Book Chapter

1. R. Parlikar, K. Bagali, V. S. Sreeraj, H. S. Shekhawat, G. Venkatasubramanian, Advancing Data Science: A New Ray of Hope to Mental Health Care. Exploration of Artificial Intelligence and Blockchain Technology in Smart and Secure Healthcare Advances in Computing Communications and Informatics (2024) 7: 199. Bentham Science Publisher.

Journal papers

1. Bhattacharjee, S., Mishra, J., Shekhawat, H. S., Jasuja, R., & Mahadeva Prasanna, S. R. (2025). Improving ASR Fairness for Cleft Lip and Palate Speech: A Study on Severity-Aware Augmentation. Speech Communication, 2026.

2. S. M. Mishra, S. Kundu, N. Y. Meitei, H. S. Shekhawat, and G. Trivedi, SpikeEdge: A Residual Spiking Neural Network Architecture with Edge-Based Data Encoding for Efficient Hardware Design, IEEE Trans. Very Large Scale Integr. (VLSI) Syst., 2026.

3.  B. N. Tripathi, H.S. Shekhawat, "Improved Error Bounds for the DEIM and Related Masked Projection Techniques", IEEE Control Letters, 2025. 

4. S. M. Mishra, H S Shekhawat, J Pidanic, G Trivedi, FPGA-Based Adaptive LIF Neuron for High-Speed, Energy-Efficient Spiking Neural Network,  IEEE Transactions on Circuits and Systems for Artificial Intelligence, 2025.

5. Deepika Gupta, H.S. Shekhawat, Artificial Bandwidth Extension using Frequency Shifting, H∞ Optimization,  and Deep Neural Network, Circuits, Systems, and Signal Processing, 2024.

6. S K Pandey, H S Shekhawat, S R M Prasanna, Multi-Cultural Speech Emotion Recognition using Language and Speaker Cues.  Biomedical Signal Processing and Control Journal. 2023

7.  H S. Shekhawat, Correlation and Subtraction, College Mathematics Journal. DOI: 10.1080/07468342.2022.2045151

8.  Deepika Gupta and H S Shekhawat, Artificial Bandwidth Extension Using Deep Neural Network and H∞ sampled-data control theory, Journal of Speech Communication, 2021, https://doi.org/10.1016/j.specom.2021.08.004

9.  Deepika Gupta, H S Shekhawat, R Sinha, A New Framework for Artificial Bandwidth Extension using H∞ Filtering,  Journal of Circuits, Systems, and Signal Processing. https://doi.org/10.1007/s00034-021-01925-0

10.  Sandeep Pandey, HS Shekhawat, SRM Prasanna, Attention Gated Neural Network Architectures for Speech Emotion Recognition,  Biomedical Signal Processing and Control Journal, 2022. https://doi.org/10.1016/j.bspc.2021.103173

11.  S K Pandey, H S Shekhawat, S R M Prasanna, S Bhasin,  R Jasuja, A deep tensor-based approach for automatic depression recognition from speech utterances, Plos one, 2022.

12. H. S. Shekhawat, Frequency Truncated Discrete-Time System Norm, in IEEE Control Systems Letters, vol. 4, no. 3, pp. 590-595, July 2020.

13.  H. S. Shekhawat and G. Meinsma. A sampled-data approach to optimal relaxed causal sampling. Mathematics of control, signals, and systems, vol. 33, pages 669–705 2021  doi.org/10.1007/s00498-021-00297-9 

14.  Deepika Gupta and H S Shekhawat, High-band Feature Extraction for Artificial Bandwidth Extension Using Deep Neural Network and H∞ optimisation. IET Signal Processing Journal, vol 14, no. 10, pp. 783-790, Dec 2020.

15.  H. S. Shekhawat and S. Weiland. A locally convergent Jacobi iteration for tensor decompositions. Multidimensional Systems and Signal Processing, 29(3), 1075-1094, 2018.

16. H. S. Shekhawat and G. Meinsma. A sampled-data approach to optimal non-causal downsampling. Mathematics of control, signals and systems, 27(3):277-315, 2015.

