Toward Identifying Values and Tensions in Designing a Historically-Sensitive Data Platform: A Case-Study on Urban Renewal

Urban renewal was a national initiative from 1960s through 70s aimed at improving so-called “blighted” areas, and resulted in the displacement of many vibrant communities. While the underlying mechanisms of urban renewal have been examined, there have been very few data-driven, evidence-based studies that take into account the histories and interests of former residents. The “Human Face of Big Data” project started as a digital curation effort to design and develop a web-based, big data platform that provides insights and analytics into the mechanisms of this process.

Cycle Atlanta: Seeing Like a Bike

The Cycle Atlanta project aims at creating sensor systems that allow a bike to "see" its environment and collect data as a participatory effort so that we can help the City of Atlanta to make informed decisions about biking infrastructures. Specifically, a sensor box equipped with sonars, lidars, PM sensors, gas sensors, gyroscope, accelerometer, and others was developed to detect environmental factors that can give rise to cyclists' stress level. I participated in this project as a Data Science for Social Good (Atlanta's DSSG) Summer fellow in 2017.

A Tool for Estimating and Visualizing Poverty Maps

"Poverty maps" are designed to simultaneously display the spatial distribution of welfare and different dimensions of poverty determinants. The plotting of such information on maps heavily relies on data that is collected through infrequent national household surveys and censuses. However, due to the high cost associated with this type of data collection process, poverty maps are often inaccurate in capturing the current deprivation status.

Human Face of Big Data

This project aims to build a map-based platform that can be used in presenting historical documents of the nation-wide, urban renewal project in 1960's and 70's to provide easy-to-use interfaces that can be used by former residents, archivists, researchers, and citizens; and ultimately to reconstruct a virtual neighborhood where people can share their memories.

Open Data Impact Map

The Center for Open Data Enterprise is a non-profit organization that aims to maximize the value of open data as a public resource that anyone can use. As a means to promote the impact and value of using open data, the center designed and developed the Open Data Impact map. As a Data Science & Technology Fellow at the Center for Open Data Enterprise, I have worked on the Open Data Impact Map, which is a searchable, centralized database of open data use cases from around the world. The map shows the distribution of organizations in the world that make use of open data.

Large-scale News Image Analysis with MapReduce-based LSH and VisualRank

Hao Li (Ph.D. student from CS) and I conducted a big-data analysis project using the MapReduce framework (Hadoop) for the final project of INFM718G (Data-Intensive Computing with MapReduce, by Dr. Jimmy Lin). Targeting all the news images in April 2013, we tried to rank news images based on the importance and popularity level of each news image. To do that, we extracted image features using SIFT (Scale-invariant feature transform) and constructed a graph of images using LSH (Locality-sensitive Hashing) as a means to approximate the similarity of images.

Human-Robot Interaction via Sound

This prototype was an intermediate result of a robot-human interaction project conducted at Torooc Inc., a start-up company where I was a co-founder and Director of Software Development, in 2011. I first designed microphone amplifier circuits using transistors and amplifier chips, respectively. Then, I connected three microphones to Texas Instruments' Stellaris LM4F embedded board. On top of that, I implemented a Time-Difference of Arrival (TDOA) algorithm in C language.

"I know where that is": Cultural Differences in Perception of New Places

This research project had been conducted for my master's thesis (Master of Information Management degree). I conceptualized cultual background with Hall's high- and low-context culture (1976) and tried to see whether people's perceptions of urban places vary between physical addresses and symbolic representations of spaces (landmarks), when their cultural backgrounds were different. A survey questionnaire was used to measure cultural background, and a web-based online game was used to measure people's perceptions of places.

"What Makes a Place More Familiar?": Implications of Geospatial Information Format and Content

This project was originally initiated as a class project from INST 741 (Social Computing) class in 2013, and redesigned to a research project and accepted to CHI '15 Work-in-progress session. I organized a 4-member team and we collaborated on designing the study as a team. The video was created originally for Social Media Expo, iConfernece 2014, so the title is different from the CHI paper. This research project tried to identify the role of geospatial information format (image or text) and content (place or space) on people's familiarity of new places.

Cozy Street Blocks

This was the final project of the "Theory and Practice in Intelligent Convergence Systems" class from the Graduate School of Convergence Scinece and Technology in 2009. The goal of this system was (1) to grow plants in an urban environment; (2) to change urban places into eco-friendly and entertaining spaces; and (3) to make use of street blocks as indicators for urban information. In order to do that, we presented designs of the software/hardware architectures of the blocks and user scenarios.