Publications

  • Kim, Joon-Seok, Anderson, Taylor, Shashidharan, Ashwin & Hohl, Alexander (2023). GeoSim 2022 Workshop Report: The 5th ACM SIGSPATIAL International Workshop on Geospatial Simulation. SIGSPATIAL Special. Published, 11/07/2023.
    https://doi.org/10.1145/3632268.3632280
  • Lotfata A. & Hohl A. (2023). Spatiotemporal associations of mental distress with socioeconomic and environmental factors in Chicago, IL, 2015–2019. (pp. 573-581). Vol. 31, Spatial Information Research. Published, 10/01/2023.
  • Choi M. & Hohl A. (2023). Investigating factors in indoor transmission of respiratory disease through agent-based modeling. (pp. 1794-1827). Vol. 27, Transactions in GIS. Published, 09/01/2023.
  • Hohl, A. (2023). COVID-19: adverse population sentiment and place-based associations with socioeconomic and demographic factors. Spatial Information Research. 1-12. Published, 08/23/2023.
    https://doi.org/10.1007/s41324-023-00544-y
  • Yan J., Huang X., Wang S., He Y., Li X., Hohl A., Li X., Aly M. & Lin B. (2023). Toward a comprehensive understanding of eye-level urban greenness: a systematic review. (pp. 4769-4789). Vol. 16. International Journal of Digital Earth. Published, 01/01/2023.
  • Aynaz Lotfata & Alexander Hohl (2022). Spatial association of respiratory health with social and environmental factors: case study of Cook County, Illinois, USA. Cities & health. Published, 12/20/2022.
    https://doi.org/10.1080/23748834.2021.2011538
  • Xiao Huang, Siqin Wang, Mengxi Zhang, Tao Hu, Alexander Hohl, Bing She, Xi Gong, Jianxin Li, Xiao Liu, Oliver Gruebner, Regina Liu, Xiao Li, Zhewei Liu , Xinyue Ye & Zhenlong Li (2022). Social media mining under the COVID-19 context: Progress, challenges, and opportunities. International Journal of Applied Earth Observation and Geoinformation. Published, 08/19/2022.
    https://doi.org/10.1016/j.jag.2022.102967
  • Alexander Hohl & Aynaz Lotfata (2022). Modeling spatiotemporal associations of obesity prevalence with biking, housing cost and green spaces in Chicago, IL, USA, 2015–2017. Journal of Transport & Health. Published, 06/25/2022.
    https://doi.org/10.1016/j.jth.2022.101412
  • Alexander Hohl, Wenwu Tang, Eric Delmelle, Irene Casas, Eric Delmelle & Xun Shi (2022). Detecting space–time patterns of disease risk under dynamic background population. Journal of geographical systems. Published, 04/20/2022.
    https://doi.org/10.1007/s10109-022-00377-7
  • Alexander Hohl & Aynaz Lotfata (2022). geographical analysis of socioeconomic and environmental drivers of physical inactivity in post pandemic cities: The case study of Chicago, IL, USA. Urban Science. Published, 04/14/2022.
    https://doi.org/10.3390/urbansci6020028
  • Michael Desjardins, Alexander Hohl, Eric Delmelle & Irene Casas (2022). Identifying and Visualizing Space-Time Clusters of Vector-Borne Diseases. Springer International Publishing. Published, 03/22/2022.
    https://doi.org/10.1007/978-3-030-71377-5_11
  • Alexander Hohl, Moongi Choi, Aggie J Yellow Horse, Richard M Medina, Neng Wan & Ming Wen (2022). Spatial Distribution of Hateful Tweets Against Asians and Asian Americans During the COVID-19 Pandemic, November 2019 to May 2020. American Public Health Association. Published, 03/20/2022.
    https://doi.org/10.2105/AJPH.2021.306653
  • Eric Delmelle, Michael R. Desjardins, Paul Jung, Claudio Owusu, Yu Lan, Alexander Hohl & Coline Dony (2021). Uncertainty in geospatial health: challenges and opportunities ahead. Elsevier. Published, 10/14/2021.
    https://doi.org/10.1016/j.annepidem.2021.10.002
  • Alexander Hohl, Eric M. Delmelle, Michael R. Desjardins & Yu Lan (2020). Daily surveillance of COVID-19 using the prospective space-time scan statistic in the United States. Spatial and Spatio-temporal Epidemiology. Vol. 34. Published, 08/2020.
    https://doi.org/10.1016/j.sste.2020.100354
