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Dr Vengadeswaran S

vidwan id: 594897
Male

Assistant Professor (Grade-II), Department of Computer Science and Engineering
Indian Institute of Information Technology, Kottayam

Expertise

  • Computer Science Software Engineering

Publications

Total Articles 11
Books 0
Proceedings 0

Publications

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Scopus

Citations 38
h-index 4

CrossRef

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Citations 17
h-index 3
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Bio

Computer Science and Engineering

Personal Details

  • Male
  • Assistant Professor (Grade-II) , Indian Institute of Information Technology, Kottayam
  • Department of Computer Science and Engineering, Indian Institute of Information Technology Kottayam
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Assistant Professor (Grade-II) Jul 2022 – Present
Indian Institute of Information Technology, Kottayam | Department of Computer Science and Engineering

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Co-Authors (3)

S R

Prof S R Balasundaram

National Institute of Technology Tiruchirappalli

Geetha

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S R M Institute of Science & Technology, Chennai

Scholarly Work

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Scholarly Publications

Software defect prediction using graph sample and aggregate-attention network optimized with nomadic people optimizer for enhancing the software reliability

Open Access
Article
Authors: Dhavakumar P.;Vengadeswaran S.

An Efficient Predictive Big Data Analytics for Supply Chain Demand Forecasting Through Ensemble Learning

Open Access
Conference Paper

GSHetero -Grouping and Heterogeneity-Aware Data Placement to Improve MapReduce Performance in Hadoop

Open Access
Article
Authors: Vengadeswaran S.;Dhavakumar P.;Viswanathan V.

IDaPS — Improved data-locality aware data placement strategy based on Markov clustering to enhance MapReduce performance on Hadoop

Open Access
Article

CLUST - Grouping aware data placement for improving the performance of large-scale data management system

Open Access
Conference Paper
Authors: Vengadeswaran S.;Balasundaram S.R.

CORE - An optimal data placement strategy in Hadoop for data intensive applications based on cohesion relation

Open Access
Article

An optimal data placement strategy for improving system performance of massive data applications using graph clustering

Open Access
Article

Significance of hierarchical and Markov clustering in grouping-aware data placement for data intensive applications with interest locality

Open Access
Article