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<!DOCTYPE html>
<div id="ItrActMapModal" class="modal fade" role="dialog">
<div class="modal-dialog">
<div class="modal-content">
<div class="modal-header">
<button type="button" class="close" data-dismiss="modal">×</button>
<h4 class="modal-title">Interactive Maps</h4>
</div>
<div class="modal-body">
<span class="affiliation">Hobby</span>
<span class="timeperiod">2014, 2016</span>
<figure>
<figcaption>Watersheds</figcaption>
<img class="img-responsive" src="images/water_zoom.png" alt="Map showing watersheds of eastern Asia">
</figure>
<p>
<a href="projects/interactive_maps">Project Index</a>
</p>
<p>
As just a fun project, I like to create interative visualizations of real data.
This started as a project for <a href="http://homes.cs.washington.edu/~jheer/">Jeff Heer</a>'s Data Visualization class with project partner <a href="http://homes.cs.washington.edu/~clzhang/">Congle Zhang</a>, I've improved the code to add modularity and have interactive maps of both language families and water basins.
The water basin tree demonstrates how water resources transcend national boundaries, sometimes unexpectedly.
The language tree uses unconfirmed groupings, but it is interesting to explore the taxonomic relations of languages and their geographic distributions.
The maps are SVG hand-drawn by me (Conrad) based on raster images. My javascript framework adds interactivity and hierarchy.
This is my current hobby project and I'd love more input so I could find more uses of the interactive visualization.
</p>
<p>
You can make comments or access the code on <a href="https://github.com/conradarcturus/interactive_maps">git <img src='images/icons/github.png' style="height:20px; padding:0px"/></a>
</p>
<figure>
<figcaption>Language Families</figcaption>
<img class="img-responsive" src="images/language_zoom.png">
</figure>
</div>
</div>
</div>
</div>
<div id="TwitterCSSModal" class="modal fade" role="dialog">
<div class="modal-dialog">
<div class="modal-content">
<div class="modal-header">
<button type="button" class="close" data-dismiss="modal">×</button>
<h4 class="modal-title">Identifying Rumors in Crisis Social Media</h4>
</div>
<div class="modal-body">
<span class="affiliation">Twitter</span>
<span class="timeperiod">2016</span>
<img class="img-responsive" src="images/twitterbird_RGB.png">
<p>
I interned in the Product Safety Systems team @ Twitter. I helped improve the service that catches spam and harassment by optimizing the database requests. At the scale of every single tweet, that saved the company quite a bit of money.
</p>
</div>
<!--<div class="modal-footer">-->
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</div>
</div>
</div>
<div id="MisInfoSNAModal" class="modal fade" role="dialog">
<div class="modal-dialog">
<div class="modal-content">
<div class="modal-header">
<button type="button" class="close" data-dismiss="modal">×</button>
<h4 class="modal-title">Examining Misinformation Propagating on Social Networks</h4>
</div>
<div class="modal-body">
<span class="affiliation">University of Washington</span>
<span class="timeperiod">2015 - 2016</span>
<img class="img-responsive" src="images/AConradNied_MisinfoSNA_full_20160819.png">
<p>
I examined the flow of misinformation during crisis events, particularly the Umpqua CC Shooting and Paris Attacks in 2015 Q4. While I believe these events happened and were very tragic, I found many users resisting mainstream media narratives, using evidence-based reasoning to deny the events. I examined the sources of this evidence & the social activity driving the spread of kinds of information like this. This led me to uncover many fake accounts spreading this information as well as network dynamics that we did not expect. I'd say more but we hope to publish findings from this project.
</p>
</div>
<!--<div class="modal-footer">-->
<!--<button type="button" class="btn btn-default" data-dismiss="modal">Close</button>-->
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</div>
</div>
</div>
<div id="MisInfoInfraModal" class="modal fade" role="dialog">
<div class="modal-dialog">
<div class="modal-content">
<div class="modal-header">
<button type="button" class="close" data-dismiss="modal">×</button>
<h4 class="modal-title">Social Media Capture Infrastructure</h4>
</div>
<div class="modal-body">
<span class="affiliation">University of Washington</span>
<span class="timeperiod">2015 - 2016</span>
<img class="img-responsive" src="images/AConradNied_TwitterInfra_20151205.png">
<p>
Over 12 researchers (2 PIs, 4 grads, and 6+ undergrads) work on different facets identifying and analyzing rumors in social media.
