Curriculum Vitae

About Me

I am a Postdoctoral Researcher in the Complex Systems Research group at Autodesk Research. I received my Ph.D at the Department of Computer Science, University of Toronto in July 2015, where my supervisor was Dr. Ravin Balakrishnan. I was affiliated with the Dynamic Graphic Project (DGP) lab during my Ph.D study. Before coming to University of Toronto, I received my B.Eng (with honour) at the College of Computer Science, Zhejiang University in June 2009, where I was also affiliated with the Chu Kochen Honors College.

My research interests, broadly, are Information Visualization and Human Computer Interaction. My PhD thesis is titled with Interactive Visual Data Exploration: A Multi-Focus Approach. Specifically, my work falls in topics about designing novel interactive visualization systems supporting multi-focus visual exploration of complicated real-world datasets, developing new methods for information seeking and navigation on web, creating interaction techniques for mobile phones, and quantitatively modeling user performance on touch screens.

Publications

Conference Full Papers and Journal Articles

Conference Short Papers

Posters, Work-in-Progress, and others

[O3]

Ji Wang, Jian Zhao, Sheng Guo, Chris North.
Clustered Layout Word Cloud for User Generated Review.
Yelp Dataset Challenge (Grand Prize Winner), 2013.

[O2]

Jian Zhao.
A Particle Filter Based Approach of Visualizing Time-varying Volume.
LDAV'12 IEEE Symposium on Large-Scale Data Analysis and Visualization, 2012.
Abstract Paper

Abstract: Extracting and presenting essential information of time-varying volumetric data is critical in many fields of sciences. This paper introduces a novel approach of identifying important aspects of the dataset under the particle filter framework in computer vision. With the view of time-varying volumes as dynamic voxels moving along time, an algorithm for computing the 3D voxel transition curves is derived. Based on the curves which characterize the local data temporal behavior, this paper also introduces several post-processing techniques to visualize important features such as curve clusters by k-means and curve variations computed from curve gradients.

[O1]

Jian Zhao, R. William Soukoreff, Ravin Balakrishnan.
A Model of Multi-touch Manipulation.
GRAND'11 Proceedings of the 2nd annual Grand Conference, 2011.
Abstract Paper

Abstract: As touch-sensitive devices become increasingly popular, fundamentally understanding the human performances of multi-touch gestures is critical. However, there is currently no mathematical model for interpreting such gestures. In this paper, a novel model of multi-touch interaction is derived by combining the Mahalanobis distance metric and Fitts' law. The model describes the time required to complete an object manipulation task that includes translocation, rotation, and scaling. Empirical data is reported that validates the new model (R2>0.9). Linear relationship between the difficulty and time elapsed is revealed indicating that the model can provide guidelines for interface designers for empirically comparing gestures and devices.

PhD Thesis

[T1]

Jian Zhao.
Interactive Visual Data Exploration: A Multi-Focus Approach.
Department of Computer Science, University of Tornoto, 2015.
Abstract Paper Bibtex

Abstract: Recently, the amount of digital information available in the world has been growing at a tremendous rate. This huge, heterogeneous, and complicated data that we are continuously generating could be an incredible resource for us to seek insights and make informed decisions. For this knowledge extraction to be efficient, visual exploration of data is demanded in addition to fully automatic methods, because visual exploration can integrate the creativity, flexibility, and general experience of the human user into the sense-making process through interaction and visualization techniques.

Due to the scale and complexity of data, robust conclusions are usually formed by coordinating many sub-regions in an information space, which leads to the approach of multi-focus visual exploration that allows browsing different data segments with multiple views and perspectives simultaneously. While prior research has proposed a myriad of information visualization techniques, there still lacks comprehensive understanding about how visual exploration can be facilitated by multi-focus interactive visualizations. This dissertation investigates issues and techniques of multi-focus visual exploration through five design studies, touching various types of data in a range of application domains.

The first two design studies address the exploration of numerical data values. KronoMiner presents a multi-purpose visual tool for exploring time-series based on a dynamic radial hierarchy; and the ChronoLenses system supports exploratory visual analysis of time-series by allowing users to progressively construct advanced analytical pipelines. The third design study focuses on the exploration of logical data structures, and presents DAViewer that facilitates computational linguistics researchers to explore and compare rhetorical trees. The last two design studies consider the exploration of heterogeneous data attributes (or facets). TimeSlice facilitates the browsing of multi-faceted events timelines by organizing visual queries in a tree structure; and PivotSlice aids the mining of relationships in multi-attributed networks through a dynamic subdivision of data with customized semantics.

This dissertation ends with critical reflections and generalizations of the experiences obtained from the case studies. High-level design considerations, conceptual models, and visualization theories are distilled to inform researchers and practitioners in information visualization for devising effective multi-focus visual interfaces.

See my other interesting unpublished projects!

Professional Experiences

Postdoctoral Researcher, Autodesk Research, Toronto, ON, 2015.7-
Graduate Research Assistant, University of Toronto, Toronto, ON, 2009.9-2015.7
Research Intern, Microsoft Research, Redmond, WA, 2014.12-2015.3
Research Intern, Adobe Research, San Francisco, CA, 2014.6-2014.9
Research Intern, IBM Almaden Research Center, San Jose, CA, 2013.6-2013.9
Research Intern, Microsoft Research, Redmond, WA, 2011.6-2011.9
Visiting Student, North Carolina State University, Raleigh, NC, 2008.6-2008.8

Major Awards

Patents

[P4]

Jian Zhao, Michael Glueck, Azam Khan.
Node Centric Analysis of Dynamic Networks.. Filed in 2016.

[P3]

Mira Dontcheva, Jian Zhao, Aaron Hertzmann, Alan Wilson, Zhicheng Liu.
Providing Visualizations of Event Sequence Data. Filed in 2015.

[P2]

Liang Gou, Fei Wang, Jian Zhao, Michelle Zhou.
Personal Emotion State Monitoring from Social Media. US Patent 20150213002 A1, 2015.

[P1]

Jian Zhao, Steven Drucker, Danyel Fisher, Donald Brinkman.
Relational Rendering of Multi-Faceted Data. US Patent 20130194294 A1, 2013.

Teaching Assistantships

Talks

Public Talks

Conference Presentations

Services

Program Committee

Conference Paper Reviewer

Journal Article Reviewer

Student Volunteer

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