AG

Peer-Reviewed Publications (* – Graduate Students)

JOURNALS

  1. Suryawanshi S.*, Goswami A., and Patil P., “CDA-PDDWE: Concept Drift-Aware Performance-Based Diversified Dynamic Weighted Ensemble for Non-stationary Environments“, Arabian Journal for Science and Engineering, Springer (2024).
    IF: 2.9
    DOI: 10.1007/s13369-024-08929-3
  2. Suryawanshi S.*, Goswami A., and Patil P., “FakeIDCA: Fake news detection with incremental deep learning based concept drift adaption“, Multimedia Tools and Applications, Springer (2023).
    IF: 3.6
    DOI: 10.1007/s11042-023-16588-z
  3. Kaliyar R., Goswami A., Narang P., and Chamola V., “Understanding the use and abuse of social media: Generalized fake news detection with a multichannel deep neural network“, IEEE Transactions on Computational Social Systems (2022).
    IF: 5.0
    DOI:    10.1109/TCSS.2022.3221811
  4. Choudhary T.*, Gurjar S., Mishra V., Goswami A., and Badal T., “Deep learning-based important weights-only transfer learning approach for COVID-19 CT-scan classification“, Applied Intelligence (2022).
    IF: 5.3
    DOI:     10.1007/s10489-022-03893-7
  5. Suryawanshi S.*, Goswami A., Patil P., and Mishra V., “Adaptive Windowing Based Recurrent Neural Network for Drift Adaption in Non-Stationary Environment“, Journal of Ambient Intelligence and Humanized Computing, Springer (2022).
    IF: 4.76
    DOI:     10.1007/s12652-022-04116-0
  6. Choudhary T.*, Mishra V., Goswami A., and Sarangapani J., “Inference-aware convolutional neural network pruning”, Future Generation Computer Systems (2022), Volume 135, Pages 44–56, Elsevier (2022).
    IF: 7.5
    DOI:     10.1016/j.future.2022.04.031
  7. Choudhary T.*, Mishra V., Goswami A., and Sarangapani J., “Heuristic-Based Automatic Pruning of Deep Neural Networks”, Neural Computing and Applications (2022), Issue 34, pages 4889–4903, Springer (2022).
    IF: 6.0
    DOI:     10.1007/s00521-021-06679-z
  8. Jain, V., Kaliyar, R.*, Goswami, A., Narang, P., and Sharma, Y., “AENeT: An Attention Enabled Neural Architecture for Fake News Detection using Contextual Features”, Neural Computing and Applications (2022), Volume 34, issue 1, pages 771–782, Springer.
    IF: 6.0
    DOI: 10.1007/s00521-021-06450-4
  9. Mishra, V., Dixit, M., Choudhary, T.*, Goswami, A., Kaur, M., Cheikhrouhou, O., and Hamam, H., “A Heuristic-Driven and Cost-Effective Majority/Minority Logic Synthesis for Post-CMOS Emerging Technologies”, IEEE Access, Volume 9, Pages 168689–168702, 2021.
    IF: 3.9
    DOI:     10.1109/ACCESS.2021.3079310
  10. Choudhary T.*, Mishra V., Goswami A., and Sarangapani J., “A Transfer Learning with Structured Filter Pruning Approach for Improved Breast Cancer Classification on Point-of-Care Devices“, Computers in Biology and Medicine, Vol. 134, Elsevier (2021).
    IF: 7.7
    DOI: 10.1016/j.compbiomed.2021.104432
  11. Kaliyar R.*, Goswami A., and Narang P., “EchoFakeD: Improving Fake News Detection in Social Media with An Efficient Deep Neural Network“, Neural Computing and Applications (2021), Volume 33, Issue 14, Pages 8597–8613, Springer (2021).
    IF: 6.0
    DOI: 10.1007/s00521-020-05611-1
  12. Kaliyar R.*, Goswami A., and Narang P., “FakeBERT: Fake News Detection in Social Media with a BERT-based Deep Learning Approach“, Multimedia Tools and Applications, Volume 80, Issue 8, Pages 11765–11788, Springer (2021).
    IF: 3.6
    DOI: 10.1007/s11042-020-10183-2
  13. Kaliyar R.*, Goswami A., and Narang P., “DeepFakE- Improving Fake News Detection using Tensor Decomposition-based Deep Neural Network“, The Journal of Supercomputing, Volume 77, Issue 2, Pages 1015–1037, Springer (2020).