This creates a need for technical infrastructure to gather social media posts and automatically provide statistics and interactive support for their analysis.
Thereby, Conrad has made a series of webpages to 1) show dataset availability 2) provide on-demand timeseries visualization 3) report on the accuracy & trends of manual annotations and 4) report frequent terms and patterns in the sets of tweets.
This work required migranting the data into a relational database, building Python utilities to transfer data around, interfacing with MySQL, MongoDB, Google Docs as well as other rest APIs.
The front-end is built in javascript and php, using D3 and JQuery and smaller libraries to drive particular user patterns.
</p>
<p>
You can access the code on <a href="https://github.com/emCOMP/visualization">
git <img src='images/icons/github.png' style="height:20px; padding:0px"/></a>
</p>
<p>
The website can be found at <a href="http://boston.somelab.net/analysis">boston.somelab.net/analysis</a>. Unfortunately we do not support external authentication yet.
</p>
</div>
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</div>
</div>
<div id="ValueCommModal" class="modal fade" role="dialog">
<div class="modal-dialog">
<div class="modal-content">
<div class="modal-header">
<button type="button" class="close" data-dismiss="modal">×</button>
<h4 class="modal-title">Data Mining Personal Values to Improve Online Deliberation</h4>
</div>
<div class="modal-body">
<span class="affiliation">University of Washington</span>
<span class="timeperiod">2014 - 2015</span>
<img class="img-responsive" src="images/AConradNied_ValueComm_LVG_2015Q1.png">
<p>
<a href="papers/AConradNied_ValueComm_poster_20141025.pdf">Poster</a>
<a href="papers/AConradNied_ValueComm_writeup_20150422.pdf">Writeup 2015Q1</a>
</p>
<p>
<i>On hiatus, would like to resume sometime but project does not have funding support.</i>
</p>
<p>
Two people with the same facts may have very different conclusions if they have different values, experiences, and needs.
I'm working on a project using natural language processing to identify the values used by conversants in online deliberation.
The goal of this task is to inform social media tools to steer online debate towards constructive common ground.
</p>
<p>
See my <a href="papers/AConradNied_ValueComm_writeup_20150422.pdf">writeup</a> from a small-scope project examining values in debates on the Living Voters Guide.
</p>
</div>
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</div>
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<div class="modal-dialog">
<div class="modal-content">
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<button type="button" class="close" data-dismiss="modal">×</button>
<h4 class="modal-title">Visual Feedback in Online Communication</h4>
</div>
<div class="modal-body">
<span class="affiliation">University of Washington</span>
<span class="timeperiod">2014 - 2015</span>
<img class="img-responsive" src="images/AConradNied_Verbalucce_2015Q3.png">
<p>
<a href="papers/AConradNied_Verbalucce_poster_20151020.pdf">Poster</a>
</p>
<p>
Verbalucce is a system prototyped @ Intel that gives communication feedback in emails.
I joined the project to conduct a field study of the system and analyze its effects on email composition.
Qualitatively, participants liked the granular feedback and were more reflective when writing emails with the feedback.
See the poster for an overview of the system and summary of results.
</p>
<p>
My main responsibilities were updating the code base and administering a field study on the tool.
Margaret Morris and <a href="http://www.adrienneslaughter.com/">Adrienne Andrew Slaughter</a> originally worked on the tool.
<a href="http://www.lucascolusso.com">Lucas Colusso</a> helped us design the aesthetic of the latest version.
Gary Hsieh and Sean Munson advised me during the study.
</p>
</div>
</div>
</div>
</div>
<div id="Google2014Modal" class="modal fade" role="dialog">
<div class="modal-dialog">
<div class="modal-content">
<div class="modal-header">
<button type="button" class="close" data-dismiss="modal">×</button>
<h4 class="modal-title">Mobile Input Research</h4>
</div>
<div class="modal-body">
<span class="affiliation">Google</span>
<span class="timeperiod">2014</span>
<img class="img-responsive" src="images/AConradNied_Google2014_fig_20141025.png">
<p>I interned with <a href="http://research.google.com/pubs/TomOuyang.html">Tom Ouyang</a> and <a href="http://www.shuminzhai.com/">Shumin Zhai</a> in the Mobile Input Research Group.
