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Shane G. Henderson

Shane G. Henderson

D-Index & Metrics

Computer Science

D-Index
38
Citations
4993
World Ranking
10376
National Ranking
4339

Overview

Shane G. Henderson is affiliated with Cornell University in the United States. Their research focuses on the intersection of computer science, management science, and operations research, with particular emphasis on simulation techniques and applications.

The scientific contributions of Henderson span multiple subfields, including Management Science and Operations Research, Modeling and Simulation, Infectious Diseases, Artificial Intelligence, and Computer Networks and Communications.

The main topics within Henderson's work cover:

  • Simulation Techniques and Applications
  • COVID-19 Epidemiological Studies
  • SARS-CoV-2 and COVID-19 Research
  • COVID-19 Digital Contact Tracing
  • Vaccine Coverage and Hesitancy
  • Healthcare Operations and Scheduling Optimization
  • Viral Infections and Outbreaks Research

Henderson has a considerable publication record, with recent papers including:

  • Modeling for COVID-19 College Reopening Decisions: Cornell, a Case Study, 2021, Proceedings of the National Academy of Sciences
  • SimOpt: A Testbed for Simulation-Optimization Experiments, 2023, INFORMS Journal on Computing
  • Minimizing Multimodular Functions and Allocating Capacity in Bike-Sharing Systems, 2022, Operations Research
  • Safe Blues: A Method for Estimation and Control in the Fight Against COVID-19, 2020, bioRxiv (Cold Spring Harbor Laboratory)
  • Diagnostic Tools for Evaluating and Comparing Simulation-Optimization Algorithms, 2023, INFORMS Journal on Computing

Key frequent co-authors in Henderson's research include:

  • David B. Shmoys
  • David J. Eckman
  • Peter I. Frazier
  • Jiayue Wan
  • Sara Shashaani

The venues where Henderson has most frequently published are:

  • INFORMS Journal on Computing
  • bioRxiv (Cold Spring Harbor Laboratory)
  • arXiv (Cornell University)
  • Proceedings of the National Academy of Sciences
  • Operations Research

Best Publications

  • Approximate Dynamic Programming for Ambulance Redeployment

    Matthew S. Maxwell;Mateo Restrepo;Shane G. Henderson;Huseyin Topaloglu

  • A Guide to Sample Average Approximation

    Sujin Kim;Raghu Pasupathy;Shane G. Henderson

  • Call Center Staffing with Simulation and Cutting Plane Methods

    Júlíus Atlason;Marina A. Epelman;Shane G. Henderson

  • Ambulance Service Planning: Simulation and Data Visualisation

    Shane G. Henderson;Andrew J. Mason

  • Optimizing Call Center Staffing Using Simulation and Analytic Center Cutting-Plane Methods

    Júlíus Atlason;Marina A. Epelman;Shane G. Henderson

  • Robust optimization for intensity modulated radiation therapy treatment planning under uncertainty.

    Millie Chu;Yuriy Zinchenko;Shane G Henderson;Michael B Sharpe

  • Behavior of the NORTA method for correlated random vector generation as the dimension increases

    Soumyadip Ghosh;Shane G. Henderson

  • Forecasting emergency medical service call arrival rates

    David S. Matteson;Mathew W. McLean;Dawn B. Woodard;Shane G. Henderson

  • Predicting Bike Usage for New York City's Bike Sharing System

    Divya Singhvi;Somya Singhvi;Peter I. Frazier;Shane G. Henderson

  • Travel time estimation for ambulances using Bayesian data augmentation

    Bradford S. Westgate;Dawn B. Woodard;David S. Matteson;Shane G. Henderson

  • Fairness and efficiency in web server protocols

    Eric J. Friedman;Shane G. Henderson

  • Two Issues in Setting Call Centre Staffing Levels

    Bert P. K. Chen;Shane G. Henderson

  • Input model uncertainty: Why do we care and what should we do about it?

    Shane G. Henderson

  • Erlang loss models for the static deployment of ambulances

    Mateo Restrepo;Shane G. Henderson;Huseyin Topaloglu

  • Chessboard Distributions and Random Vectors with Specified Marginals and Covariance Matrix

    Soumyadip Ghosh;Shane G. Henderson

  • BISECTION SEARCH WITH NOISY RESPONSES

    Rolf Waeber;Peter I. Frazier;Shane G. Henderson

  • A Spatio-Temporal Point Process Model for Ambulance Demand

    Zhengyi Zhou;David S. Matteson;Dawn B. Woodard;Shane G. Henderson

  • Large-network travel time distribution estimation for ambulances

    Bradford S. Westgate;Dawn B. Woodard;David S. Matteson;Shane G. Henderson

  • Minimizing Multimodular Functions and Allocating Capacity in Bike‐Sharing Systems

    Daniel Freund;Shane G. Henderson;David B. Shmoys

  • EFFICIENT RANKING AND SELECTION IN PARALLEL COMPUTING ENVIRONMENTS

    Eric Cao Ni;Dragos Florin Ciocan;Shane G. Henderson;Susan R. Hunter

  • Ambulance redeployment: an approximate dynamic programming approach

    Matthew S. Maxwell;Shane G. Henderson;Huseyin Topaloglu

Frequent Co-Authors

David B. Shmoys
David B. Shmoys Cornell University
Peter I. Frazier
Peter I. Frazier Cornell University
Peter W. Glynn
Peter W. Glynn Stanford University
Huseyin Topaloglu
Huseyin Topaloglu Cornell University
Lee W. Schruben
Lee W. Schruben University of California, Berkeley
Sean P. Meyn
Sean P. Meyn University of Florida
Barry L. Nelson
Barry L. Nelson Northwestern University
Russell R. Barton
Russell R. Barton Pennsylvania State University
Michael C. Fu
Michael C. Fu University of Maryland, College Park

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