Department of Computer Sciences
University of Wisconsin, Madison
1210 West Dayton St.
Madison, WI 53706
Office: 6385 Computer Sciences Building
Phone: 608-263-2874, Fax: 608-262-9777
Spring 2017 Office Hours: by appointment only. I am traveling a lot in March and April, so I may be hard to catch.
I am a professor working in areas related to Computer Graphics.
These days, my main things are Data Visualization and Robotics, but I remain interested in animation, multimedia, ...
A brief biography will tell you how I got here. You can see a reasonably current CV, but you probably are looking for select publications (papers, videos, talks by project), or a more complete list of papers, talks, or videos in date order. I'l try to keep a list of project descriptions.
On this page: things I'm working on, teaching, recent papers.
Here is my most recent attempt at summarizing my research interests:
How can we use our understanding of human perception and artistic traditions to improve our tools for communicating and comprehending?
This semester (Spring 2017) I am teaching CS765 Data Visualization. I will teach this class again in the Fall of 2017 as well.
I have some pages with various Advice I generally give to students. This includes the format for status reports, what I'd like to see in Prelims and Theses, my grad school FAQ, but my advice on how to give a talk is still elsewhere.
You might be interested in my grad school FAQ. Come and talk to me if you're interested in computer graphics or related topics.
If you're interested in joining our group, come talk to me! If you aren't a student at Wisconsin yet, please look at my grad school FAQ, particularly the last few questions.
Some things that I am working on these days
Two new threads in my work are applying machine learning techniques to visualization problems to help people build "comprehensible models" and perceptually-inspired robotics (that is, making robots move in ways that are easier for people to understand when they watch them).
| Visualizing Comparisons|
Increasingly, visualization needs to help people make comparisons between things in increasingly large data sets. In the past, visualization has focused on helping with particular types of objects: volumes, graphs, molecules, etc. In contast, the Visual Comparisons project tries to understand the general principles that apply no matter what is being compared. We are working with several domain collaborators to explore case studies of comparison to inform the general principles.
Current domain collaborations include Educational Science (comparing epistemic frames), Genetics (comparing whole genome alignments), Structural biology (protein shapes and motions), Literary Scholarship (statistical analysis of text corpora), and Virology (understanding virus evolution). We also collaborate with perception experts to better understand the mechanisms in interpreting images.
Example Projects: Splatterplots, Tagged Text Collections, Whole Genome Sequence Overviews, Comparing Epistemic Frames, Visualizing Virus Evolution, Explaining High-Dimensional Groups
| Animating Communicative Characters|
We are working on better ways to synthesize human motions to make animated characters (both on screen and robots) that are better able to communicate. Generally, we focus on trying to make use of collections of examples (such as motion capture) to build models that allow us to generate novel movements, or to define models of communicative motions.
Example Projects: Simulating Gaze Behaviors, Parametric Motion Controllers
| Visualizing English Print|
Working with Humanities scholars (literary scholars, linguists, historians, ...) we seek to apply "computational thinking" to find new ways of understanding literature and the development of language. We are exploring ways to combine visualization and statistical analytics to help with humanist understanding, and allow scholarship of large text collections. We are also seeing how the ideas of humanist scholarship can be applied in computer science.
Example Projects: TextDNA, CorpusSeperator, High-Dimensional Explanations
| Perceptually-Inspired Robotics|
If robots are going to work around people, it will be important that people can interpret the robots movements correctly.
We are develop ways to make robots move such that people will interpret them correctly. For example, we are considering how to design robot control algorithms such that the resulting movements are understandable, predictable, aesthetically pleasing, and convey a sense of appropriate affect (e.g. confidence).
Example Projects: - Conversational Gaze Aversion for Humanlike Robots, Perceptually Inspired Arm Dynamics
| Re-thinking Photography and Videography|
Digital photography (and videography) has changed the world: it is easy (and cheap) to take lots of pictures and video, to share them with others, and to change them. This means its easy to get lots of bad pictures: good pictures (and video) still takes work.
Our goal is to make it easier for people to have useable images and video. For example, we have developed methods for improving pictures and video as a post-process (e.g. removing shadows and stabilizing video). We have also worked on adapting imagery for use in new settings (e.g. image and video retargeting or automatic video editing) and making use of large image collections (e.g. intestingness detection or panorama finding). In the future, we hope to put these elements together to make systems that help people make effective use of large collections of images and videos.
|| Other Stuff|
I have a bad case of Academic Attention Defecit Disorder, so I am always interested in other things - especially if they involve pictures, geometry, or motion.
My teaching schedule used to be regular, but now it changes every semester.
The classes I teach:
- Visualization: (CS 765 - Spring 2017). I taught this as a special topics class Spring 2015, and a trial run in 2012. It's an experiment in teaching a broad class that serves a very wide range of students (most from outside CS). The experiments were successes, so I intend to do it again.
- CS559 Computer Graphics: I used to teach CS559 Computer Graphics each fall. In the future, I will teach it regularly (but maybe not every fall). Past offerings: 2015, 2014, 2010, 2009, 2008, 2007, 2006, 2005, and if you're really curious, even older versions of the course page are still on the Graphics Group Courses Page.
Older classes that might not get taught again for a while:
- CS777: Computer Animation is a graduate level CS class for people with some graphics background. This taught was taught regularly in the past (2013, 2011,2006,2004, 2003).
- CS679 Computer Games Technologies: this class is popular enough that we try to teach it regularly. I was able to teach it every year for the past few years (2012, 2011, 2010
- Advanced Graphics: In the Spring of 2009, I taught an Advanced Graphics class.
You can find other information on graphics group classes on the Graphics Group Courses Page.
Selected Recent Publications
I try to keep the complete list available here. Here are some selected recent ones:
- Eurographics '17: Zooming on All Actores: Automatic Focus+Context Split Screen Video Generation w/Kumar et al.
- HRI '17: A Motion Retargeting Method for Effective Mimicry-based Teleoperation of Robot Arms w/Rakita and Mutlu
- SIGGRAPH ASIA '16: Authoring Directed Gaze for Full-body Motion Capture w/Pejsa et al.
- VAST '16: The Semantics of Sketch: A Visual Query System for Time Series Data w/Correll
- TVCG '16: Lightness Constancy in Surface Visualization w/Szafir et al.
- ROMAN '16: Motion Synopsis for Robot Arm Trajectories w/Rakita et al.
- ROMAN '16: ''Evaluating Intent-Expressive Robot Arm Motion;; w/Bodden et al. (AWARD)
- BigData '16: A Framework for Considering Comprehensibility in Modeling
- AVI '16: Assessing Topic Representations for Gist-Forming w/Alexander
- EuroVis '16: TextDNA: Visualizing Word Usage with Configurable Colorfields w/Szafir et al.
- EuroVis '16: Visualizing Co-occurrence of Events in Populations of Viral Genome Sequences w/Sarikaya et al.
- Journal of Vision '16: Four Types of Ensemble Encoding in Data Visualizations Szafir et al.