The project involved providing users new methods to interact with the keyboard.</p>
</div>
</div>
</div>
</div>
<div id="PrefabModal" class="modal fade" role="dialog">
<div class="modal-dialog">
<div class="modal-content">
<div class="modal-header">
<button type="button" class="close" data-dismiss="modal">×</button>
<h4 class="modal-title">Prefab: Reverse Engineering User Interfaces to Insert New Features</h4>
</div>
<div class="modal-body">
<span class="affiliation">University of Washington</span>
<span class="timeperiod">2014</span>
<img class="img-responsive" src="images/AConradNied_Prefab_UIST_fig_20141025.png">
<p>
<a href="papers/AConradNied_Prefab_UIST_20141025.pdf">Paper</a>
<a href="https://www.youtube.com/watch?v=kxu7cyrBfjM">Video</a>
</p>
<p>
I worked for two quarters with <a href="http://homes.cs.washington.edu/~jfogarty/">James Fogarty</a> and <a href="http://homes.cs.washington.edu/~mdixon/">Morgan Dixon</a> on their project Prefab.
Prefab is a C# program that interprets interfaces and can reconfigure how they are used.
I helped to setup and run a user study on Prefab.
I also investigated the overlap between Prefab's ability to reverse engineer interfaces and Android layout hierarchies for accessibility.
</p>
</div>
</div>
</div>
</div>
<div id="GPSModal" class="modal fade" role="dialog">
<div class="modal-dialog">
<div class="modal-content">
<div class="modal-header">
<button type="button" class="close" data-dismiss="modal">×</button>
<h4 class="modal-title">Massachusetts General Hospital</h4>
</div>
<div class="modal-body">
<span class="affiliation">Massachusetts General Hospital</span>
<span class="timeperiod">2011 - 2013</span>
<img class="img-responsive" src="images/AConradNied_GPS_fig_20140106.png">
<p>
<a href="papers/AConradNied_GPS_BiomagPoster_2012.pdf">Poster</a>
<a href="https://martinos.org/software/gps">Website</a>
</p>
<p>
While processing brain imaging data, I built a graphical user interface to speed up the analysis.
I programmed it in Matlab and it plugs into the Freesurfer & Martinos MNE software as well as provides new tools to interact with the data.
One utility assists in identifying clusters of neural activity on the cortical surface.
Another program predicts Granger-causality between these regions and generates visualizations for publication.
</p>
</div>
</div>
</div>
</div>
<div id="OneBusAwayModal" class="modal fade" role="dialog">
<div class="modal-dialog">
<div class="modal-content">
<div class="modal-header">
<button type="button" class="close" data-dismiss="modal">×</button>
<h4 class="modal-title">Predicting Bus Arrivals Using One Bus Away Real-Time Data</h4>
</div>
<div class="modal-body">
<span class="affiliation">University of Washington</span>
<span class="timeperiod">2013</span>
<img class="img-responsive" src="images/AConradNied_OneBusAway_Image.png">
<p><a href="papers/AConradNied_OneBusAway_Writeup_20131209.pdf">Paper</a></p>
<p>
Class project for <a href="https://courses.cs.washington.edu/courses/cse546/13au/index.html">Machine Learning</a>.
<a href="http://homes.cs.washington.edu/~cmbaker/">Catie Baker</a> and I used an array of machine learning techniques to predict bus arrival times.
</p>
<p>
<i>Abstract:</i> Providing real-time bus arrival times can enhance the experience of riders using public transit, but errors in the predictions can cause a decrease in ridership.
Using data collected from a local transit agency, we created models to predict arrival times using K-Nearest Neighbors and Kernel Regression and seven sets of features.
The best feature set had a RMSE of 34 seconds, a large improvement over the baseline of always predicting on-time arrivals, which had an RMSE of 99 seconds.
