Projects

Development and calibration of a digital model of Princeton's stormwater drainage network using rainfall and flow observations. The model is used to investigate runoff behavior and evaluate green infrastructure and low-impact development strategies.

Related links:
GitHub repository

Development of a machine learning-based flood susceptibility model for Tashkent using topographic, rainfall, and land-use data. Random Forest classification and geospatial analysis were used to identify and map areas with elevated urban flood susceptibility.

Related links:
GitHub repository

Supported by the Princeton German Department Summer Work Program

Investigation of how agricultural systems can contribute to flood mitigation and disaster resilience. The project combined hydrologic and hydraulic modeling with analysis of disaster risk reduction frameworks and agricultural resilience strategies.

Hydrologic modeling was used to assess flood mitigation potential across agricultural landscapes, while comparative research examined how agricultural systems are incorporated into disaster risk reduction approaches in Germany and Japan.

Princeton International Internship Program (IIP)

Contributed to the development and testing of neutrally buoyant balloon-based tracers for studying atmospheric flows. Conducted quantitative experiments on helium retention and buoyancy stability, including evaluating Hi-Float gel treatments, and assisted with prototyping and testing components of a drone-mounted balloon-release mechanism.

Related publication:
Borra et al. (2026) — A Lagrangian Tracer System Using Balloons to Study Wind Farm Interactions with the Atmospheric Boundary Layer

Assisted with fieldwork supporting research on seedling establishment and forest restoration in Uzbekistan.

Related publication:
Azami et al. (2022) — Application of Nursery Block Seedlings in Uzbekistan: Prospects Based on Planting Trial Results