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<!DOCTYPE html> | ||
<html> | ||
<head> | ||
<meta name="viewport" content="width=device-width, initial-scale=1" /> | ||
<link rel="stylesheet/less" type="text/css" href="styles/baseStyles.less"/> | ||
<script type="text/javascript" src="node_modules/less/dist/less.min.js" data-log-level="1"></script> | ||
<script type="text/javascript" src="node_modules/d3/dist/d3.min.js"></script> | ||
<script type="module" src="node_modules/uki/dist/uki.esm.js"></script> | ||
<script type="module" src="node_modules/@ukijs/ui/dist/uki-ui.esm.js"></script> | ||
<script type="module"> | ||
import CvController from './controllers/CvController/CvController.js'; | ||
window.controller = new CvController(); | ||
</script> | ||
</head> | ||
<body> | ||
<div class="CV flexbox-albatross"> | ||
<div class="column"> | ||
<div> | ||
<h1 style="white-space: nowrap">Alex Bigelow</h1> | ||
<div class="contactInfo"></div> | ||
</div> | ||
|
||
<h2>Experience</h2> | ||
<div class="experience"> | ||
<h5>Employment</h5> | ||
<head> | ||
<meta name="viewport" content="width=device-width, initial-scale=1" /> | ||
<link rel="stylesheet/less" type="text/css" href="styles/baseStyles.less" /> | ||
<script | ||
type="text/javascript" | ||
src="node_modules/less/dist/less.min.js" | ||
data-log-level="1" | ||
></script> | ||
<script | ||
type="text/javascript" | ||
src="node_modules/d3/dist/d3.min.js" | ||
></script> | ||
<script type="module" src="node_modules/uki/dist/uki.esm.js"></script> | ||
<script | ||
type="module" | ||
src="node_modules/@ukijs/ui/dist/uki-ui.esm.js" | ||
></script> | ||
<script type="module"> | ||
import CvController from './controllers/CvController/CvController.js'; | ||
window.controller = new CvController(); | ||
</script> | ||
</head> | ||
<body> | ||
<div class="CV flexbox-albatross"> | ||
<div class="column"> | ||
<h2> | ||
<span class="showInPrint hideInFullPrint">Selected</span> | ||
Publications | ||
</h2> | ||
<div class="pubchunk" data-type="theses"> | ||
<h5>Theses</h5> | ||
</div> | ||
<div class="pubchunk" data-type="preprints"> | ||
<h5>Preprints</h5> | ||
</div> | ||
<div class="pubchunk" data-type="papers"> | ||
<h5>Refereed Conference and Journal Papers</h5> | ||
</div> | ||
<div class="pubchunk" data-type="patents"> | ||
<h5>Patents</h5> | ||
</div> | ||
<div class="pubchunk hideInPrint showInFullPrint" data-type="abstracts"> | ||
<h5>Extended Abstracts</h5> | ||
</div> | ||
<div class="pubchunk hideInPrint showInFullPrint" data-type="posters"> | ||
<h5>Posters</h5> | ||
</div> | ||
</div> | ||
|
||
<div class="service"> | ||
<h5>Service</h5> | ||
</div> | ||
</div> | ||
<div class="column"> | ||
<div style="text-align: right;"> | ||
<h1 style="white-space: nowrap">Alex Bigelow</h1> | ||
<div class="contactInfo"></div> | ||
</div> | ||
|
||
<div class="column"> | ||
<h2>Education</h2> | ||
<div class="education"> | ||
<div class="entry"> | ||
<h6 class="title">PhD Computing: Data Management and Analysis</h6> | ||
<h6 class="date">2019</h6> | ||
<ul class="meta"> | ||
<li class="meta">University of Utah, Salt Lake City, UT</li> | ||
<li>Advisor: Dr. Miriah Meyer</li> | ||
</ul> | ||
<h2>Education</h2> | ||
<div class="education"> | ||
<div class="entry"> | ||
<h6 class="title">PhD Computing: Data Management and Analysis</h6> | ||
<h6 class="date">2019</h6> | ||
<ul class="meta"> | ||
<li class="meta">University of Utah, Salt Lake City, UT</li> | ||
<li>Advisor: Dr. Miriah Meyer</li> | ||
</ul> | ||
</div> | ||
<div class="entry"> | ||
<h6 class="title">B.S. Computer Science</h6> | ||
<h6 class="date">2012</h6> | ||
<ul class="meta"> | ||
<li class="meta">University of Utah, Salt Lake City, UT</li> | ||
</ul> | ||
</div> | ||
</div> | ||
<div class="entry"> | ||
<h6 class="title">B.S. Computer Science</h6> | ||
<h6 class="date">2012</h6> | ||
<ul class="meta"> | ||
<li class="meta">University of Utah, Salt Lake City, UT</li> | ||
</ul> | ||
|
||
<h2>Experience</h2> | ||
<div class="experience"> | ||
<h5>Employment</h5> | ||
</div> | ||
