Peter K. Kitanidis

About

Peter K. Kitanidis is a Professor of Civil and Environmental Engineering at Stanford University. His research develops methods for the solution of interpolation and inverse problems utilizing observations and mathematical models of flow and transport. He studies dilution and mixing of soluble substances in heterogeneous geologic formations, issues of scale in mass transport in heterogeneous porous media, and techniques to speed up the decay of pollutants in situ. Additionally, he develops methods for hydrologic forecasting and the optimization of sampling and control strategies. Kitanidis holds a Dipl. from the National Technical University of Athens in Civil Engineering, obtained in 1974, a Master's degree from MIT in Civil Engineering earned in 1976, and a PhD from MIT in Water Resources completed in 1978.

Research topics

• Computer Science
• Artificial Intelligence
• Geology
• Geography
• Geotechnical engineering
• Mathematics
• Algorithm
• Data Mining
• Environmental science
• Soil science

Selected publications

• Hydrogeophysical Characterization of Nonstationary DNAPL Source Zones by Integrating a Convolutional Variational Autoencoder and Ensemble Smoother

  Water Resources Research · 2021 · 65 citations

  Abstract Detailed characterization of dense nonaqueous phase liquid (DNAPL) source zone architecture (SZA) is essential for designing efficient remediation strategies. However, it is difficult to characterize a highly irregular and localized SZA, because traditional drilling investigations provide limited information. With limited data, the estimation accuracy of traditional geostatistical methods is strongly affected by the parameterization of the prior description of the SZA. To improve charac…

  DOI

• Integrating deep learning-based data assimilation and hydrogeophysical data for improved monitoring of DNAPL source zones during remediation

  Journal of Hydrology · 2021 · 39 citations

  DOI

• Deep learning technique for fast inference of large-scale riverine bathymetry

  Advances in Water Resources · 2020 · 35 citations

  Senior authorCorresponding
  DOI

• Hierarchical Bayesian Inversion of Global Variables and Large‐Scale Spatial Fields

  Water Resources Research · 2022-04-11 · 17 citations

  articleOpen access

  Abstract Bayesian inversion is commonly applied to quantify uncertainty of hydrological variables. However, Bayesian inversion is usually focused on spatial hydrological properties instead of hyperparameters or non‐gridded physical global variables. In this paper, we present a hierarchical Bayesian framework to quantify uncertainty of both global and spatial variables. We estimate first the posterior of global variables and then hierarchically estimate the posterior of the spatial field. We prop…

  PublisherOA PDFDOI

• Routing algorithms as tools for integrating social distancing with emergency evacuation

  Scientific Reports · 2021-10-04 · 15 citations

  articleOpen access

  One of the lessons from the COVID-19 pandemic is the importance of social distancing, even in challenging circumstances such as pre-hurricane evacuation. To explore the implications of integrating social distancing with evacuation operations, we describe this evacuation process as a Capacitated Vehicle Routing Problem (CVRP) and solve it using a DNN (Deep Neural Network)-based solution (Deep Reinforcement Learning) and a non-DNN solution (Sweep Algorithm). A central question is whether Deep Rein…

  PublisherOA PDFDOI

Recent grants

• CMG Collaborative Research: Subsurface Imaging and Uncertainty Quantification.

  NSF · $355k · 2009–2013

• Collaborative Research: Fundamental Research on Oscillatory Flow in Hydrogeology

  NSF · $226k · 2012–2015

• Nonequilibrium Transport and Transport-Controlled Reactions

  NSF · $380k · 2008–2012

Frequent coauthors

• Craig S. Criddle

  78 shared

• Jian Luo

  Georgia Institute of Technology

  76 shared

• David B. Watson

  70 shared

• Wei‐Min Wu

  69 shared

• Philip M. Jardine

  67 shared

• Tonia L. Mehlhorn

  62 shared

• Jack Carley

  Oak Ridge National Laboratory

  59 shared

• Jizhong Zhou

  Tsinghua University

  47 shared

Education

• Ph.D., Hydrology

  Stanford University

  1987

• M.S., Hydrology

  Stanford University

  1984

• B.S., Civil Engineering

  University of California, Berkeley

  1982

Similar researchers at Stanford University

• Mark Z. Jacobsonh-133
• William Mitchh-72
• Stephen Monismithh-71