About

We are a research group that integrates geospatial data science, urban informatics, and human dynamics modeling to transform multi-source urban observations into decision-relevant intelligence for urban resilience and health.

Research topics

• Computer Science
• Natural Language Processing
• Political Science
• Machine Learning
• Artificial Intelligence
• Psychology
• Statistics
• World Wide Web
• Data science
• Economics
• Environmental planning
• Geography
• Socioeconomics

Selected publications

• Relationship between chromatin configuration and maturation ability of rat oocytes in vitro and in vivo

  PLoS ONE · 2025-02-13

  articleOpen accessCorresponding

  PURPOSE: Embryo engineering requires a large number of oocytes, which undergo in vitro maturation (IVM). Understanding how to select the best quality oocytes is key to improving IVM efficiency. Oocytes have different germinal vesicle (GV) chromatin configurations, which may explain the heterogeneity in oocyte quality during IVM. However, no reports have categorized, the chromatin configuration of rat GVs or evaluated, the association between the chromatin configuration and oocytes development. METHODS: The GV chromatin configuration of rat oocytes was divided into seven types according to the degree of chromatin compaction: non-surrounded nucleolus (NSN), prematurely condensed NSN, partly NSN, partly surrounded nucleolus (SN-1), SN-1, condensed SN-1, and aggregated (SN-2). The chromatin configuration distribution was compared during the different stages of oocyte growth and maturation. We also analyzed the changes in the chromatin configuration at different GV stages during IVM. Moreover, the factors affecting the chromatin configuration were analyzed. RESULTS: The SN-2 configuration increased with rat oocyte growth and maturation, suggesting that SN-2 facilitates oocyte development. RNA transcription activity in rat oocyte GVs was inversely correlated with oocyte IVM. CONCLUSIONS: The SN-2 chromatin configuration was related to rat oocyte growth and maturation. RNA transcription activity in rat oocytes in the GV stage was inversely correlated with oocyte maturation.

  PublisherDOI

• An Acoustic Positioning Algorithm for Complex Array Configurations on Underwater Platforms

  2025-06-16

  article1st authorCorresponding

  The Ultra-short baseline(USBL) system plays an important role in underwater vehicle positioning, and the acoustic array is the core component in the USBL system. To adapt different models of platforms, acoustic arrays are typically designed with complex geometries. The existing positioning algorithms for complex arrays exhibit low computational efficiency due to the large number of subarray combinations in complex arrays. To address this challenge, we propose an efficient positioning algorithm for complex arrays by introducing a position correction term into the existing positioning model. It aims to reduce the number of subarray combinations by normalizing the positioning results of independent subarrays based on the position correction term. Simulation and field trial results show that the proposed algorithm can achieve positioning accuracy comparable to the existing algorithm, while requiring less computation time.

  PublisherDOI

• Rapid Disaster Response and Damage Estimation with Social Media and Pretrained Large Language Models: Insights from Multiple Hurricanes

  Annals of the American Association of Geographers · 2025-11-06

  article
  PublisherDOI

• Urban Climate Adaptation and REsilience (U-CARE) in Texas: Insights from Interdisciplinary Perspectives

  Applied Spatial Analysis and Policy · 2025-05-07 · 3 citations

  article
  PublisherDOI

• Integrating Natural Language Processing in Human Geography

  Springer geography · 2025-01-01

  book-chapterSenior author
  PublisherDOI

• Unveiling community adaptations to extreme heat events using mobile phone location data

  Journal of Environmental Management · 2024-07-19 · 21 citations

  articleCorresponding
  PublisherDOI

• Structural insights into the distinct ligand recognition and signaling of the chemerin receptors CMKLR1 and GPR1

  Protein & Cell · 2024-12-30 · 6 citations

  articleOpen access
  PublisherOA PDFDOI

• Sensing the pulse of the pandemic: unveiling the geographical and demographic disparities of public sentiment toward COVID-19 through social media