    IF: 3.3
    DOI: 10.1007/s11227-020-03294-y
  14. Choudhary T.*, Mishra V., Goswami A., and Sarangapani J., “A Comprehensive Survey on Model Compression and Acceleration“, Artificial Intelligence Review, Volume 53, Issue 7, Pages 5113–5155, Springer (2020).
    IF: 12.0
    DOI: 10.1007/s10462-020-09816-7
  15. Kaliyar R.*, Goswami A., Narang P., and Sinha S., “FNDNet- A Deep Convolutional Neural Network for Fake News Detection”, Cognitive Systems Research, Volume 61, Pages 32-44, Elsevier (2020).
    DOI: 10.1016/j.cogsys.2019.12.005
    IF: 3.9
  16. Goswami A., Walia G., and Singh A., “Using Learning Styles of Software Professionals to Improve their Inspection Team Performance“, International Journal on Software Engineering and Knowledge Engineering, Volume 25, Issue 09n10, Pages 1721–1726, 2015.
    IF: 0.9
    DOI: 10.1142/S0218194015710060

CONFERENCES

  1. Suryawanshi S.*, Goswami A., and Patil P., “IRBM: Incremental Restricted Boltzmann Machines for Concept Drift Detection and Adaption in Evolving Data Streams”, 13th Proceedings of the 10th Springer International Advance Computing Conference, IAAC, 2023, Kolhapur, India, December 15–16, 2023.
    DOI: 10.1007/978-3-031-56700-1_37
  2. R. Kumar Kaliyar, A. Goswami, U. Sharma, K. Kanojia, and M. Agrawal., “HSDH: Detection of Hate Speech on social media with an effective deep neural network for code-mixed Hinglish data”, 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), Delhi, India, 2023, pp. 1-6.
    DOI: 10.1109/ICCCNT56998.2023.10306709
  3. Suryawanshi S.*, Goswami A., and Patil P., “Enhancing Drift Detection and Model Uncertainty Handling in Imbalanced Streaming Data Using Autoencoder-based Approach”, Proceedings of the 2nd IEEE International Conference on Smart Technologies for Smart Nation (SmartTechCon 2023), 18–19 August 2023, Singapore.
    DOI: 10.1109/SmartTechCon57526.2023.10391432
  4. Kaliyar, R.K., Goswami, A., Sharma, U., Kanojia, K., “ACDNet: Abusive Content Detection on Social Media with an Effective Deep Neural Network Using Code-Mixed Hinglish Data”, 12th Proceedings of the 10th Springer International Advance Computing Conference, IAAC, 2022.
    DOI: 10.1007/978-3-031-35644-5_22
  5. R. K. Kaliyar, M. Agrawal and A. Goswami, “FndIP: Fake News Detection on Social Media Using Incompatible Probabilistic Method,” 2022 International Conference on Inventive Computation Technologies (ICICT), Nepal, 2022, pp. 417–422.
    DOI: 10.1109/ICICT54344.2022.9850787
  6. N. Singh, R. K. Kaliyar, T. Vivekanand, K. Uthkarsh, V. Mishra, and A. Goswami, “B-LIAR: A novel model for handling Multiclass Fake News data utilizing a Transformer Encoder Stack-based architecture,” 2022 1st International Conference on Informatics (ICI), 2022, pp. 31–35.
    DOI: 10.1109/ICI53355.2022.9786925
  7. A. Garg, R. Kumar Kaliyar, and A. Goswami, “PDRSD-A systematic review on plan-driven SDLC models for software development”, 2022 8th International Conference on Advanced Computing and Communication Systems (ICACCS), 2022, pp. 739–744.
    DOI: 10.1109/ICACCS54159.2022.9785261
  8. Kaliyar, R.* Fitwe, R. P. and Goswami, A., “Classification of Hoax/NonHoax News Article Using an Effective Deep Neural Network”, Proceedings of the 5th IEEE International Conference on Computing Methodologies and Communication (ICCMC 2021) 08-10, April 2021, Tamil Nadu, India.
    DOI: 10.1109/ICCMC51019.2021.9418282
  9. Kaliyar R.*, Goswami A., and Narang P, “A Hybrid Model for Effective Fake News Detection with a Novel COVID-19”, Proceedings of the 13th International Conference on Agents and Artificial Intelligence (ICAART 2021), February 4-6, Vienna, Austria.
