Morteza Karimzadeh

Research Interests 

I am a spatial data scientist, with research and contributions cutting across geographic information retrieval, machine learning, geovisualization, and visual analytics. I conduct integrative research that brings together data science with social/environmental science to inform best practices for a more sustainable and equitable society. My research primarily focuses on method development, spanning various domains including GeoAI-based sea ice mapping, human mobility analysis, social media analytics, energy (resilience and production), crisis management, situational awareness, precision agriculture, and digital humanities; and I am always excited about applying my expertise in other domains.

Current Research 

My most recently funded project (2021-2024 period, supported by a $1.2M National Science Foundation award) is concerned with sea ice classification and mapping. We will use innovative, machine-learning for the geospatial fusion of heterogeneous big geoscientific data on the cloud to create high-resolution sea ice maps. I lead this project in collaboration with co-investigators in the National Snow and Ice Data Center and the Computer Science Department at CU Denver. 

My team is also creating new methods for leveraging large human-mobility data in studying social distancing mitigation measures and observed mobility patterns in response to local COVID-19 outbreaks.  

Another thread in my research, going back to my Ph.D. and postdoc years, focuses on geo-text analysis. A large portion of my research has focused on developing methods for enabling the use of geographical information embedded in textual data, a field of research formally known as Geographic Information Retrieval (GIR). GIR integrates GIScience, information extraction/retrieval, natural language processing (NLP), and spatial indexing/search for (geographic) data extraction, storage, analysis and visualization. While the overwhelming majority of all data in digital form exists as text, unstructured text has not been well-supported by either GIScience theories or existing GIS tools.

While computational, my approach to research and development is human-centered, from visual/system design to algorithm integration and evaluation, to domain deployment and field studies. My visualization-related work in the past couple of years has focused on visual analytics for human-in-the-loop machine learning aiming to (1) develop flexible, performant computational methods leveraging human expertise for dynamic situations (that do not lend themselves to one-off training/deployment), and (2) helping users understand machine learning methods output/biases when applied to geospatial data, falling under what is commonly known as explainable artificial intelligence. Examples include our recent projects on (a) human-in-the-loop learning of topic-relevance in social media data for real-time situational awareness, and (b) interactive feature exploration/selection in hyperspectral imagery using domain knowledge for building optimized regression methods for forecast precision agriculture.

I have developed visual analytics and GIR methods extracting and disambiguating place references in (social media) text in a scalable manner to support situational awareness in crisis management. My dissertation research culminated in two systems and one annotated dataset. Most notably, I developed GeoTxt, a geoparsing software that identifies and geolocates place references in text, which has been used by multiple research projects in various universities. In addition, I developed GeoAnnotator, an interactive semi-automatic annotation system for creating geo-labeled datasets for training/evaluation of machine learning models or spatial linguistics studies.

More recently, my text- and GIR-related work includes interactive learning of topic relevance in social media data, interactive identification of social (media) spambots and troll campaigns, geolocation estimation of social media posts, and developing spatio-textual embeddings for GIR.

More Info 

Prospective students: I am actively recruiting students. Please feel free to reach out to me with your CV, explaining how your research background and expertise may align with my work, and what areas you'd be interested in working on in the future. 

Recent Courses Taught 

• Spring 2024  GEOG 3023  Statistics and Geographic Data
• Spring 2024  GEOG 5100/PSYC 6831PSCI/SOCY 6851  Interdisciplinary Social Science Project Seminar
• Fall 2023  GEOG 3023  Statistics and Geographic Data
• Fall 2023  GEOG 4003/5100  Topics in Geographic Skills: Machine Learning & Spatial Data
• Fall 2023  GEOG 5100/PSYC 6831PSCI/SOCY 6851  Interdisciplinary Social Science Project Seminar
• Spring 2023  GEOG 3023  Statistics and Geographic Data
• Spring 2023  GEOG 5100/PSYC 6831PSCI/SOCY 6851  Interdisciplinary Social Science Project Seminar
• Fall 2022  GEOG 4003/5100  Topics in Geographic Skills: Machine Learning & Spatial Data
• Fall 2022  GEOG 4043/5043  Advanced Geovisualation and Web Mapping
• Fall 2021  GEOG 4003/5100  Topics in Geographic Skills: Machine Learning & Spatial Data
• Fall 2021  GEOG 4043/5043  Advanced Geovisualation and Web Mapping
• Spring 2021  GEOG 3023  Statistics and Geographic Data
• Fall 2020  GEOG 4003/5100  Topics in Geographic Skills: Spatial Data Science
• Fall 2020  GEOG 4203/5203  Geographic Information Science: Spatial Modeling
• Spring 2020  GEOG 3023  Statistics and Geographic Data
• Fall 2019  GEOG 3023  Statistics and Geographic Data