Arpit Bhardwaj

About

Dr. Arpit Bhardwaj did his PhD from the Indian Institute of Technology Indore (IIT Indore) in December 2015. He did his M.E. from Shri Govindram Seksaria Institute of Technology and Science (SGSITS, Indore) in 2011. Currently he is working as an Assistant Professor in Bennett University. His research interests focus on Soft Computing Frameworks that are able to perform learning by handling real life ambiguous situations; more specifically these include Genetic Programming and Artificial Neural Networks and their applications in bioinformatics and medical diagnosis. In addition, he is also interested in creating soft computing algorithms scalable to address the problem of Big Data for classification and feature selection.

Employment

Employment history is unavailable.

Education

• Indian Institute of Technology Indore PhD
  2012 - 2015

Projects & Funding

Projects & funding information is unavailable.

Publications (10)

• A genetically optimized neural network model for multi-class classification
  Expert Systems with Applications 2016 42 citations DOI: 10.1016/j.eswa.2016.04.036
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• A novel genetic programming approach for epileptic seizure detection
  Computer Methods and Programs in Biomedicine 2016 63 citations DOI: 10.1016/j.cmpb.2015.10.001
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• An analysis of integration of hill climbing in crossover and mutation operation for EEG signal classification
  GECCO 2015 - Proceedings of the 2015 Genetic and Evolutionary Computation Conference 2015 20 citations DOI: 10.1145/2739480.2754710
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• Breast cancer diagnosis using Genetically Optimized Neural Network model
  Expert Systems with Applications 2015 251 citations DOI: 10.1016/j.eswa.2015.01.065
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• A genetically optimized neural network for classification of breast cancer disease
  Proceedings - 2014 7th International Conference on BioMedical Engineering and Informatics, BMEI 2014 2014 19 citations DOI: 10.1109/BMEI.2014.7002862
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• Classification of EEG signals using a novel genetic programming approach
  GECCO 2014 - Companion Publication of the 2014 Genetic and Evolutionary Computation Conference 2014 24 citations DOI: 10.1145/2598394.2609851
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• A novel genetic programming based classifier design using a new constructive crossover operator with a local search technique
  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2013 19 citations DOI: 10.1007/978-3-642-39479-9_11
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• Performance improvement in genetic programming using modified crossover and node mutation
  GECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference Companion 2013 10 citations DOI: 10.1145/2464576.2480787
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• Handling the problem of code bloating to enhance the performance of classifier designed using genetic programming
  Proceedings of the 5th Indian International Conference on Artificial Intelligence, IICAI 2011 2011
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• Removing code bloating in crossover operation in Genetic Programming
  International Conference on Recent Trends in Information Technology, ICRTIT 2011 2011 17 citations DOI: 10.1109/ICRTIT.2011.5972430
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