PRIYA SINGH

About

I am an Assistant Professor in the Deptartment of Software Engineering at Delhi Technological University. My expertise spans application of Deep Learning, Machine Learning, Natural Language processing, large Language Models and AI for Software Engineering.

Employment

• Oracle Software Engineer
  2018 - 2020
• Delhi Technological University Assistant Professor

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (22)

• A Unified Deep Learning Based Feature Representation Approach for Effective Software Defect Prediction
  Software: Practice and Experience 2026 DOI: 10.1002/spe.70081
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• Comparative Study of Machine Learning Based Defect Prediction Models for Python Software
  2025 DOI: 10.1109/ICIRCA65293.2025.11089647
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• Harnessing Tc-Ls-Ga-At: a novel deep learning based hybrid approach for wind power forecasting
  International Journal of System Assurance Engineering and Management 2025 DOI: 10.1007/s13198-025-02738-z
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• DHG-BiGRU: Dual-attention based hierarchical gated BiGRU for software defect prediction
  Information and Software Technology 2025 DOI: 10.1016/j.infsof.2024.107646
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• CodeBERT-BiGRU for Software Defect Prediction
  2025 DOI: 10.1007/978-3-031-91340-2_22
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• Deep AST-Based Approach for Software Defect Prediction: A Comparative Analysis
  2025 DOI: 10.1007/978-981-96-2647-2_31
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• Multi-objective hyperparameter optimization on gradient-boosting for breast cancer detection
  International Journal of System Assurance Engineering and Management 2024 DOI: 10.1007/s13198-023-01955-8
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• Generating Image Captions in Hindi Based on Encoder-Decoder Based Deep Learning Techniques
  Springer Series in Reliability Engineering 2024 DOI: 10.1007/978-3-031-55048-5_6
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• Empirical Validation of Deep Learning Based on Image Captioning Models
  Lecture Notes in Networks and Systems 2024 DOI: 10.1007/978-981-99-5015-7_38
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• Deep Learning Methods for Vehicle Trajectory Prediction: A Survey
  Lecture Notes in Networks and Systems 2024 DOI: 10.1007/978-981-99-6586-1_37
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