  • Alexander Hohl, Erik Saule, Eric Delmelle & Wenwu Tang (2020). Spatiotemporal Domain Decomposition for High Performance Computing: A Flexible Splits Heuristic to Minimize Redundancy. Springer. Published, 07/21/2020.
    https://link.springer.com/chapter/10.1007/978-3-03...
  • Alexander Hohl (2020). Rapid detection of COVID-19 clusters in the United States using a prospective space-time scan statistic: an update. ACM. Published, 06/2020.
    https://doi.org/10.1145/3404820.3404825
  • Michael R. Desjardins, Alexander Hohl & Eric Delmelle (2020). Rapid surveillance of COVID-19 in the United States using a prospective space-time scan statistic: Detecting and evaluating emerging clusters. Elsevier. Vol. 118. Published, 05/2020.
    https://doi.org/10.1016/j.apgeog.2020.102202
  • Alexander Hohl & Peilin Chen (2019). Spatiotemporal simulation: local Ripley's K function parameterizes adaptive kernel density estimation. (pp. 16-23). GeoSim '19 Proceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation. Published, 11/05/2019.
    https://dl.acm.org/citation.cfm?doid=3356470.33655...
  • Michael Desjardins, Alexander Hohl, Adam Griffith & Eric Delmelle (2018). A space–time parallel framework for fine-scale visualization of pollen levels across the Eastern United States. Cartography and Geographic Information Science. 428-440. Published, 10/18/2018.
    https://doi.org/10.1080/15230406.2018.1515664
  • Alexander Hohl, Adam D. Griffith, Martha Cary Eppes & Eric M. Delmelle (2018). Computationally Enabled 4D Visualizations Facilitate the Detection of Rock Fracture Patterns from Acoustic Emissions. Rock Mechanics and Rock Engineering. Vol. 51(9), 2733-2746. Published, 09/01/2018.
    https://link.springer.com/article/10.1007/s00603-0...
  • Alexander Hohl, Minrui Zheng, Wenwu Tang, Eric Delmelle & Irene Casas (2017). Spatiotemporal Point Pattern Analysis Using Ripley’s K Function. (pp. 155-175). Karimi & Karimi: Geospatial Data Science: Techniques and Applications. Published, 10/2017.
    https://www.taylorfrancis.com/chapters/spatiotempo...
  • Erik Saule, Dinesh Panchananam, Alexander Hohl, Wenwu Tang & Eric Delmelle (2017). Parallel space-time kernel density estimation. 46th International Conference on Parallel Processing (ICPP). Published, 08/14/2017.
  • Jesse Piburn, Robert Stewart, Aaron Meyers, Alex Sorokine, Eric Axley, David Anderson, Jordan Burdette, Christian Biddle, Alexander Hohl, Ryan Eberle, Jason Kaufman & April Morton (2017). The World Spatiotemporal Analytics and Mapping Project (WSTAMP): Further Progress in Discovering, Exploring, and Mapping Spatiotemporal Patterns Across the World’s Largest Open Source Data Sets. Vol. IV-4/W2. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Published, 08/2017.
  • Michael Desjardins, Alexander Hohl, Adam Griffith & Eric Delmelle (2017). Fine-scale visualization of pollen concentrations across the Eastern United States: A space-time parallel approach. http://www.geocomputation.org/ 2017/papers/68.pdf. Published, 08/2017.
  • Alexander Hohl (2016). Hybrid Indexing for Parallel Analysis of Spatiotemporal Point Patterns. International Conference on GIScience Short Paper Proceedings. Published, 12/2016.
  • Alexander Hohl, Eric Delmelle, Wenwu Tang & Irene Casas (2016). Accelerating the discovery of space-time patterns of infectious diseases using parallel computing. Spatial and spatio-temporal epidemiology. Vol. 19, 10-20. Published, 11/01/2016.
  • Alexander Hohl, Eric Delmelle & Wenwu Tang (2015). SPATIOTEMPORAL DOMAIN DECOMPOSITION FOR MASSIVE PARALLEL COMPUTATION OF SPACE-TIME KERNEL DENSITY. Vol. II-4/W2. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Published, 07/2015.
  • Alexander Hohl, Tomáš Václavík & Ross K Meentemeyer (2014). Go with the flow: geospatial analytics to quantify hydrologic landscape connectivity for passively dispersed microorganisms. International Journal of Geographical Information Science. Vol. 28 (8), 1626-1641. Published, 08/03/2014.

