Amy Zhang

PhD Candidate

Critical Visualization, Visual Learning & Reasoning

 Team Garrison

I'm a scientifically-minded illustrator, designer, and visualization researcher. I contribute to projects that foster an appreciation and understanding of science within the VisGroup at the University of Bergen and VISABLI research network at the University of Toronto. Specifically, I am interested in the sociotechnical contexts of visualization as well as investigating visual representations as tools for learning and reasoning.

Prior to my PhD, I trained as a medical illustrator at the MSc Biomedical Communications program at the University of Toronto. After graduation, I worked as a researcher at the Science Visualization Lab, studying the use of visuals in undergraduate biology education. As well, I practiced as a policy analyst and designer within the Knowledge Translation division at the Public Health Agency of Canada. You can view a selection of my work at www.amykzhang.com.

Publications

2025

    [PDF] [DOI] [Bibtex] 
    @article{zhang2025deconstruct,
title={Deconstructing Implicit Beliefs in Visual Data Journalism: Unstable Meanings Behind Data as Truth & Design for Insight},
author={Zhang, Ke Er Amy and Jenkinson, Jodie and Garrison, Laura},
journal={arXiv, IEEE Transactions on Visualization and Computer Graphics--in press},
year={2025},
numpages={11},
publisher={arXiv},
doi = {10.48550/arXiv.2507.12377},
abstract={We conduct a deconstructive reading of a qualitative interview study with 17 visual data journalists from newsrooms across the globe. We borrow a deconstruction approach from literary critique to explore the instability of meaning in language and reveal implicit beliefs in words and ideas. Through our analysis we surface two sets of opposing implicit beliefs in visual data journalism: objectivity/subjectivity and humanism/mechanism. We contextualize these beliefs through a genealogical analysis, which brings deconstruction theory into practice by providing a historic backdrop for these opposing perspectives. Our analysis shows that these beliefs held within visual data journalism are not self-enclosed but rather a product of external societal forces and paradigm shifts over time. Through this work, we demonstrate how thinking with critical theories such as deconstruction and genealogy can reframe "success" in visual data storytelling and diversify visualization research outcomes. These efforts push the ways in which we as researchers produce domain knowledge to examine the sociotechnical issues of today's values towards datafication and data visualization. All supplemental materials for this work are available at osf.io/5fr48.},
pdf = {pdfs/zhang2025deconstruct.pdf},
images = {images/zhang2025deconstruct.png},
thumbnails = {images/zhang2025deconstruct_thumb.png},
project = {VIDI},
git={https://osf.io/5fr48/}
}
    [PDF] [Bibtex] 
    @inproceedings{alhazwani2025datahum,
author = {Al-Hazwani, Ibrahim and Zhang, Ke Er Amy and Garrison, Laura and Bernard, J{\"u}rgen},
title = {Data Humanism decoded: A characterization of its principles to bridge
data visualization researchers and practitioners},
booktitle = {Proceedings of IEEE VIS 2025 (Short Papers)--in press"},
year = {2025},
numpages = {5},
publisher = {IEEE Computer Society},
address = {Los Alamitos},
abstract = {Data Humanism is a human-centered design approach that emphasizes the personal, contextual, and imperfect nature of data. Despite its growing influence among practitioners, the 13 principles outlined in Giorgia Lupi’s visual manifesto remain loosely defined in research contexts, creating a gap between design practice and systematic application. Through a mixed-methods approach, including a systematic literature review, multimedia analysis, and expert interviews, we present a characterization of Data Humanism principles for visualization researchers. Our characterization provides concrete definitions that maintain interpretive flexibility in operationalizing design choices. We validate our work through direct consultation with Lupi. Moreover, we leverage the characterization to decode a visualization work, mapping Data Humanism principles to specific visual design choices. Our work creates a common language for human-centered visualization, bridging the gap between practice and research for future applications and evaluations.},
pdf = {pdfs/alhazwani2025datahum.pdf},
images = {images/alhazwani2025datahum.png},
thumbnails = {images/alhazwani2025datahum_thumb.png},
}
    [PDF] [Bibtex] 
    @inproceedings{zhang2025stories,
author = {Zhang, Ke Er Amy and Garrison, Laura},
title = {Modern snapshots in the crafting of a medical illustration},
booktitle = {Proceedings of CHI '25 Workshop "How do design stories work? Exploring narrative forms of knowledge in HCI"},
year = {2025},
numpages = {3},
abstract = {The time-honored practice of medical illustration and visualization, has, like nearly all other disciplines, seen changes in its tooling and development pipeline in step with technological and societal developments. At its core, however, medical visualization remains a discipline focused on telling stories about biology and medicine. The story we tell in this work assumes a more distant vantage point to tell a story about the biomedical storytellers themselves. Our story peers over the shoulders of two medical illustrators in the middle of a project to illustrate a procedure in one of the small blood vessels around the heart, and through the medium of an online chat explores the dialogue, tensions, and goals of such projects in the digital age. We adopt the two-column format of the CHI template, as it is more reminiscent of the width of our usual messaging windows while working. The second part of our submission reflects on these tensions and modes of storytelling from an HCI and Visualization-situated perspective.},
pdf = {pdfs/zhang2025stories.pdf},
images = {images/zhang2025stories.png},
thumbnails = {images/zhang2025stories.png},
project = {VIDI}
}

