Orhun Aydin

Assistant Professor, Earth and Atmospheric Sciences, Saint Louis University
Assistant Professor (by courtesy), Computer Science , Saint Louis University

aydin_pic_small.png

Des Peres Hall 202C

3672 West Pine Mall

St. Louis, MO 63108

I am an Assistant Professor in the Department of Earth and Atmospheric Sciences and the Department of Computer Science (by courtesy) at Saint Louis University, where I direct the AI-CHESS Lab (Artificial Intelligence in Coupled Human-Environment Systems for Sustainability and Resilience).

I am also the founding Director of ADAPT-STL, a U.S. Department of Energy-funded Resilience Center (one of only 10 nationwide) focused on building a hybrid urban digital twin of St. Louis, deploying a hybrid weather station network, and advancing community-driven resilience planning.

My research spans GeoAI, sensor networks, spatial statistics, and computational sustainability. I spatial machine learning and graph-based methods for geospatial analysis, design IoT sensor systems for urban environmental monitoring, and use UAVs and satellite imagery for environmental mapping. Application domains include urban heat islands, green/blue carbon, plastic pollution, methane mapping, food-water-energy security, and climate resilience.

My recent funding includes awards from the U.S. Department of Energy, the National Science Foundation, NVIDIA, the Taylor Geospatial Institute, the R Consortium, and the EPA.

Prior to joining SLU, I served as a senior researcher and product engineer for the Spatial Statistics team at Esri. I hold a Ph.D. and M.Sc. in Geostatistics from Stanford University, an M.Sc. in Computer Science from Georgia Institute of Technology, and dual B.Sc. degrees in Petroleum Engineering and Electrical & Electronic Engineering from Middle East Technical University. I am an FAA-licensed drone pilot.

news

Feb 1, 2026 New paper published in Geothermics: “Predictive analytics and statistical time series imputation of subsurface temperatures for a campus-scale geothermal exchange field” — collaborative work with J.M. Tinjum, D. Fratta, and colleagues.
Dec 15, 2025 AI-CHESS Lab students present 6 papers at AGU Fall Meeting 2025 in New Orleans, covering urban heat islands, fallow field mapping, IoT waste sensors, urban tree mapping, and urban microclimate modeling.
Dec 1, 2025 New paper published in Applied Computing and Geosciences: “Graph-based evidence accumulation for clustering 3D orientation measurements in planetary surface mapping under relational constraints.”
Nov 1, 2025 AI-CHESS Lab co-authors 6 abstracts at ASN Kidney Week 2025, applying GeoAI methods to nephrology and kidney disease research in collaboration with the SLU School of Medicine.
Oct 1, 2025 Rockwood School District students Adithya Chengalvala and Satvik Seetharaman, mentored by Dr. Aydin, are selected for the AGU Bright STaRS program to present their research at AGU 2025. Read more.

latest posts

Jul 1, 2020 useR! 2020: arcgisbinding: An R package for integrating R in ArcGIS
May 14, 2020 Solutions to World’s Complex Problems: The Rise of Spatial Data Science
May 14, 2020 GeoAI and Pandemics: Spatial and Space-Time Data on COVID-19

research highlights

2025

  1. ACAG
    Graph-based evidence accumulation for clustering 3D orientation measurements in planetary surface mapping under relational constraints
    O. Aydin
    Applied Computing and Geosciences, 2025

2023

  1. skater_prob.png
    Probabilistic Regionalization via Evidence Accumulation with Random Spanning Trees as Weak Spatial Representations
    Orhun Aydin, Mark V Janikas, Renato Martins Assunção, and 1 more author
    Geographical Analysis, 2023

2022

  1. seagrass_cons.png
    Conservation planning implications of modeling seagrass habitats with sparse absence data: a balanced random forest approach
    Orhun Aydin, Carlos Osorio-Murillo, Kevin A Butler, and 1 more author
    Journal of Coastal Conservation, 2022

2021

  1. eartquake_opt_2021.png
    Quantifying the Impact of a Tsunami on Data-Driven Earthquake Relief Zone Planning in Los Angeles County via Multivariate Spatial Optimization
    Yueqi Gu, Orhun Aydin, and Jacqueline Sosa
    Geosciences, 2021

2020

  1. covid_gis.png
    Sensitivity analysis for covid-19 epidemiological models within a geographic framework
    Zhongying Wang, and Orhun Aydin
    In Proceedings of the 1st ACM SIGSPATIAL International Workshop on Modeling and Understanding the Spread of COVID-19, 2020

2018

  1. skater_con.png
    SKATER-CON: Unsupervised regionalization via stochastic tree partitioning within a consensus framework using random spanning trees
    Orhun Aydin, Mark V Janikas, Renato Assunçao, and 1 more author
    In Proceedings of the 2nd ACM SIGSPATIAL international workshop on AI for geographic knowledge discovery, 2018