    DOI: 10.5220/0010316010661072
  10. Kaliyar R.*, Goswami A., and Narang P, “MCNNet: Generalizing Fake News Detection with a Multichannel Convolutional Neural Network using a Novel COVID-19 Dataset”, Proceedings of the ACM India Joint International Conference on Data Science and Management of Data (CODS-COMAD) 2021 (8th ACM IKDD CODS and 26th COMAD), January 2-4, Bangalore, India.
    DOI: 10.1145/3430984.3431064
  11. Asudani M., Mishra V., and Goswami A., “A 2D ResU-net Powered Segmentation of Thoracic Organs at Risk using Computed Tomography Images”, Proceedings of the 10th Springer International Advance Computing Conference IAAC 2020, December 5–6, Goa, Panaji, India.
    DOI: 10.1007/978-981-16-0401-0_4
  12. Suryawanshi S.*, Goswami A., and Patil P., “Incremental Ensemble of One class classifier for Data Streams with Concept drift adaption”, Proceedings of the 10th Springer International Advance Computing Conference IAAC 2020, December 5–6, Goa, Panaji, India.
    DOI: 10.1007/978-981-16-0401-0_31
  13. Choudhary T.*, Gurjar S., Panchal K., Sarvjeet, Mishra V., and Goswami A., “A deep learning-based transfer learning approach for the bird species classification”, Proceedings of the 10th Springer International Advance Computing Conference IAAC 2020, December 5–6, Goa, Panaji, India.
    DOI: 10.1007/978-981-16-0404-1_4
  14. Choudhary T.*, Mishra V., and Goswami A., “DualPrune: A dual purpose pruning of convolutional neural networks for resource-constrained devices”, Proceedings of the 10th Springer International Advance Computing Conference IAAC 2020, December 5–6, Goa, Panaji, India.
    DOI: 10.1007/978-981-16-0401-0_30
  15. Kaliyar R.*, Singh R., Sai L., Sudarshan M., Goswami A., and Garg, D., “RumEval2020-An Effective Approach for Rumour Detection with a Deep Hybrid C-LSTM Model”, Proceedings of the 10th Springer International Advance Computing Conference IAAC 2020, December 5–6, Goa, Panaji, India.
    DOI: 10.1007/978-981-16-0401-0_23
  16. Kaliyar R.*, Mohnot A., Raghul R., VK P., Goswami A., Singh N. and Dash P., “MultiDeepFake: Improving Fake News Detection with a Deep Convolutional Neural Network using a Multimodal Dataset”, Proceedings of the 10th Springer International Advance Computing Conference IAAC 2020, December 5-6, Goa, Panaji, India.
    DOI: 10.1007/978-981-16-0401-0_20
  17. Kaliyar R.*, Goswami A., and Narang P., “Multiclass Fake News Detection using Ensemble Machine Learning”, Proceedings of the 9th IEEE International Advance Computing Conference IAAC 2019, December 13–14, Tiruchirapalli, Tamil Nadu, India.
    DOI: 10.1109/IACC48062.2019.8971579
  18. Suryawanshi S.*, Goswami A., and Patil P., “Email Spam Detection: An Empirical Comparative Study of Different ML and Ensemble Classifiers“, Proceedings of the 9th IEEE International Advance Computing Conference IAAC 2019, December 13–14, Tiruchirapalli, Tamil Nadu, India.
    DOI: 10.1109/IACC48062.2019.8971582
  19. Kaliyar R.*, Narang P., and Goswami A., “SMS Spam Filtering on Multiple Background Datasets Using Machine Learning Techniques: A Novel Approach“, Proceedings of the 8th IEEE International Advance Computing Conference IAAC 2018, December 14–15, Greater Noida, India.
    DOI: 10.1109/IADCC.2018.8692097
  20. Singal G., Goswami A., Gupta S., and Choudhary T.*, “Pitfree: Pot-holes detection on Indian Roads Using Mobile Sensors“, Proceedings of the 8th IEEE International Advance Computing Conference IAAC 2018, December 14–15, Greater Noida, India.