2024

    [PDF] [Bibtex] 
    @MISC{zhang2024ManhattanWheel,
booktitle = {Eurographics Workshop on Visual Computing for Biology and Medicine (Posters)},
title = {{The Manhattan Wheel: A Radial Visualization Story for Genome-wide Association Study Data}},
author = {Zhang, Ke Er and Vaudel, Marc and Garrison, Laura A.},
year = {2024},
howpublished = {Poster presented at VCBM 2024.},
publisher = {The Eurographics Association},
abstract = {Genome-wide association studies (GWAS) are critical to identifying genetic variations associated with a particular trait or disease. It is important to cultivate an awareness of GWAS in the general public as members of this group are key participants of these studies. However, low genetic data literacy and trust in the sharing of genetic data pose challenges to learning and engaging with GWAS concepts. In this design study, we explore design strategies for the public communication of GWAS data. As part of this study, we present an interactive visual prototype that explores the use of narrative structure, linked visualizations through scrollytelling, and plain language to onboard and communicate genetic concepts to a GWAS-naive audience.},
pdf = {pdfs/KEZHANG_VCBM2024_Poster_ManhattanWheel.pdf},
images = {images/zhangManhattanWheel.png},
thumbnails = {images/zhangManhattanWheelthumb.png},
project = {VIDI},
git={https://github.com/amykzhang/manhattan-wheel}
}
    [PDF] [DOI] [Bibtex] 
    @article{zhang2024toolkit,
title={The Visual Science Communication Toolkit: Responding to the Need for Visual Science Communication Training in Undergraduate Life Sciences Education},
author={Zhang, Ke Er and Jenkinson, Jodie},
journal={Education Sciences},
year={2024},
volume={14},
number={3},
pages={296},
publisher={MDPI},
abstract={Visual representations are essential to scientific research and teaching, playing a role in conceptual understanding, knowledge generation, and the communication of discovery and change. Undergraduate students are expected to interpret, use, and create visual representations so they can make their thinking explicit when engaging in discourse with the scientific community. Despite the importance of visualization in the biosciences, students often learn visualization skills in an ad hoc fashion without a clear framework. We used a mixed-methods sequential explanatory study design to explore and assess the pedagogical needs of undergraduate biology students (n = 53), instructors (n = 13), and teaching assistants (n = 8) in visual science communication education. Key themes were identified using inductive grounded theory methods. We found that extrinsic motivations, namely time, financial resources, and grading practices, contribute to a lack of guidance, support, and structure as well as ambiguous expectations and standards perceived by students and instructors. Biology and science visualization instructors cite visual communication assessments as a way of developing and evaluating students’ higher-order thinking skills in addition to their communication competencies. An output of this research, the development of a learning module, the Visual Science Communication Toolkit, is discussed along with design considerations for developing resources for visual science communication education.},
pdf = {pdfs/zhang2024toolkit.pdf},
images = {images/zhang2024toolkit.png},
thumbnails = {images/zhang2024toolkitthumb.png},
issn={2227-7102},
doi={10.3390/educsci14030296},
url={https://www.mdpi.com/2227-7102/14/3/296}
}

2023

    [PDF] [DOI] [Bibtex] 
    @book{zhang2023framework,
title={A Framework for the Design, Production, and Evaluation of Scientific Visualizations},
author={Zhang, Ke Er and Saharan, Shehryar and McGill, Ga{\"e}l and Jenkinson, Jodie},
editor={Shapiro, Leonard},
booktitle={Graphic Medicine, Humanizing Healthcare and Novel Approaches in Anatomical Education},
pages={131--162},
year={2023},
publisher={Springer Nature Switzerland},
address={Cham},
abstract={Visualizations play a critical role in discovering, understanding, interpreting, synthesizing, and communicating scientific knowledge. Effective scientific visualization requires careful attention to a number of factors, in particular, a faithful translation of scientific evidence, understanding of the communication needs of the target audience, and skillful application of visualization design principles. As a result, science visualization projects require a team of contributors with specialized knowledge and technical expertise. Regardless of team size and structure, a clear definition and appreciation of the design process as well as an understanding of the responsibilities of each contributor are imperative to the success of a project. Gaps in understanding often result in conflict between visualizers and stakeholders, compromising the quality of the scientific visualization. Although many companies have developed their own process through trial and error over years of experience, to date, there is no formalized framework for scientific visualization that details the steps of the process and the contributions of each individual. Informed by our examination of case studies, frameworks, and our collective experience as practitioners, we propose a framework tailored to the design, production, and evaluation of scientific visualization that aims to support practitioners in meeting their objectives and facilitating conversations that allow others to better understand the impact of the design process on the final product. We explore underlying drivers of decision-making within the visualization design space, describe the activities and outputs that impact decisions made about the final visualization, and discuss potential applications and limitations of this framework in practice.},
pdf = {pdfs/zhang2023framework.pdf},
images = {images/zhang2023framework.png},
thumbnails = {images/zhang2023frameworkthumb.png},
isbn={978-3-031-39035-7},
doi={10.1007/978-3-031-39035-7_7},
url={https://doi.org/10.1007/978-3-031-39035-7_7}
}