</p>
</div>
</div>
</div>
</div>
<div id="PopAlgoModal" class="modal fade" role="dialog">
<div class="modal-dialog">
<div class="modal-content">
<div class="modal-header">
<button type="button" class="close" data-dismiss="modal">×</button>
<h4 class="modal-title">Visual Population Algorithms</h4>
</div>
<div class="modal-body">
<span class="affiliation">Hobby Project</span>
<span class="timeperiod">2012 - Present</span>
<img class="img-responsive" src="images/AConradNied_PopAlgo_fig_20141101.png">
<p><a href="https://www.youtube.com/watch?v=NvQtIusaEqM&list=PLOzUGhfPlMJzd8wCJ_eWUoQwP1fO5LN6x">Videos</a></p>
<p>
In my spare time, I've continued my work on mapping influence, but using new heuristics and making new visuals.
The focus of these particular algorithms is to divide the world into informed countries.
The first video below explores what happens when you combine points of the world in order of highest population.
This forms countries based on spatial continuity of people - which usually is realistic because people move within high population zones and form communities.
Other videos show heuristics attempting to divide the world into even population zones.
There are a lot more videos I didn't get a chance to make in this project too that I may revisit some day.
</p>
</div>
</div>
</div>
</div>
<div id="PTCModal" class="modal fade" role="dialog">
<div class="modal-dialog">
<div class="modal-content">
<div class="modal-header">
<button type="button" class="close" data-dismiss="modal">×</button>
<h4 class="modal-title">Neuroimaging of Phonotactic Constraints</h4>
</div>
<div class="modal-body">
<span class="affiliation">Massachusetts General Hospital</span>
<span class="timeperiod">2011 - 2013</span>
<img class="img-responsive" src="images/AConradNied_PTC_PLoSONE_fig_20140121.png">
<p>
<a href="papers/AConradNied_PTC_PLoSONE_20140121.pdf">Paper</a>
</p>
<p>
<a href="http://www.massgeneral.org/neurology/researcher_profiles/gow_david.aspx">David Gow</a>, <a href="http://www.massgeneral.org/neurology/researcher_profiles/caplan_david.aspx">David Caplan</a>, and I examined linguistic neural connectivity using brain imaging technology.
We scanned subjects in MRI and MEG scanning machines.
Subjects sat in the MEG machine and discriminated audio phonological irregularities (/sl/ and /ʃr/ which are legal in English and /sr/ and /ʃl/ which are not) or discriminated between English words and nonwords.
The MEG machine recorded electrical and magnetic activity coming from their brain.
We then took structural MRIs and created 3D surface models of the subjects gray matter, white matter, skull and scalp with <a href="http://surfer.nmr.mgh.harvard.edu/">Freesurfer</a>.
Their MEG/EEG activity is mapped on to the cortex using <a href="http://martinos.org/mne/stable/index.html">Minimum Norm Estimates Software</a>.
We used a Kalman-Granger technique to infer the causal interaction between regions of the brain.
My primarily responsibilities were to produce and conduct the experiments, then write and run data analysis routines to interpret the neural data.
</p>
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<h4 class="modal-title">Self Organizing Maps to Model Phonology in the Brain</h4>
</div>
<div class="modal-body">
<span class="affiliation">Boston University</span>
<span class="timeperiod">2011</span>
<img class="img-responsive" src="images/AConradNied_PhonSOM_20110512.png">
<p>
I worked for a year at the Boston University Sargent College <a href="http://www.bu.edu/speechlab/">Speech Lab</a>.
The lab's most ambitious project is DIVA, a neural network that learns and produces speech sounds.
My project with DIVA was to investigate how a self-organizing map could automatically classify speech sound features into phonemes using a self-organizing map.
My results demonstrated possible ways that a neural network could adapt to phonemes.
</p>
</div>
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</div>
<div id="InfMapModal" class="modal fade" role="dialog">
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<h4 class="modal-title">Simulating Influence on a Global Scale</h4>
</div>
<div class="modal-body">
<span class="affiliation">Boston University</span>
<span class="timeperiod">2010</span>
<img class="img-responsive" src="images/AConradNied_InfMap_fig_20141103.png">
<p>
<a href="papers/AConradNied_InfMap_Writeup_2010.pdf">Paper</a>
<a href="https://www.youtube.com/watch?v=dkxP1LFREXg&list=PLD759E8906A91964F">Videos</a>
</p>
<p>
For my Data Mining Seminar with <a href="http://www.cs.bu.edu/~evimaria/">Evimaria Terzi</a>, I built a series of programs that simulated the spread of influential artifacts on a map.