</div> | ||
|
||
<h2> | ||
<span class="showInPrint hideInFullPrint">Selected</span> | ||
Publications | ||
</h2> | ||
<div class="pubchunk" data-type="theses"> | ||
<h5>Theses</h5> | ||
</div> | ||
<div class="pubchunk" data-type="preprints"> | ||
<h5>Preprints</h5> | ||
</div> | ||
<div class="pubchunk" data-type="papers"> | ||
<h5>Refereed Conference and Journal Papers</h5> | ||
</div> | ||
<div class="pubchunk" data-type="patents"> | ||
<h5>Patents</h5> | ||
</div> | ||
<div class="pubchunk hideInPrint showInFullPrint" data-type="abstracts"> | ||
<h5>Extended Abstracts</h5> | ||
</div> | ||
<div class="pubchunk hideInPrint showInFullPrint" data-type="posters"> | ||
<h5>Posters</h5> | ||
<div class="service"> | ||
<h5>Service</h5> | ||
</div> | ||
</div> | ||
</div> | ||
</div> | ||
<div class="footer"> | ||
click roles or publication titles for more details | ||
</div> | ||
<div class="printHelper"> | ||
<!-- sneaky way to force the page to load fonts so that printing doesn't go blank--> | ||
<h1>printHelper</h1> | ||
<p>printHelper</p> | ||
</div> | ||
</body> | ||
<div class="footer">click roles or publication titles for more details</div> | ||
<div class="printHelper"> | ||
<!-- sneaky way to force the page to load fonts so that printing doesn't go blank--> | ||
<h1>printHelper</h1> | ||
<p>printHelper</p> | ||
</div> | ||
</body> | ||
</html> |
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--- | ||
title: Peer Reviewer | ||
start: 2015 | ||
stop: Present | ||
stop: 2024 | ||
service: true | ||
meta: | ||
- IEEE Information Visualization (2016-2021), Short Papers Program Committee (2020) | ||
- Eurovis VGTC Conference on Visualization (2016, 2020, 2021) | ||
- IEEE Conference on Visual Analytics Science and Technology (VAST) (2017, 2019-2021) | ||
- ACM CHI Conference on Human Factors in Computing Systems (2015, 2017-2020) | ||
- IEEE Transactions on Visualization and Computer Graphics (2019-2021) | ||
- IEEE VIS Conference, IEEE Transactions on Visualization and Computer Graphics (2016–2023), Short Papers Program Committee (2020) | ||
- Eurovis VGTC Conference on Visualization (2016, 2020–2022) | ||
- ACM CHI Conference on Human Factors in Computing Systems (2015, 2017–2022, 2024) | ||
- Workshop on Visualization in Practice (2017) | ||
- alt.VIS Workshop (2021) | ||
--- |
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--- | ||
title: Software Engineer | ||
start: 2021 | ||
stop: Present | ||
stop: 2024 | ||
meta: | ||
- Stardog Union | ||
- Arlington, VA | ||
reference: 'Mentors: Annee Barrett, Dr. Jason Rogers, Laura Firey Monroe, Dr. Michael Grove, Paul Ambro' | ||
--- | ||
|
||
Since starting at Stardog, I've helped mock up, implement, and deploy a visual network modeling tool, as well as contribute to the development of an existing IDE and network visualization tool. | ||
At Stardog, I helped design, implement ship, and maintain several user-facing applications (and associated libraries and Cloud UI), used by all of Stardog's customers and beyond. These included: | ||
|
||
- Stardog Designer, a graph modeling and mapping tool which was largely based off my Origraph research work | ||
- Stardog Explorer, a simple node-link diagram visualization tool with an accessible (yet very expressive) visual query building interface | ||
- Stardog Studio, an IDE for writing and editing queries, and managing Stardog databases and virtual graphs | ||
|
||
I was also heavily involved in the design and integration of Stardog Voicebox—a Large Language Model-powered chat assistant that translated natural language into SPARQL queries, executed the queries against data in Stardog, and summarized the results with an explainable UX with citations and a visual rendering of the query, that communicated exactly how the AI was able to find its answers. |
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@article{sakin2022traveler, | ||
title={Traveler: Navigating Task Parallel Traces for Performance Analysis}, | ||
