Hi, I'm Serena

computational social scientist


I'm an assistant professor of research methods in the School of Public and International Affairs at NC State University. From 2019 to 2023, I was a research associate in the College of Engineering, Design, and Computing and a scholar in residence in the School of Public Affairs at the University of Colorado Denver. During this time, I taught graduate courses on evidence-based decision-making, public policy analysis, and research and analytic methods.

My primary research interest lies in the social science applications of full-stack data analytics, which integrates understanding of social problems, creating and managing databases, deploying models based on statistics and machine learning algorithms, developing systems and software for continuous and reliable data generation and processing, and communicating data to promote data-informed decision-making. Topics of interest include neural networks for natural language processing and computer vision, data mining, geospatial data science, network analysis using big data, machine learning algorithms for prediction, applied software development, data visualization, and data-centric AI for systematic data engineering in social science research.

I have domain expertise in US energy policy and the energy transition such as the adoption of renewable and distributed energy resources. But I've also collaborated with researchers who focus on public health and environmental sustainability, and I apply full-stack data analytics in these domains. My work has appeared in peer-reviewed journals, including Energy Policy, Policy Studies Journal and SSM - Population Health among others, and my research has been featured in media outlets such as The New York Times and Washington Post. I have a strong foundation in institutional analysis, and my research is often informed by transaction cost economics and collective action frameworks. For more information, please see the Research page. When I'm not at work, I enjoy hiking, dancing, practicing yoga, playing the piano, trying new recipes, reading books, watching movies, and attending performing arts shows and college and professional basketball games.



Serena Kim

Computational social scientist with domain expertise in energy policy, renewable energy adoption, public perception of renewable energy, institutional analysis, and collective action

  • 2221 Hillsborough St, Raleigh, NC 27607
  • serena_kim@ncsu.edu


PhD in Public Administration

Askew School of Public Administration and Policy, Florida State University, Tallahassee, FL

Dissertation: Essays on U.S. Renewable Energy and Sustainability Policy

MS in Computer Science

University of Colorado Boulder, Boulder, CO

Courses Taken: Natural Language Processing, Software Engineering, Data Science Teams, Network Analysis and Modeling, Geographic Information Systems, Data Mining, Machine Learning, Entrepreneurial Projects, Computer Graphics, Neural Networks and Deep Learning, Big Data Analytics: Systems, Algorithms, and Applications

BA in Public Administration & Economics (Dual Major)

Yonsei University, Seoul, South Korea

Professional Experience

Assistant Professor

August 2023 -

School of Public and International Affairs, NC State University

  • Teach and research social science research methods

Senior Instructor & Scholar in Residence

2019 - July 2023

School of Public Affairs, CU Denver

  • Taught 27 sections of four graduate courses
  • Public policy analysis concentration director

Postdoctoral Research Associate

2021 - July 2023

College of Engineering, Design, and Computing, CU Denver

  • Research on the energy transition to renewables and vehicle electrification

Senior Researcher

2020 - Present

The Schreiber Research Group

  • Geospatial, text, and network data analysis and visualization

Data Analysis Skills & Tech Stack

I love coding and programming for scientific discovery and research communication. I have developed my statistical and computational skills over 10+ years of formal training in computer science, economics, and public policy and administration, and I am motivated and excited to learn new tools and important developments in computer science and statistics. Below are selected skills and tools that I use regularly. Although I have used other programming languages, including C/C++, Go, JavaScript, Ruby, Kotlin, R, and MATLAB for various projects, Python has been my main working language. Progress bars below indicate how far along I am in the process of developing each skill as of January 2024.

Data Engineering & Management
Data Mining - Web Scraping, APIs95%
Data Wrangling - Pandas, JSON, pickle, OS, etc. 100%
Data Engineering - SQL, GCP, MongoDB, AWS S360%

Statistical Analysis
Python - Regression and Time Series Models95%
R - Regression and Time Series Models, Synthetic Control85%
Stata - Regression and Time Series Models, Survey Analysis95%

Spatial Data Science & Engineering
Spatial Database - POSTGIS80%
Geospatial Data Management - GeoPandas, shapely100%
Raster and Vector Data - GDAL60%
Map Visualization - LeafletJS, Folium, Mapbox, geoplotlib 90%
ArcGIS Suite - ArcMap, ArcGIS Online, ArcGIS Pro90%

Data Visualization
Python - Matplotlib, seaborn, Plotly100%
R - ggplot2, Plotly75%

Machine Learning (ML) & Neural Networks
ML - scikit-learn, XGBoost, CatBoost, LightGBM95%
Computer Vision - Keras, TensorFlow, OpenCV, Pytorch80%
NLP - HuggingFace, TensorFlow, PyTorch, NLTK95%
Interpretable AI - Shap, Global Surrogate85%

Network Analysis & Modeling
Python - NetworkX, graph-tool90%

Applied Software Development
Version Control, CI/CD - Git 80%
Backend - Django (Python), Flask (Python), NodeJS (JavaScript)75%
Frontend - React, HTML/CSS/SASS, Bootstrap80%
DevOps - Git, Docker, Kubernetes 40%

Computer Graphics
Adobe Suite - Photoshop, Illustrator, InDesign70%
3D Graphics - OpenGL (C/C++)70%

Surveys & Interviews
Interview Data Collection and Analysis75%
Survey Data Collection and Analysis85%


I am passionate about fostering data literacy and providing robust computing education for students in social and behavioral sciences and humanities. My courses are designed to help students read, analyze, interpret, visualize, and communicate data effectively as well as to understand the use of data in decision-making. I believe data literacy and computing skills can empower students to engage with important socioeconomic and environmental issues and promote equity and inclusion in learning outcomes. Students in my classes are from various academic disciplines, including urban and regional planning, public policy, business administration, sociology, economics, criminal justice, public health, information science, and civil engineering, among others. Please find the syllabi below.

