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Dr Hari Singh

vidwan id: 229516
Male

Assistant Professor, Department of Computer Science and Engineering and Information Technology
Jaypee University of Information Technology, Waknaghat

Expertise

  • Computer Science Theory and Methods

Publications

Total Articles 26
Books 0
Proceedings 0

Publications

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Scopus

Citations 111
h-index 6

CrossRef

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Citations 83
h-index 6
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Professional Recognition

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Community & Membership

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Bio

Distributed & Parallel Computing, Machine Learning, Deep Learning, Natural Language Processing

Personal Details

  • Male
  • Assistant Professor , Jaypee University of Information Technology, Waknaghat
  • Jaypee University of Information Technology
Ph.D
Other Institute 2017
Assistant Professor Jul 2018 – Present
Jaypee University of Information Technology, Waknaghat | Department of Computer Science and Engineering and Information Technology

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Scholarly Work

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IMPROVING EXECUTION WORKLOADS IN IN-MEMORY DISTRIBUTED COMPUTING PLATFORM – SPARK

University Jaypee University of Information Technology
Year 2024
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Scholarly Publications

A Predictive Analysis of the COVID-19 Pandemic for Traditional and Tree-Based Regression Algorithms

Open Access
book chapter
Authors: Hari Singh, Piyush Sewal, and Dinesh Chander Verma

Performance Comparison of Apache Spark and Hadoop for machine learning based iterative GBTR on HIGGS and Covid-19 datasets

Open Access
article

Performance optimization of Spark MLlib workloads using cost efficient RICG model on exponential projective sampling

Open Access
article

Algorithmic Proficiency in Spark Configuration Tuning: An Empirical Study using Execution Time Metrics across Varied Workloads

Open Access
article

Comparison of Classification Algorithms for Alzheimer’s Disease Prediction

Open Access
conference paper
Authors: Harshit Saxena, Divyanshu Sharma, Hari Singh, and Rohit Anand

A feature extraction based improved sentiment analysis on Apache Spark for real-time twitter data

Open Access
article

Analyzing distributed Spark MLlib regression algorithms for accuracy, execution effciency and scalability using best subset selection approach

Open Access
article

A machine learning approach for predicting execution statistics of spark application

Open Access
conference paper