  Cartography and Geographic Information Science · 2024-03-21 · 7 citations

  article

  Social media offers a unique lens to observe large-scale, spatial-temporal patterns of users' reactions toward critical events. However, social media use varies across demographics, with younger users being more prevalent compared to older populations. This difference introduces biases in data representativeness, and analysis based on social media without proper adjustment will lead to overlooking the voices of digitally marginalized communities and inaccurate estimations. This study explores solutions to pinpoint and alleviate the demographic biases in social media analysis through a case study estimating the public sentiment about COVID-19 using Twitter data. We analyzed the pandemic-related Twitter data in the U.S. during 2020–2021 to (1) elucidate the uneven social media usage among demographic groups and the disparities of their sentiments toward COVID-19, (2) construct an adjusted public sentiment measurement based on social media, the Sentiment Adjusted by Demographics (SAD) index, to evaluate the spatiotemporal varying public sentiment toward COVID-19. The results show higher proportions of female and adolescent Twitter users expressing negative emotions to COVID-19. The SAD index unveils that the public sentiment toward COVID-19 was most negative in January and February 2020 and most positive in April 2020. Vermont and Wyoming were the most positive and negative states toward COVID-19.

  PublisherDOI

• Understanding the disparate impacts of the 2021 Texas winter storm and power outages through mobile phone location data and nighttime light images

  International Journal of Disaster Risk Reduction · 2024-02-15 · 19 citations

  article
  PublisherDOI

• Understanding Human-COVID-19 Dynamics using Geospatial Big Data: A Systematic Literature Review

  arXiv (Cornell University) · 2024-04-13

  preprintOpen access

  The COVID-19 pandemic has changed human life. To mitigate the pandemic's impacts, different regions implemented various policies to contain COVID-19 and residents showed diverse responses. These human responses in turn shaped the uneven spatial-temporal spread of COVID-19. Consequently, the human-pandemic interaction is complex, dynamic, and interconnected. Delineating the reciprocal effects between human society and the pandemic is imperative for mitigating risks from future epidemics. Geospatial big data acquired through mobile applications and sensor networks have facilitated near-real-time tracking and assessment of human responses to the pandemic, enabling a surge in researching human-pandemic interactions. However, these investigations involve inconsistent data sources, human activity indicators, relationship detection models, and analysis methods, leading to a fragmented understanding of human-pandemic dynamics. To assess the current state of human-pandemic interactions research, we conducted a synthesis study based on 67 selected publications between March 2020 and January 2023. We extracted key information from each article across six categories, e.g., research area and time, data, methodological framework, and results and conclusions. Results reveal that regression models were predominant in relationship detection, featured in 67.16% of papers. Only two papers employed spatial-temporal models, notably underrepresented in the existing literature. Studies examining the effects of policies and human mobility on the pandemic's health impacts were the most prevalent, each comprising 12 articles (17.91%). Only 3 papers (4.48%) delved into bidirectional interactions between human responses and the COVID-19 spread. These findings shed light on the need for future research to spatially and temporally model the long-term, bidirectional causal relationships within human-pandemic systems.

  PublisherOA PDFDOI

Frequent coauthors

• Lei Zou

  50 shared

• Nina Lam

  25 shared

• Bing Zhou

  Guangdong Ocean University

  24 shared

• Lei Luo

  20 shared

• Yi Qiang

  University of South Florida

  18 shared

• Mingzheng Yang

  16 shared

• Lun Wu

  16 shared

• Xinyuan Wang

  16 shared

Education

• Ph.D. in Environmental Science

  Louisiana State University

  2017

• M.S. in Cartography and Geographic Information System

  Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences

  2013

• B.E. in Surveying and Mapping Engineering

  China University of Geosciences Beijing

  2010

Awards & honors

• Early-Career Research Fellowship Award in the Human Health a…
• 2025 TAMU Montague-Center for Teaching Excellence Scholar