CS Graduate Student

Publications

2025

  1. Gaurav Srivastava, Shuxiang Cao, and Xuan Wang. “Towards Reasoning Ability of Small Language Models.” arXiv preprint arXiv:2502.11569 (2025). [arxiv] [leaderboard]

Before 2025

Journal Papers

  1. Gaurav Srivastava and Nitesh Pradhan. “Handling imbalanced class in melanoma: Kemeny–Young rule based optimal rank aggregation and Self-Adaptive Differential Evolution Optimization.” Engineering Applications of Artificial Intelligence, vol. 125, p. 106738, 2023. (impact factor: 8.0) [link] [pdf]

  2. Gaurav Srivastava, Aninditaa Chauhan, and Nitesh Pradhan. “Cjt-deo: Condorcet’s jury theorem and differential evolution optimization based ensemble of deep neural networks for pulmonary and colorectal cancer classification.” Applied Soft Computing, vol. 132, p. 109872, 2023. (impact factor: 8.3) [link] [pdf]

  3. Gaurav Srivastava, Nitesh Pradhan, and Yashwin Saini. “Ensemble of deep neural networks based on condorcet’s jury theorem for screening covid-19 and pneumonia from radiograph images.” Computers in Biology and Medicine, vol. 149, p. 105979, 2022. (impact factor: 7.7) [link] [pdf]

  4. Gaurav Srivastava, Aninditaa Chauhan, Nitigya Kargeti, Nitesh Pradhan, and Vijaypal Singh Dhaka. “ApneaNet: A hybrid 1DCNN-LSTM architecture for detection of Obstructive Sleep Apnea using digitized ECG signals.” Biomedical Signal Processing and Control, vol. 84, p. 104754, 2023. (impact factor: 5.1) [link] [pdf]

  5. Gaurav Srivastava, Aninditaa Chauhan, Mahesh Jangid, and Sandeep Chaurasia. “Covixnet: A novel and efficient deep learning model for detection of covid-19 using chest x-ray images.” Biomedical Signal Processing and Control, vol. 78, p. 103848, 2022. (impact factor: 5.1) [link] [pdf]

  6. Amitesh Kumar Dwivedi, Gaurav Srivastava, Sakshi Tripathi, and Nitesh Pradhan. “eFuseNet: A deep ensemble fusion network for efficient detection of Arrhythmia and Myocardial Infarction using ECG signals.” Multimedia Tools and Applications, pages 1-32, 2024. (impact factor: 3.0) [link] [pdf]

Conference Proceedings

  1. Gaurav Srivastava and Mahesh Jangid. “Multi-view sparse laplacian eigenmaps for nonlinear spectral feature selection.” 2023 International Conference on System Science and Engineering (ICSSE), IEEE, 2023, pp. 548–553. [link] [pdf]

  2. Amitesh Kumar Dwivedi, Gaurav Srivastava, and Nitesh Pradhan. “Nff: A novel nested feature fusion method for efficient and early detection of colorectal carcinoma.” Proceedings of Fourth International Conference on Computer and Communication Technologies, Springer, 2023, pp. 297–309. [link] [pdf]

  3. Ayush Singh, Gaurav Srivastava, and Nitesh Pradhan. “Pneumothorax segmentation using feature pyramid network and mobilenet encoder through radiography images.” International Conference on Soft Computing and Signal Processing, Springer, 2023, pp. 107–117. [link] [pdf]

  4. Rugved Sanjay Chavan, Gaurav Srivastava, and Nitesh Pradhan. “Advance plant health monitoring and forecasting system using edge-fog-cloud computing and lstm networks.” Proceedings of 3rd International Conference on Artificial Intelligence: Advances and Applications: ICAIAA 2022, Springer, 2023, pp. 335–344. [link] [pdf]

  5. Nitesh Pradhan, Saransh Gupta, and Gaurav Srivastava. “Image colorization: A convolutional network approach.” Proceedings of International Conference on Data Science and Applications: ICDSA 2022, Volume 2, Springer, 2023, pp. 533–544. [link] [pdf]

  6. Gaurav Srivastava, Aninditaa Chauhan, Mahesh Jangid, and Ashish Jain. “An analysis of deep learning models to diagnose covid-19 using radiography images.” 2022 International Conference for Advancement in Technology (ICONAT), IEEE, 2022, pp. 1–7. [link] [pdf]

Book Chapters

  1. Gaurav Srivastava, Devika Sapra, Akruti Sinha, Mahin Anup, and Deepak Sinwar. “Artificial intelligence and iot-assisted sustainable manufacturing for industry 4.0.” Computational Intelligence based Optimization of Manufacturing Process for Sustainable Materials, CRC Press, 2024, pp. 15–34. [link] [pdf]

  2. Akruti Sinha, Gaurav Srivastava, Devika Sapra, and Chhavi Deshlahra. “Fog computing for agriculture applications and its issues.” Bio-Inspired Optimization in Fog and Edge Computing Environments, Auerbach Publications, 2023, pp. 117–138. [link] [pdf]

  3. Akruti Sinha, Deepak Sapra, Gaurav Srivastava, Mahin Anup, and Deepak Sinwar. “AI-assisted big data analytics for smart healthcare systems.” Intelligent Internet of Things for Smart Healthcare Systems, CRC Press, 2023, p. 81. [link] [pdf]