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Sanjeev Kumar

Researcher at Lovely Professional University

Publications -  1656
Citations -  62663

Sanjeev Kumar is an academic researcher from Lovely Professional University. The author has contributed to research in topics: Large Hadron Collider & Medicine. The author has an hindex of 113, co-authored 1325 publications receiving 54386 citations. Previous affiliations of Sanjeev Kumar include Indian Institute of Science & Boston Children's Hospital.

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Proceedings ArticleDOI

The PARSEC benchmark suite: characterization and architectural implications

TL;DR: This paper presents and characterizes the Princeton Application Repository for Shared-Memory Computers (PARSEC), a benchmark suite for studies of Chip-Multiprocessors (CMPs), and shows that the benchmark suite covers a wide spectrum of working sets, locality, data sharing, synchronization and off-chip traffic.
Journal ArticleDOI

Sensor networks: evolution, opportunities, and challenges

TL;DR: The history of research in sensor networks over the past three decades is traced, including two important programs of the Defense Advanced Research Projects Agency (DARPA) spanning this period: the Distributed Sensor Networks (DSN) and the Sensor Information Technology (SensIT) programs.
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Combined Measurement of the Higgs Boson Mass in pp Collisions at √s=7 and 8 TeV with the ATLAS and CMS Experiments

Georges Aad, +5120 more
TL;DR: A measurement of the Higgs boson mass is presented based on the combined data samples of the ATLAS and CMS experiments at the CERN LHC in the H→γγ and H→ZZ→4ℓ decay channels.
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GW190814: Gravitational Waves from the Coalescence of a 23 Solar Mass Black Hole with a 2.6 Solar Mass Compact Object

Richard J. Abbott, +1337 more
TL;DR: In this paper, the authors reported the observation of a compact binary coalescence involving a 222 −243 M ⊙ black hole and a compact object with a mass of 250 −267 M ⋆ (all measurements quoted at the 90% credible level) The gravitational-wave signal, GW190814, was observed during LIGO's and Virgo's third observing run on 2019 August 14 at 21:10:39 UTC and has a signal-to-noise ratio of 25 in the three-detector network.
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On the solution of population balance equations by discretization—II. A moving pivot technique

TL;DR: A new framework for the discretization of continuous population balance equations (PBEs) is presented and a numerical technique has been developed that is applicable to binary or multiple breakage, aggregation, simultaneous breakage and aggregation and yields excellent predictions in all cases.