Research Keywords

  • geovisualization
  • Spatial Statistics and Space-time Modeling
  • Spatial Epidemiology
  • Health Geography
  • Geographical information systems (GIS)
  • Geocomputation

Presentations

  • Choi., M. & Hohl, A. Fixing Equifinality of ABM: sequential parameter space searching method based on global sensitivity analysis. Annual Meeting of the AAG. Denver, CO, USA. Presentation, Presented, 03/27/2023.
  • Spatiotemporal analysis of anti-Asian hate on social media in the United States. Annual Meeting of the American Association of Geographers (AAG). Denver, CO, USA. Presentation, Presented, 03/24/2023.
  • Space-time clustering of COVID-19: An early career research trajectory during the pandemic. Distinguished Invited Speaker, Geography Graduate Student Association (GGSA), Department of Geography and Geographic Information Science (GGIS), University of Illinois Urbana-Champaign. Invited Talk/Keynote, Presented, 11/10/2022.
  • Hohl, A. Space-time clustering of COVID-19: An early career research trajectory during the pandemic. GIScience Colloquium, Department of Geography, University of Zurich. Zurich, Switzerland. Invited Talk/Keynote, Presented, 07/20/2022.
  • The Geography of Anti-Asian Hate on Twitter during the COVID-19 Pandemic, November 2019 to May 2020. When Big Data Meets Sociological Imagination: Transdisciplinary Approaches and Infrastructures for Computational Social Science. City University of Hong Kong. Virtual Symposium. Invited Talk/Keynote, Presented, 06/15/2022.
    https://live.polyv.cn/watch/3167102
  • Geospatial Approaches for addressing the COVID-19 pandemic. Utah Valley University GIS Seminar Series. Invited Talk/Keynote, Presented, 04/11/2022.
    https://youtu.be/GLap2rCwclA
  • How Can We Stop AAPI Hate and Bias? Research & Policy Perspectives. Asia Center, Hinkley Institute, University of Utah. Panel, Presented, 03/30/2022.
    https://www.youtube.com/live/ImK56X5w6Kg?feature=s...
  • Hohl, A., Choi, M., Yellow Horse, A.J., Medina, R.M, Wan, N., Wen, M. (2022) The Geography of Anti-Asian Hate on Twitter during the COVID-19 Pandemic, November 2019 to May 2020. Annual Meeting of the American Association of Geographers (AAG). Virtual Meeting. Presentation, Presented, 03/01/2022.
    https://youtu.be/19X2_o_78mM
  • Hohl, A., Choi, M., Yellow Horse, A., Medina, R., Wan, N., Wen, M. Adverse sentiment and anti-Asian hate during COVID-19. (2021). The 28th International Conference on Geoinformatics (CPGIS 2021). Virtual Meeting. Presentation, Presented, 08/05/2021.
  • Understanding Adverse Population Sentiment Towards the Spread of COVID-19 in the United States. COVID-19 Symposium. The Immunology, Inflammation, and Infectious Disease Initiative (3i), University of Utah Health. Virtual Meeting. Presentation, Presented, 06/04/2021.
    https://youtu.be/KdoZAL0HX2E
  • Hohl, A., Desjardins, M.R., Lan, Y., Brewer, S. & Delmelle, E. (2021). COVID-19 Surveillance. Annual Meeting of the American Association of Geographers (AAG). Virtual Meeting. Presentation, Presented, 04/11/2021.
  • Daily Surveillance of COVID-19 in the United States. Johns Hopkins University Center for a Livable Future GIS Week. Presentation, Accepted, 11/19/2020.
    https://youtu.be/kQMcIXzwJ4A?t=1704
  • Rapid detection of COVID-19 clusters in the United States using a prospective space-time scan statistic: An update. COVID-2020 Workshop@ACM SIGSPATIAL 2020. Presentation, Accepted, 11/03/2020.
    https://drive.google.com/file/d/1CDL7GaiVed95lRJQf...
  • Spatiotemporal simulation: local Ripley's K function parameterizes adaptive kernel density estimation. The 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation (GeoSim '19), November 5, 2019, Chicago, IL, USA. Presentation, Presented, 11/05/2019.
    https://www.geosim.org/p/program.html
  • Hohl, A., Tang, W., Delmelle, E. & Shi, X. (2019). Detecting Space-Time Patterns Under Non-Stationary Background Population. Annual Meeting of the American Association of Geographers (AAG). Washington, DC, USA. Presentation, Presented, 04/2019.
  • Hohl, A. (2018). Detecting Space-Time Patterns Under Non-Stationary Background Population. 2018 Utica College Faculty Research Day. Presentation, Presented, 11/09/2018.
  • Hohl, A., Tang, W., Delmelle, E. & Shi, X. (2018). Detecting Space-Time Patterns Under Non-Stationary Background Population. Annual Meeting of the Middle States Division of the American Association of Geographers (AAG). Montclair, NJ, USA. Presentation, Presented, 08/2018.
  • Hohl, A. (2018). Space-Time GIS Using Ripley’s K Function. Annual Meeting of the American Association of Geographers (AAG). New Orleans, LA, USA. Presentation, Presented, 04/2018.
