Ankit Thakkar

About

Dr Ankit Thakkar is working as a Professor at the Department of Computer Science and Engineering, Institute of Technology, Nirma University. Dr Thakkar has more than 19 years of teaching experience. He received his BE degree in Computer Engineering from North Gujarat University, MTech and PhD degree in Computer Science and Engineering from Nirma University, Ahmedabad, in 2002, 2009, and 2014, respectively. His research interests include Computational Intelligence Techniques, Wireless Sensor Networks, Machine Learning and its Applications, and Network Security. He has published several research papers in international journals and conferences. He is an Associate Editor for Swarm and Evolutionary Computation. He has been a reviewer for many international journals and conferences. He received the Gold Medal for securing the highest CPI among all graduating 2007 to 2009 batch MTech students of Computer Science and Engineering Branch, Institute of Technology, Nirma University. He is a recognized PhD guide at Nirma University and three out of four PhD candidates have completed their PhD under his guidance. He is a Life Member of ISTE, a Senior Member of IEEE, and a member of ACM.

Employment

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Education

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Publications (53)

• A survey of machine learning and deep learning methods for vibration-based Bearing fault diagnosis: The need, challenges, and potential future research directions
  Neurocomputing 2026 DOI: 10.1016/j.neucom.2025.131628
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• PANS: A novel polarity-adjusted noise scaling approach for privacy-preserving sentiment analysis in federated learning
  Knowledge-Based Systems 2026 DOI: 10.1016/j.knosys.2026.115348
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• Fusion of linear and non-linear dimensionality reduction techniques for feature reduction in LSTM-based Intrusion Detection System
  Applied Soft Computing 2024 DOI: 10.1016/j.asoc.2024.111378
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• Applicability of genetic algorithms for stock market prediction: A systematic survey of the last decade
  Computer Science Review 2024 DOI: 10.1016/j.cosrev.2024.100652
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• Attack Classification of Imbalanced Intrusion Data for IoT Network Using Ensemble-Learning-Based Deep Neural Network
  IEEE Internet of Things Journal 2023 DOI: 10.1109/JIOT.2023.3244810
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• Neural network systems with an integrated coefficient of variation-based feature selection for stock price and trend prediction
  Expert Systems with Applications 2023 DOI: 10.1016/j.eswa.2023.119527
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• Data fusion with factored quantization for stock trend prediction using neural networks
  Information Processing & Management 2023 DOI: 10.1016/j.ipm.2023.103293
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• Fusion of statistical importance for feature selection in Deep Neural Network-based Intrusion Detection System
  Information Fusion 2022 DOI: 10.1016/j.inffus.2022.09.026
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• Improving the Performance of Sentiment Analysis Using Enhanced Preprocessing Technique and Artificial Neural Network
  IEEE Transactions on Affective Computing 2022 DOI: 10.1109/TAFFC.2022.3206891
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• Information fusion-based genetic algorithm with long short-term memory for stock price and trend prediction
  Applied Soft Computing 2022 DOI: 10.1016/j.asoc.2022.109428
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