17. G. Meinsma and H. S. Shekhawat. Frequency-truncated system norms. Automatica, 47(8):1842-1845, 2011. doi:10.1016/j.automatica.2011.05.004

18.  B. N. Tripathi, H. S. Shekhawat, and S. Weiland. On the Equivalence of Classical and Multilinear DEIM on Tensor-Product Basis. Numerical algorithm (major Revision)

 Conference papers:

• 1. Susmita Bhattacharjee, Himashri Deka, H.S. Shekhawat , S. R. Mahadeva Prasanna. “Fairness Evaluation of Edge-AI Implementation for CLP speech ASR,”  IHCI, 2026, China.

  2. Kavya P. V. and Hanumant Singh Shekhawat, “A Graph Theoretic Interpretation of the Jacobian in the Tensor Singular Value Problem,” Proceedings of the International Conference on Numerical Analysis and Applied Mathematics (ICNAAM), 2026, Greece.

  3. V. S. Sapaharam, A. T. Abebe, A. Kumar, M. K. Saini, J. Pidanic, H. S. Shekhawat, and T. Boruvka, “Limited Transferability of IMU-Based Pothole Detection under Domain Shift,” in 2026 International Conference on New Trends in Signal Processing (NTSP 2026), 2026, Slovakia.

  4. Deka, H.; Vinodkumar, D. U.; Yadav, K. K.; Shekhawat, H. S. “Objective Schizophrenia Detection from Eye Movements via Blending Ensemble Learning.” In Proceedings of the 2026 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2026), Bangkok, Thailand, November 9–12, 2026 (accepted).

• 5. Majji, V. K.; Ramrakhiyani, H.; Shekhawat, H. S. “Audio Spectrogram Transformer for Speech Emotion Recognition on Indian Languages.” In Proceedings of the 2026 IEEE Guwahati Subsection Conference (GCON), IEEE, 2026, Guwahati, India.

  6. H. A. Ramrakhiyani, H. Deka, S. K. Pandey, N. S. Sreenivasalu, H. S. Shekhawat, and R. Jasuja, Audio Spectrogram Transformer for Automatic Speech-Based Depression Detection, 17th International Conference on Intelligent Human-Computer Interaction (IHCI-2025), Jaipur, India.

  7. S. M. Mishra, H. S. Shekhawat, and G. Trivedi, Temporal Data Encoding and On-Chip Training of an SNN for ECG Classification, Accepted in International Conference on VLSI Design (VLSID), Pune, 2026.

  8. S. Bhattacharjee, J. Mishra, H. S. Shekhawat, and S. R. M. Prasanna, Parameter-Efficient Fine-Tuning of Foundation Models for CLP Speech Classification, in Proc. 2025 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Singapore, 2025.

  9. H. A. Ramrakhiyani, H. Deka, S. K. Pandey, N. S. Sreenivasalu, H. S. Shekhawat, and R. Jasuja, Optimized Conv-LSTM Model for Analyzing Negative Affective State Vocalization in Dairy Cattle for an Edge Device, ICA 2025, IIT Guwahati, Guwahati, 2025.

  10. B. Tripathi, H. S. Shekhawat, Model Reduction of Dynamical Systems with Selection of States. 22nd International Conference on Numerical Analysis and Applied Mathematics, Greece 2024. 

  11.  H. A. Ramrakhiyani, S. K. Pandey, NS Shreenivasnalu, H. S. Shekhawat, R. Jasuja, Negative Affective State Vocalization Analysis of Dairy Cattle using 3D MFCC Features on CNN-LSTM Model using an Edge Device, ICA 2024, IIIT Delhi, New Delhi. 

  12. H S Shekhawat, Shodhan Rao, Nesterov Acceleration of the Jacobi Iteration for Tensor Singular Value Problems. 21st International Conference on Numerical Analysis and Applied Mathematics, Greece 2023.

  13. S. Bhattacharjee, H. S. Shekhawat, SRM Prasanna, Classification of Cleft Lip and Palate Speech using Fine-tuned Transformer Pretrained Models, IHCI-2023, South Korea.