author={Sakin, Sayef Azad and Bigelow, Alex and Tohid, R and Scully-Allison, Connor and Scheidegger, Carlos and Brandt, Steven R. and Taylor, Christopher and Huck, Kevin A. and Kaiser, Hartmut and Isaacs, Katherine E.}, | ||
journal={arXiv preprint arXiv:2208.00109}, | ||
year={2022} | ||
author={Sakin, Sayef Azad and Bigelow, Alex and Tohid, R. and Scully-Allison, Connor and Scheidegger, Carlos and Brandt, Steven R. and Taylor, Christopher and Huck, Kevin A. and Kaiser, Hartmut and Isaacs, Katherine E.}, | ||
journal={IEEE Transactions on Visualization and Computer Graphics}, | ||
title={Traveler: Navigating Task Parallel Traces for Performance Analysis}, | ||
year={2023}, | ||
volume={29}, | ||
number={1}, | ||
pages={788-797}, | ||
keywords={Task analysis;Performance analysis;Measurement;Data visualization;Codes;Navigation;High performance computing;software visualization;parallel computing;traces;performance analysis;event sequence visualization}, | ||
doi={10.1109/TVCG.2022.3209375} | ||
} |
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https://doi.org/10.1109/TVCG.2022.3209375 |
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Two people looking at the same dataset will create different mental models, prioritize different attributes, and connect with different visualizations. We seek to understand the space of data abstractions associated with mental models and how well people communicate their mental models when sketching. Data abstractions have a profound influence on the visualization design, yet it’s unclear how universal they may be when not initially influenced by a representation. We conducted a study about how people create their mental models from a dataset. Rather than presenting tabular data, we presented each participant with one of three datasets in paragraph form, to avoid biasing the data abstraction and mental model. We observed various mental models, data abstractions, and depictions from the same dataset, and how these concepts are influenced by communication and purpose-seeking. Our results have implications for visualization design, especially during the discovery and data collection phase. |
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@inproceedings{williams2023elephants, | ||
author = {Williams, Katy and Bigelow, Alex and Isaacs, Katherine E.}, | ||
title = {Data Abstraction Elephants: The Initial Diversity of Data Representations and Mental Models}, | ||
year = {2023}, | ||
isbn = {9781450394215}, | ||
publisher = {Association for Computing Machinery}, | ||
address = {New York, NY, USA}, | ||
url = {https://doi.org/10.1145/3544548.3580669}, | ||
doi = {10.1145/3544548.3580669}, | ||
abstract = {Two people looking at the same dataset will create different mental models, prioritize different attributes, and connect with different visualizations. We seek to understand the space of data abstractions associated with mental models and how well people communicate their mental models when sketching. Data abstractions have a profound influence on the visualization design, yet it’s unclear how universal they may be when not initially influenced by a representation. We conducted a study about how people create their mental models from a dataset. Rather than presenting tabular data, we presented each participant with one of three datasets in paragraph form, to avoid biasing the data abstraction and mental model. We observed various mental models, data abstractions, and depictions from the same dataset, and how these concepts are influenced by communication and purpose-seeking. Our results have implications for visualization design, especially during the discovery and data collection phase.}, | ||
booktitle = {Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems}, | ||
articleno = {803}, | ||
numpages = {24}, | ||
keywords = {Human-centered computing, data abstractions, visualization theory}, | ||
location = {, Hamburg, Germany, }, | ||
series = {CHI '23} | ||
} |
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https://doi.org/10.1145/3544548.3580669 |
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