BANKSY: Spatial Clustering Algorithm that Unifies Cell-Typing and Tissue Domain Segmentation. Python package for spatial transcriptomics analysis.

Clustering spatial points with algorithm of Fast Search, high performace computing implements of CUDA or parallel in CPU, and runnable implements on python standalone or arcgis.

SnapLoc is a product that does automatic image classification and spatio-temporal analysis in order to recommend the places of interest in a new city. The packages that I have used for creating the product are Python(Pandas, NumPy, Shapely, Keras, Leaflet) and TensorFlow

Heterogeneous clustering and cross-modal evaluation metrics for crime prediction

CutESC: Cutting Edge Spatial Clustering Technique based on Proximity Graphs

DR.SC: Joint dimension reduction and spatial clustering for single-cell/spatial transcriptomics data

Python-Implementation of the Spatial Clustering Algorithm 'Supercluster' for ArcGIS and ArcPy.

This project analyses data from missing females in the USA. I have performed Exploratory Data Analysis(EDA), KMeans, and Spatial clustering.

Identifies Commercial Centers within the Jaipur city using Point of Interest (POI) spatial data of Jaipur, Rajasthan, India.

The Public Innovations Explorer: a geo-spatial and linked-data visualization platform for publicly funded innovation research in the United States

Spatiotemporal clustering algorithm for personal location data

SPACEGERM shiny app (archived, see GitLab for active fork)

Notebook of Goepp and van de Kassteele (2021)

This project highlights the critical relationship between substance use and mental health in the US using 2021 NSDUH data. Key findings show opioid use significantly impacts mental health, with the South and Midwest regions having the highest prevalence. Spatial analysis highlights clusters of misuse, offering insights to inform public health strat