Taylor is an assistant professor in the department of geographical sciences at the University of Maryland. He broadly interested in characterizing spatial patterns and processes through the use of quantitative geographic methods, which typically falls under the banners of spatial analysis and spatial statistics, geographic information science, and spatial data science. Overall, my research his targeted the development of multivariate spatial statistics and how they can be used to capture how relationships change by spatial and temporal contexts. This includes issues of theory, interpretation, scalability, and integration of traditional geographic models with novel "big" datasets, as well as applications in public health, crime, urban mobility, and transportation systems.

Zheng Liu is a Ph.D. candidate in the Center for Geographical Information Science, University of Maryland, College Park. His research interest lies in urban analytics and micro-mobility modeling using big data and machine learning techniques. He is working on multi-temporal mobility modeling of micro-mobility as his dissertation topic. He is also interested in the application of GIScience in the self-driving industry. Before joining UMD, he obtained his Bachelor of Science in Geographical Information Science at Peking University.

Mengyu's interests include spatiotemporal theories and applications, big data, spatial data science, as well as geospatial modeling with machine learning. As a Ph.D student, she eager to use those above to explore how humans perceive, interact with, and change space/environments. Particularly, she has a strong interest in bridging geospatial modeling with criminology, human mobility and health.

Ushashi's interests include geospatial visualization, spatial data science, spatial modeling, and machine learning with applications in urban, transportation and health geography. She aims to expand her skills and apply those to study the mobility patterns, behaviors, and activities of humans across space. She also aims to apply her skills to the health sector to study infectious diseases by taking into account human mobility patterns. Bike sharing system and sustainable transportation is also an arena of interest that she is exploring.

Victor Irekponor is a first-year Ph.D. student in the Center for Geographical Information Science, University of Maryland, College Park. He is broadly interested at the cutting-edge of research and development in urban informatics, smart cities, and geospatial data science; specifically, the science that investigates the ‘where’ and ‘why’ of various human and natural phenomena in cities. Before coming to Maryland, he studied at the University of Lagos, Nigeria, and graduated with a first-class bachelor’s degree in urban planning. Beyond academics, Victor has over three years of software engineering experience as well as experience building and deploying machine learning models. His major tools include Python, Scikit-learn, Keras, Tensorflow, and React.js. He hopes to deploy his skills in software engineering, data science, and urban planning to conceptualize and contribute significantly to smart cities research.

Janna is a senior undergraduate double majoring in Environmental Science and Technology and Geographical Sciences and a 4+1 masters student in Geographical Sciences. She is interested in using GIS to analyze the spatial patterns of environmental issues such as the urban heat island effect, deforestation, and air pollution to help inform sustainable solutions to those problems. She plans to a career in environmental data science.

Oluwatomisin is a University of Maryland graduate, having obtained a degree in Geographical Sciences with a specialization in GIS/Computer Cartography in 2017. With a professional background as a GIS / Data analyst, Oluwatomisin developed proficient skills in spatial analysis and data visualization. He has since leveraged his experience in marketing and project management across various sectors, including government, web3, and agency projects, enabling him to adeptly apply a unique fusion of analytical and creative expertise, resulting in highly impactful outcomes.

As a Geospatial Web3 Developer, John combines GIS domain knowledge and full stack web development to create beautiful (and fast) DApps. Previously, John studied GIS under thought leaders (Michael Goodchild, Waldo Tobler, Krzysztof Janowicz, and Dan Montello) while completing a B.A. in Geography at UC Santa Barbara and an M.S. in Geoinformatics and Geospatial Intelligence at George Mason University.

Coming from a background of math and computer science, Tyler is interested in methods development and algorithm design for spatial data science. He's also an advocate for the use of spatial methods in broader research. In his spare time, Tyler loves watching movies, playing video games, and biking. He's currently a Ph.D student at Arizona State University in the Spatial Analysis Research Center (SPARC).

Matthew is a undergraduate at the University of Maryland studying computer and information science. He has experience in developing client-side apps in both the Ethereum and Solana ecosystem. As a developer for the EASIER Data Initiative, he aims to explore decentralized storage and compute and how they can be used for data-intensive geospatial workflows.

Jack is a Master of Quantitative Finance student at the Robert H. Smith School of Business and he graduated in 2021 from the University of Maryland with a Bachelor's Degree in Mathematics. He is interested in exploring the economic and organizational implications of decentralized web technology on the geospatial data ecosystem. He also runs a consulting business, providing modeling and analytics services in token economics for web3 startups and companies.