The program was generalized to simulate viruses, the Roman Empire, language or general culture evolving, and genetic drift.
The heuristic was pretty simple but demonstrative of global-scale interactions.
</p>
</div>
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<h4 class="modal-title">Data Mining Personal Values to Improve Online Deliberation</h4>
</div>
<div class="modal-body">
<span class="affiliation">University of Washington</span>
<span class="timeperiod">2014 - Present</span>
<!--<img class="img-responsive" src="images/AConradNied_BUCS440.png">-->
<!--<p><a href="projects/BUCS440/index.html">Demos</a></p>-->
<p>
I did a series of projects with my classmates in our artificial intelligence class.
They included an interactive Rock Paper Scissors game with the computer and hand gesture recognition and a neural network number classifier.
I don't have the files at hand but when I do I will upload them to the website.
</p>
</div>
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</div>
</div>
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<h4 class="modal-title">Baking: Cookies, Cupcakes, Cronuts, Banana Bread</h4>
</div>
<div class="modal-body">
<!--<span class="affiliation"></span>-->
<!--<span class="timeperiod">2014 - Present</span>-->
<img class="img-responsive" src="images/AConradNied_Cookies_Rainbow_20130608.jpg">
<p>I bake often, at least once a week. Baked goods make everyone happy :)</p>
<img width="150px" src="images/examples/AConradNied_Cookies_Snickerdoodle_20131127.jpg" />
<img width="150px" src="images/examples/AConradNied_Cronuts_fig1_20131011.jpg" />
<img width="150px" src="images/examples/AConradNied_Cupcakes_PBChocBanana_20140530.jpg" />
<img width="150px" src="images/examples/AConradNied_BananaBread_20090802.jpg" />
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<h4 class="modal-title">Art: Sculpture, Crafts, Painting</h4>
</div>
<div class="modal-body">
<img class="img-responsive" src="images/AConradNied_Frabjous_Paper_20120117.jpg">
<p>Frabjous Sculpture: <a href="http://georgehart.com/sculpture/frabjous.html">Original Design</a></p>
<p>I like to express myself with creative, hands on activities.</p>
<img height="150px" src="images/examples/AConradNied_Frabjous_Mono_20101028.jpg" />
<img height="150px" src="images/examples/AConradNied_Flowers_20110220.jpg" />
<img height="150px" src="images/examples/AConradNied_Painting_20121024.jpg" />
<img height="120px" src="images/examples/AConradNied_Monkeys_20101108.jpg" />
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<h4 class="modal-title">My Cat, Simba Nied</h4>
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<img class="img-responsive" src="images/AConradNied_Simba_Window_20130125.jpg">
<h4>American Domestic, Medium Hair, Tuxedo Colored</h4>
<p><a href="https://www.youtube.com/watch?v=PjocWFPFSZQ&list=PL77CBE8217A144307">Videos</a></p>
<p>He's friendly and adorable.</p>
<img width="120px" src="images/examples/AConradNied_Simba_20140609.jpg" />
<img width="120px" src="images/examples/AConradNied_SimbaConrad_20111216.jpg" />
<img width="120px" src="images/examples/AConradNied_SimbaCthulhu_20120805.jpg" />
<img width="120px" src="images/examples/AConradNied_Simba_Settlers_20110814.jpg" />
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<h4 class="modal-title">Dancing</h4>
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<p>Salsa, Merengue, Cha Cha, Rumba, Fusion</p>
<p>¿Te gusta bailar?</p>
<a href="https://flic.kr/p/riNrKs">CHI 2015 Spontaneous Salsa</a>
<img width="180px" src="images/examples/AConradNied_Dancing_Salsa_Stephanie_201306.jpg" />
<img width="180px" src="images/AConradNied_Dancing_Salsa_Stephanie_2_201306.jpg" />
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