  14. S K Pandey, M Nirgunkar, H S Shekhawat, A Longitudinal Study of the Emotional Content in Indian Political Speeches, IHCI-2022, Tashkent.

  15. D Gupta, H S Shekhawat. Artificial Bandwidth Extension Using H∞ Optimization, Deep Neural Network,and Speech Production Model, SPCOM, 2022, IISC Bangalore, India

  16. SM Mishra, HS Shekhawat, G Trivedi, P Jan, Z Nemec, "Design and Implementation of a Low Power Area Efficient Bfloat16 based CORDIC Processor", RADIOELEKTRONIKA-2022, Slovakia. 

  17. SM Mishra, A Tiwari, HS Shekhawat, P Guha, G Trivedi, P Jan, Z Nemec, "Comparison of Floating-point Representations for the Efficient Implementation of Machine Learning Algorithms", RADIOELEKTRONIKA-2022, Slovakia. 

  18. S K Pandey, H S Shekhawat, S Bhasin, R Jasuja, and S R M Prasanna, Alzheimer’s Dementia Recognition using Multimodal Fusion of Speech and Text Embeddings, IHCI-2021, Kent State University, USA. (Best paper runner up award for the overall conference)

  19. A Kumar, B J Choi, S K Pandey, S Park, S Choi, H S Shekhawat, W De Neve, M Saini, SRM Prasanna, and D Singh, “Exploring Multimodal Features and Fusion for Time-Continuous Prediction of Emotional Valence and Arousal,” Proc. International Conference on Intelligent Human Computer Interaction (IHCI), Kent, Ohio, USA, Dec. 2021. (Best session  paper award)

  20. Sharu Goel, Sandeep K Pandey, H S Shekhawat, Analysis of Emotional Content in Indian Political Speeches, IHCI2020, South Korea.

  21. D. Gupta, H.S. Shekhawat, Artificial Bandwidth Extension Using H∞ Optimization. Proc. Interspeech 2019, 3421-3425.

  22. B Sehgal,  H S Shekhawat, SK Jana. Automatic Radar Target Identification Using Radar Cross Section Fluctuations and Recurrent Neural Networks. Tencon 2019, India.

  23.  S Pandey,  H S Shekhawat, S R M Prasanna. Emotion Recognition from Raw Speech using Wavenet. Tencon 2019,  India

  24. S Pandey,  H S Shekhawat, S R M Prasanna. Deep Learning Techniques for Speech Emotion Recognition : A Review. Radioelektronika. 2019,  Czech Republic.

  25.  D Gupta, H S Shekhawat.  Artificial Bandwidth Extension Using the H ∞ Optimization and Speech Production Model.  Radioelektronika, 2019, Czech Republic.

  26. B Sehgal, H S Shekhawat, S K Jana. Automatic Target Recognition Using Recurrent Neural Networks. International Conference on Range Technology (ICORT),2019, India.

  27.  S Pandey, J Sarfaraz , S R M Prasanna, H S Shekhawat. Speaker Identification Using Tensor Decomposition of Acoustic Models. Tencon, 2018, South Korea. 

  28.  H. S. Shekhawat. Discrete frequency truncated system norm. In MTNS Symposium, July 2016, USA. 

  29.  H. S. Shekhawat and S. Weiland. A novel computational scheme for low rank approximations of tensors. ECC, 2015, Austria. 

  30.  H. S. Shekhawat and S. Weiland. On the problem of low-rank approximation of tensors. In MTNS Symposium, 2014, Netherlands. 

  31.  H. S. Shekhawat and G. Meinsma. L 2 and L∞ optimal downsampling from system theoretic viewpoint. In MTNS Symposium, 2012, Australia.  

  32.  H. S. Shekhawat and G. Meinsma. Optimal relaxed causal sampler using sampled-data system theory. In MTNS Symposium, 2012, Australia. 

  33.  G.Meinsma and H. S. Shekhawat. Truncated norms and limitations on signal reconstruction. In MTNS Symposium, 2010, Hungary.