    DOI: 10.1109/IADCC.2018.8692120
  21. Singh M., Walia G., and Goswami A., “Using Supervised Learning to Guide the Selection of Software Inspectors in Industry“, Proceedings of the 29th IEEE International Symposium on Software Reliability Engineering ISSRE 2018, October 15–18, Memphis, USA.
    DOI: 10.1109/ISSREW.2018.00-38
    Rank-A Conference
    BEST DISRUPTIVE IDEA AWARD RUNNER-UP
  22. Singh M., Vaibhav A., Walia G., and Goswami A., “Validating Requirements Reviews by Introducing Fault-Type Level Granularity: A Machine Learning Approach”, 11th ACM Innovations in Software Engineering Conference, ISEC 2018, Feb 9–11, Hyderabad, India.
    DOI: 1145/3172871.3172880
  23. Singh M., Walia G., and Goswami A., “An Empirical Investigation to Overcome Class-imbalance in Inspection Reviews”, IEEE International Conference on Machine Learning and Data Science, ICMLDS 2017, December 14–15, 2017, Greater Noida, India.
    DOI: 1109/MLDS.2017.15
  24. Singh M., Walia G., and Goswami A., “Validation of Inspection Reviews over Variable Features Set Threshold”, IEEE International Conference on Machine Learning and Data Science, ICMLDS 2017, December 14–15, 2017, Greater Noida, India.
    DOI:1109/MLDS.2017.16
  25. Goswami A., Walia G., McCourt M., and Padmanabhan G., “Improving the Requirements Inspection Abilities of Computer Science Students through Analysis of their Reading and Learning Styles“, 124th Annual ASEE Conference, June 25–28, 2017, Columbus, Ohio.
    DOI: 10.18260/1-2–28498
  26. Goswami, A, Walia G., “Teaching Software Inspections to Software Engineering Students through Practical Training and Reflection“, The ASEE Computers in Education (CoED) Journal 7.4 (2016): 2
  27. Goswami A., Walia G., and Rathod U. “Using Learning Styles to Staff and Improve Software Inspection Team Performance“, Proceedings of the 27th IEEE International Symposium on Software Reliability Engineering ISSRE 2016, October 23–27, Ottawa, Canada.
    DOI: 10.1109/ISSREW.2016.38
    Rank-A Conference
    BEST PAPER AWARD Nominee
  28. Goswami A., Walia G., McCourt M., and Padmanabhan G., “Using Eye Tracking to Investigate Reading Patterns and Learning Styles of Software Requirement Inspectors to Enhance Inspection Team Outcomes“, Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement ESEM 2016, September 8–9, Ciudad Real, Spain.
    DOI: 10.1145/2961111.2962598
    Rank-A Conference
  29. Goswami A., Walia G., “Teaching Software Inspections to Software Engineering Students through Practical Training and Reflection“, Proceedings of the 123rd American Society of Engineering Education Conference on Computer Education ASEE 2016, June 26–29, New Orleans, Louisiana, USA.
    DOI: 10.18260/p.26049
  30. Goswami A., Walia G., and Singh A., “Using Learning Styles of Software Professionals to Improve their Inspection Team Performance“, Proceedings of the 27th International Conference on Software Engineering and Knowledge Engineering, SEKE 2015. Pages 680–685, July 6–8, Pittsburgh, USA.
    DOI: 10.18293/SEKE2015-228
  31. Goswami A., Walia G., and Abufardeh S., “Using a Web-Based Testing Tool Repository in Programming Course: An Empirical Study”, Proceedings of the 10th WorldComp International Conference on Frontiers in Education: Computer Science and Computer Engineering, FECS 2014. Pages 43–49, July 21–24, Las Vegas, Nevada, USA.
  32. Goswami A., and Walia G., “Using Learning Styles to Improve Cost Effectiveness of Software Inspection Teams“, Proceedings of the 26th International Conference on Software Engineering and Knowledge Engineering, SEKE 2014. Pages 735-739, July 1–3, Vancouver, Canada.
  33. Goswami A., and Walia G., “An Empirical Study of the Effect of Learning Styles on the Faults found During the Software Inspection“, Proceedings of the 24th IEEE International Symposium on Software Reliability Engineering, ISSRE 2013. Pages 330–339, November 4–7, Pasadena, CA, USA.
    DOI: 10.1109/ISSRE.2013.6698886
    Rank A Conference
    BEST RESEARCH PAPER AWARD

Articles/Blogs