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Computer Science

D-Index
37
Citations
68536
World Ranking
10421
National Ranking
4346

Overview

Sameer Agarwal is affiliated with Google in the United States and works primarily in the engineering field. Their research spans several specialized areas, including computer vision and pattern recognition, media technology, general health professions, computational mechanics, and numerical analysis.

The core topics of Agarwal's work include advanced vision and imaging, image processing techniques and applications, sparse and compressive sensing techniques, advanced optimization algorithms research, machine learning and algorithms, robotics, and sensor-based localization, as well as hermeneutics and narrative identity.

Agarwal has contributed multiple papers to various scientific venues over recent years. The notable research publications include:

  • On the local stability of semidefinite relaxations, 2021, Mathematical Programming
  • The Chiral Domain of a Camera Arrangement, 2022, Journal of Mathematical Imaging and Vision
  • An Atlas for the Pinhole Camera, 2022, Foundations of Computational Mathematics
  • The Chiral Domain of a Camera Arrangement, 2020, arXiv (Cornell University)
  • Design and Implementation of Flight Computer for Sounding Rockets - S3FC, 2022, 2022 6th International Conference on Electronics, Communication and Aerospace Technology

Frequent coauthors who have collaborated with Agarwal in multiple publications include Rekha R. Thomas, Andrew Pryhuber, Rainer Sinn, Timothy Duff, and Shekhar Pathak.

Agarwal's work has appeared repeatedly in certain publication venues, highlighting an ongoing engagement with these platforms. These venues are:

  • arXiv (Cornell University)
  • 2022 6th International Conference on Electronics, Communication and Aerospace Technology
  • Mathematical Programming
  • Journal of Mathematical Imaging and Vision
  • Foundations of Computational Mathematics

Best Publications

  • A fast and elitist multiobjective genetic algorithm: NSGA-II

    K. Deb;A. Pratap;S. Agarwal;T. Meyarivan

  • Building Rome in a day

    Sameer Agarwal;Yasutaka Furukawa;Noah Snavely;Ian Simon

  • Building Rome in a day

    Sameer Agarwal;Noah Snavely;Ian Simon;Steven M. Seitz

  • Multicore bundle adjustment

    Changchang Wu;Sameer Agarwal;Brian Curless;Steven M. Seitz

  • BlinkDB: queries with bounded errors and bounded response times on very large data

    Sameer Agarwal;Barzan Mozafari;Aurojit Panda;Henry Milner

  • Bundle adjustment in the large

    Sameer Agarwal;Noah Snavely;Steven M. Seitz;Richard Szeliski

  • Higher order learning with graphs

    Sameer Agarwal;Kristin Branson;Serge Belongie

  • Scarlett: coping with skewed content popularity in mapreduce clusters

    Ganesh Ananthanarayanan;Sameer Agarwal;Srikanth Kandula;Albert Greenberg

  • Beyond pairwise clustering

    S. Agarwal;Jongwoo Lim;L. Zelnik-Manor;P. Perona

  • Structured importance sampling of environment maps

    Sameer Agarwal;Ravi Ramamoorthi;Serge Belongie;Henrik Wann Jensen

  • Jump: virtual reality video

    Robert Anderson;David Gallup;Jonathan T. Barron;Janne Kontkanen

  • Re-optimizing data-parallel computing

    Sameer Agarwal;Srikanth Kandula;Nicolas Bruno;Ming-Chuan Wu

  • Generalized Non-metric Multidimensional Scaling.

    Sameer Agarwal;Josh Wills;Lawrence Cayton;Gert R. G. Lanckriet

  • Knowing when you're wrong: building fast and reliable approximate query processing systems

    Sameer Agarwal;Henry Milner;Ariel Kleiner;Ameet Talwalkar

  • Devices that tell on you: privacy trends in consumer ubiquitous computing

    T. Scott Saponas;Jonathan Lester;Carl Hartung;Sameer Agarwal

  • Toward a perceptual space for gloss

    Josh Wills;Sameer Agarwal;David Kriegman;Serge Belongie

  • ShadowCuts: Photometric Stereo with Shadows

    M. Chandraker;S. Agarwal;D. Kriegman

  • Unsupervised Color Decomposition Of Histologically Stained Tissue Samples

    Andrew Rabinovich;Sameer Agarwal;Casey Laris;Jeffrey H. Price

  • Practical Global Optimization for Multiview Geometry

    Fredrik Kahl;Sameer Agarwal;Manmohan Krishna Chandraker;David Kriegman

  • Reconstructing Rome

    Sameer Agarwal;Yasutaka Furukawa;Noah Snavely;Brian Curless

  • BlinkDB: Queries with Bounded Errors and Bounded Response Times on Very Large Data

    Sameer Agarwal;Aurojit Panda;Barzan Mozafari;Samuel Madden

  • Learning from Incomplete Data

    Sameer Agarwal

Frequent Co-Authors

Serge Belongie
Serge Belongie University of Copenhagen
Ion Stoica
Ion Stoica University of California, Berkeley
Steven M. Seitz
Steven M. Seitz University of Washington
David J. Kriegman
David J. Kriegman University of California, San Diego
Noah Snavely
Noah Snavely Cornell University
Manmohan Chandraker
Manmohan Chandraker University of California, San Diego
Brian Curless
Brian Curless University of Washington
Srikanth Kandula
Srikanth Kandula Microsoft (United States)
Richard Szeliski
Richard Szeliski University of Washington

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