
Assistant Professor of Computer Science and Engineering
Assistant Professor of Psychological and Brain Sciences (courtesy)
PhD in Computer Science, Tufts University, 2016
Surina Puri | Georgia Tech
Jennifer Li | Arizona State University
Shayan Monadjemi | University of Texas at Dallas
Jordan Perry | Lincoln University
Jake Kent | Washington University in St. Louis
Jacob Pepe | Washington University in St. Louis
PROACT: Iterative Design of a Patient-Centered Visualization for
Effective Prostate Cancer Health Risk Communication [pdf]
Anzu Hakone, Lane Harrison, Alvitta Ottley, Nathan Winters, Caitlin Gutheil, Paul K. J. Han and Remco Chang
InfoVis (IEEE Transactions on Visualization and Computer Graphics (TVCG)), 2016.
Improving Bayesian Reasoning: The Effects of Phrasing, Visualization, and Spatial Ability [pdf]
Alvitta Ottley, Evan M. Peck, Lane Harrison, Daniel Afergan, Caroline Ziemkiewicz, Holly A. Taylor, Paul K. J. Han and Remco Chang
InfoVis (IEEE Transactions on Visualization and Computer Graphics (TVCG)), 2015.
Personality as a Predictor of User Strategy: How Locus of
Control Affects Search Strategies on Tree Visualizations [pdf]
Alvitta Ottley, Huahai Yang and Remco Chang
Proc. ACM Human Factors in Computer Systems (CHI), 2015.
Honorable Mention Award
Finding Waldo: Learning about Users from their Interactions [pdf]
Eli Brown, Alvitta Ottley, Jieqiong Zhao, Quan Lin, Alex Endert, Richard Souvenir and Remco Chang
VAST(IEEE Transactions on Visualization and Computer Graphics (TVCG)), 2014.
Manipulating and Controlling for Personality Effects on Visualization Tasks [pdf]
Alvitta Ottley, R. Jordan Crouser, Caroline Ziemkiewicz and Remco Chang
Journal of Information Visualization (IVI), 2013
The Adaptive User: Priming to Improve Interaction [pdf]
Alvitta Ottley, Evan M Peck, Lane Harrison and Remco Chang
ACM CHI Workshop on Many People Many Eyes, 2013
How Visualization Layout Relates to Locus of Control and Other Personality Factors [pdf]
Caroline Ziemkiewicz, Alvitta Ottley, R. Jordan Crouser, Ashley Rye Yauilla, Sara Su, William Ribarsky and Remco Chang
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2012
Dan Zeng, Micah Goodman & Manil Bastola
Wint Yee Hnin, Yongzheng Huang & Krushnaraj Kamtekar
Christopher Ogle, Brody Roush & Ben Rosenkranz
Nathan Gitter & Rob Osorio
New Coders Survey
Evan Balzuweit & Kelly Stathis
Joshua Landman & Claire Komyati
The Visual Data Analysis Group at Washington University is looking for up to motivated graduate and undergraduate students who are willing to push the limits of current practices in visual data analysis and create next generataion visualization systems. Areas of interest include:
- Machine Learning and Artificial Intelligence
- Adaptation and Personalization
- Visual Analytics for Non-Experts
- Medical Decision-Making
Apply by emailing your resume to Prof. Ottley.