  • Hohl, A. (2017). Spatiotemporal Domain Decomposition for Adaptive Bandwidth Kernel Density Estimation under Spatially and Temporally Inhomogeneous Background Population. Center for Applied GIS Seminar Series, UNC Charlotte. Invited Talk/Keynote, Presented, 10/04/2017.
  • Hohl, A. (2017). Accelerating the discovery of space-time patterns of infectious diseases. Brown Bag Seminar, Department of Geoinformatics (Z_GIS), University of Salzburg, Austria. Invited Talk/Keynote, Presented, 08/03/2017.
  • Hohl, A., Zheng, M., Jia, M., Delmelle, E., & Tang, W. (2017). Sensitivity Analysis of a High Performance Spatiotemporal Pattern Mining Algorithm. Annual Meeting of the American Association of Geographers (AAG). Boston, MA, USA. Presentation, Presented, 04/2017.
    https://drive.google.com/file/d/1138D6RQ_pshOQ8uqJ...
  • Hohl, A., Delmelle, E., Tang, W., & Casas, I. (2016). Spatiotemporal Domain Decomposition and Indexing for Discovery of Disease Patterns Using Parallel Computing. Annual Meeting of the Southeastern Division of the American Association of Geographers (SEDAAG). Columbia, SC, USA. Presentation, Presented, 11/2016.
  • Hohl, A. (2016). Hybrid Indexing for Parallel Analysis of Spatiotemporal Point Patterns. Center for Applied GIS Seminar Series, UNC Charlotte. Invited Talk/Keynote, Presented, 10/26/2016.
  • Hohl, A., Casas, I., Delmelle, E., & Tang, W. (2016). Hybrid Indexing for Parallel Analysis of Spatiotemporal Point Patterns. 9th International Conference on Geographic Information Science. Montréal, Canada. Conference Paper, Presented, 09/2016.
    https://drive.google.com/file/d/1DKCgCFjdRPTMwKC9U...
  • Hohl, A. (2016). Accelerated Discovery of Infectious Disease Clusters Using Adaptive Spatiotemporal Domain Decomposition. Annual Meeting of the American Association of Geographers (AAG). San Francisco, CA, USA. Presentation, Presented, 04/2016.
    https://drive.google.com/file/d/1-TRU0GjUB781lEi0b...
  • Hohl, A. (2015). Spatiotemporal Domain Decomposition for Massive Parallel Processing of Epidemiological Data. Annual Meeting of the Southeastern Division of the Association of American Geographers (SEDAAG). Pensacola, FL, USA. Presentation, Presented, 11/2015.
  • Hohl, A. (2015). Spatiotemporal Domain Decomposition for Massive Parallel Processing of Epidemiological Data. Center for Applied GIS Seminar Series, UNC Charlotte. Invited Talk/Keynote, Presented, 09/30/2015.
  • Hohl, A., Delmelle, E., & Tang, W. (2015). Spatiotemporal domain decomposition for massive parallel computation of space-time kernel density. 1st International Symposium on Spatiotemporal Computing, Fairfax, VA, USA. Conference Paper, Presented, 07/2015.
  • Hohl, A., Delmelle, E., & Tang, W. (2015). 3D domain decomposition for parallel processing of massive spatiotemporal geographic data. Annual Meeting of the Association of American Geographers (AAG). Chicago, IL, USA. Presentation, Presented, 04/2015.
  • Hohl, A., Václavík, T., Rizzo, D.M., & Meentemeyer, R.K. (2011). Go with the flow: Hydrological connectivity influences the dispersal of an invasive forest pathogen. 26th Annual Symposium of the US-Regional Association for the International Association for Landscape Ecology (US-IALE). Portland, OR, USA. Poster, Presented, 04/2011.
  • Hohl, A. (2011). Hydrological connectivity influences the dispersal of an invasive forest pathogen. 17th Annual Graduate Research Symposium of the Graduate and Professional Student Government at UNC Charlotte. Charlotte, NC, USA. Presentation, Presented, 04/2011.
  • Hohl, A., Václavík, T., Rizzo, D.M., & Meentemeyer, R.K. (2011). Go with the flow: Hydrological connectivity influences the dispersal of an invasive forest pathogen. Annual Meeting of the Association of American Geographers (AAG). Seattle, WA, USA. Presentation, Presented, 04/2011.
  • Hohl, A. (2010). Mapping the Spread of Sudden Oak Death Disease via Stream Baiting in California Watersheds. Annual Meeting of the South Eastern Division of the Association of American Geographers (SEDAAG). Birmingham, AL, USA. Poster, Presented, 11/2010.
  • Hohl, A., Rizzo, D.M., Václavík, T., & Meentemeyer, R.K. (2010). Stream baiting of Phytophthora ramorum for early detection of sudden oak death: Modeling forest disease spread in California at watershed level. 25th Annual Symposium of the US-Regional Association for the International Association for Landscape Ecology (US-IALE). Athens, GA, USA. Poster, Presented, 04/2010.
    https://alexanderhohl84.files.wordpress.com/2017/1...

Languages

  • English, fluent.
  • French, functional.
  • German, fluent.

Geographical Regions of Interest

  • Colombia
  • United States of America