Research &
Analytic Methods

Master's | CU Denver
2019 – 2023



Master's | CU Denver
2019 – 2023


Public Policy

Master's | CU Denver
2019 – 2023


Public Policy

Master's | CU Denver

Research Projects

My research lies at the intersection of data science and social issues, including energy transition, environmental problems, climate change, natural disasters, and public health. I aspire to leverage critical developments in computer science for addressing grand challenges in sustainability, energy, social equity, public health, and more. My recent and ongoing research projects can be organized by the following four subjects. This section is being updated as of August 2023.

  • All
  • Energy Transition
  • Environmental Sustainability
  • Public Health
  • Collective Action

Social Stigma in Substance Use Disorder

Social media analysis, Big Data, GIS

Solar Photovoltaic Deployment

Solar adoption, computer vision, neural network, machine learning

Public Sentiment Toward Solar Energy

Pubic opinion, natural language processing, BERT, machine learning

Building Energy Use Benchmarking Policy Design

Energy use intensity, machine learning

Power Outage Vulnerability

resilience, geospatial data science, software engineering

Racial Segregation in Substance Use Treatment Facilities

Panel data analysis, data mining, document analysis, GIS

Vehicle-to-Grid (V2G)

EV, bidirectional charging, WTP survey experiment, cost benefit analysis

Policy Commitments to Green Affordable Housing

Survey, machine learning, process tracing, US Local Governments

Renewable Energy Policy Diffusion

Innovation and diffusion, network analysis, international policy

Airport Solar Projects

Institutional analysis, statistical analysis, interviews

Urban-Rural Disparities in Substance Use Policy

Statistical analysis, survey weights

Conflict Across Energy Infrastructure

Energy infrastructure siting decisions; regression, interviews, mixd methods

Strategies for Planning Sustainable Development

US local sustainability policy, case study, interviews

Institutional Collective Action Framework

Transaction cost theory, institutional analysis, Theoretical articles

Recent News

Aug 2023 Awarded a National Science Foundation (NSF) Strengthening American Infrastructure (SAI) Grant (Co-PI): Integration of Electric Vehicles and the Electric Grid ($750,000).

Jul 2023 New article, "Spatial Distribution of Solar PV Deployment: An Application of the Region-Based Convolutional Neural Network" on EPJ Data Science

Apr 2023 New article, "Electricity peak shaving for commercial buildings using machine learning and vehicle to building (V2B) system," in Applied Energy.

Sep 2022 Poster presentation, "Spatial Distribution of Solar PV Deployment: An Application of the Region-Based Convolutional Neural Network," at The Rocky Mountain Celebration of Women in Computing 2022.

Aug 2022 Quoted in the article "Dulles solar farm would be the nation's largest at an airport," The Washington Post.

Jun 2022 A talk on "Big Data, Public Policy, and Distributed Energy Resources" at the Institute for Regulatory Law and Economics (IRLE)-Rocky Mountain Institute (RMI) workshop in Boulder

Jun 2022 A talk on "Polycentric Governance and Collective Action in Energy Transition" at the IRLE-RMI workshop in Boulder

Mar 2022 Grant awarded: "Community Microgrids for Energy Resilience and Emergency Planning" by the University of Colorado Denver Office of Research Services.

Feb 2022 New article, "The Distribution of Conflict and Attention Across Energy Infrastructure," in Public Administration.

Feb 2022 Talk at the 2022 IRLE workshop for graduate students, "Geospatial Data Science and Energy Research" University of Colorado Denver.

Jan 2022 Dissertation mentionend in the article "Seeking Space for Solar Farms, Cities Find Room at Their Airports," New York Times.

Oct 2021 Grant awarded: "Electric Vehicles (EVs) as a Tool for Energy Efficiency and Resilience" by the University of Colorado Denver CRC Faculty Interdisciplinary Fellowship.

Feb 2021 New article, "Public Sentiment toward Solar Energy—Opinion Mining of Twitter Using a Transformer-Based Language Model" in Sustainability.

Nov 2020 A guest talk at the seminar, "Dismantling Racism and Inequity in our Schools," in the School of Education, University of Colorado Denver.

Oct 2020 Grant awarded: “Integrated Solar Energy for Sustainable, Resilient, and Equitable Communities" by the Presidential Initiative on Urban and Place-Based Research.

Sep 2020 My paper, "Institutional Arrangements and Airport Solar PV," in Energy Policy, was featured in media outlets including Colorado Politics, International Business Times, Science Daily, The Gazette, Solar Daily, AZO Materials and Oklahoma Energy Today.

MAY 2020 A talk on "Survey Response Bias and Survey Weights" at The Schreiber Research Group.


Please reach out if you are interested in collaborating with me.

Serena Kim

Data scientist and computational social scientist with domain expertise in energy policy, renewable energy adoption, public perception of renewable energy, institutional analysis, and collective action

2221 Hillsborough St
Raleigh, NC 27607

serena_kim "at" ncsu "dot" edu