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Computer Science

D-Index
77
Citations
119377
World Ranking
1226
National Ranking
648

Overview

David S. Johnson is affiliated with AT&T in the United States. Their research spans multiple fields including accounting, economics and econometrics, sociology and political science, signal processing, and gender studies. They have contributed to a range of topics such as financial literacy, pension and retirement analysis, gender, labor and family dynamics, consumer market behavior and pricing, economics of agriculture and food markets, monetary policy and economic impact, global health care issues, and policies related to energy, environment, and transportation.

Recent papers published by David S. Johnson include:

  • "Estimating the marginal propensity to consume using the distributions of income, consumption, and wealth," 2020, Journal of Macroeconomics
  • "Inequality in 3-D: Income, Consumption, and Wealth," 2021, Review of Income and Wealth
  • "DESED-FL and URBAN-FL: Federated Learning Datasets for Sound Event Detection," 2021, 2021 29th European Signal Processing Conference (EUSIPCO)
  • "Near-Optimal Disjoint-Path Facility Location Through Set Cover by Pairs," 2020, Operations Research
  • "Continuity and Change in U.S. Children's Family Composition, 1968-2017," 2022, Demography

Frequent co-authors working alongside David S. Johnson include Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, Edward Olivares, and Luke Pardue. Each of these collaborators has co-authored multiple publications with Johnson.

Key venues where Johnson's research is regularly published are:

  • SSRN Electronic Journal
  • Journal of Macroeconomics
  • Review of Income and Wealth
  • 2021 29th European Signal Processing Conference (EUSIPCO)
  • Operations Research

The scientist's work addresses interdisciplinary subjects combining quantitative methods and practical applications. For instance, their studies include robust approaches to inequality measurement, sound event detection via federated learning datasets, and optimization problems in facility location. Their research interests suggest a strong engagement with economic behavior and policy implications as well as technological applications in signal processing.

Best Publications

  • Computers and Intractability: A Guide to the Theory of NP-Completeness

    Michael R. Garey;David S. Johnson

  • A guide to the theory of np-completeness

    Michael Randolph Garey;David S. Johnson

  • The Complexity of Flowshop and Jobshop Scheduling

    M. R. Garey;D. S. Johnson;Ravi Sethi

  • Approximation algorithms for combinatorial problems

    David S. Johnson

  • Some simplified NP-complete problems

    M. R. Garey;D. S. Johnson;L. Stockmeyer

  • Some simplified NP-complete graph problems

    M. R. Garey;David S. Johnson;Larry J. Stockmeyer

  • Unit disk graphs

    Brent N. Clark;Brent N. Clark;Charles J. Colbourn;Charles J. Colbourn;David S. Johnson;David S. Johnson

  • Optimization by simulated annealing: an experimental evaluation. Part I, graph partitioning

    David S. Johnson;Cecilia R. Aragon;Lyle A. McGeoch;Catherine Schevon

  • The Rectilinear Steiner Tree Problem is $NP$-Complete

    M. R. Garey;David S. Johnson

  • Approximation algorithms for bin packing: a survey

    E. G. Coffman;M. R. Garey;D. S. Johnson

  • The NP-completeness column: An ongoing guide

    David S. Johnson

  • Worst-Case Performance Bounds for Simple One-Dimensional Packing Algorithms

    David S. Johnson;Alan J. Demers;Jeffrey D. Ullman;M. R. Garey

  • Optimization by Simulated Annealing: An Experimental Evaluation; Part II, Graph Coloring and Number Partitioning

    David S. Johnson;Cecilia R. Aragon;Lyle A. McGeoch;Catherine Schevon

  • Crossing Number is NP-Complete

    M. R. Garey;D. S. Johnson

  • On generating all maximal independent sets

    David S. Johnson;Christos H. Papadimitriou

  • How easy is local search

    David S. Johnson;Christos H. Papadimitriou;Mihalis Yannakakis

  • An Application of Bin-Packing to Multiprocessor Scheduling

    Edward G. Coffman;M. R. Garey;David S. Johnson

  • The Complexity of Multiterminal Cuts

    E. Dahlhaus;D. S. Johnson;C. H. Papadimitriou;P. D. Seymour

  • `` Strong '' NP-Completeness Results: Motivation, Examples, and Implications

    M. R. Garey;D. S. Johnson

  • A catalog of complexity classes

    David S. Johnson

Frequent Co-Authors

Michael Randolph Garey
Michael Randolph Garey Nokia (United States)
Christos H. Papadimitriou
Christos H. Papadimitriou Columbia University
Aggelos Kiayias
Aggelos Kiayias University of Edinburgh
Edward G. Coffman
Edward G. Coffman Columbia University
Richard Weber
Richard Weber University of Cambridge
Juan A. Garay
Juan A. Garay Texas A&M University
Ron Graham
Ron Graham University of California, San Diego
Andrew V. Goldberg
Andrew V. Goldberg Amazon (United States)
János Csirik
János Csirik University of Szeged

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