Publications

[B4] Swagarika Giri, Nabil Ibtehaz, Lukasz Kurgan, & Daisuke Kihara, Identifying hidden moonlighting proteins and protein regions, Cryptic Enzymes and Moonlighting Proteins. H. Irving, C. Gehring, & A. Wong (eds), Chapter 13, pp.257-276, Academic Press (2025)

[J24] Kagaya, Y., Zhang, Z., Ibtehaz, N., Wang, X., Nakamura, T., Punuru, P. D., & Kihara, D. (2025). NuFold: end-to-end approach for RNA tertiary structure prediction with flexible nucleobase center representation. Nature communications, 16(1), 881.

[W3] Ibtehaz, N., Yan, N., Mortazavi, M., & Kihara, D. (2024). Fusion of regional and sparse attention in Vision Transformers. In CVPR 2024 Workshop on Workshop on Transformers for Vision (T4V).

[W2] Ibtehaz, N., & Mortazavi, M. (2024). Modally Reduced Representation Learning of Multi-Lead ECG Signals through Simultaneous Alignment and Reconstruction. In ICLR 2024 Workshop on Learning from Time Series For Health (TS4H).

[P5] Farheen, F., Broyles, B. K., Zhang, Y., Ibtehaz, N., Erkine, A. M., & Kihara, D. (2024). Predicting transcriptional activation domain function using Graph Neural Networks. bioRxiv.

[J23] Gaben, S. S. M., Abughanam, N., Ibtehaz, N., Mahmud, S., Al Noaimi, G., Alqahtani, A., ... & Chowdhury, M. E. (2024). ExoventQ: A novel low-cost portable negative pressure ventilator design and implementation. IEEE Access.

[J22] Giri, S. J., Ibtehaz, N., & Kihara, D. (2024). GO2Sum: generating human-readable functional summary of proteins from GO terms. npj Systems Biology and Applications, 10(1), 29.

[P3] Ibtehaz, N., Yan, N., Mortazavi, M., & Kihara, D. (2024). ACC-ViT: Atrous Convolution's Comeback in Vision Transformers. arXiv preprint arXiv:2403.04200.

[J21] Ibtehaz, N., Kagaya, Y., & Kihara, D. (2023). Domain-PFP allows protein function prediction using function-aware domain embedding representations. Communications Biology, 6(1), 1103.

[C4] Ibtehaz, N., & Kihara, D. (2023, October). Acc-unet: A completely convolutional unet model for the 2020s. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 692-702). Cham: Springer Nature Switzerland.

[J20] Ibtehaz, N., Chowdhury, M. E., Khandakar, A., Kiranyaz, S., Rahman, M. S., & Zughaier, S. M. (2023). RamanNet: a generalized neural network architecture for Raman spectrum analysis. Neural Computing and Applications, 35(25), 18719-18735.

[J19] Ibtehaz, N., Sourav, S. S. H., Bayzid, M. S., & Rahman, M. S. (2023). Align-gram: rethinking the skip-gram model for protein sequence analysis. The Protein Journal, 42(2), 135-146.

[J18] Mahmud, S., Ibtehaz, N., Khandakar, A., Rahman, M. S., Gonzales, A. J., Rahman, T., ... & Chowdhury, M. E. (2023). NABNet: A Nested Attention-guided BiConvLSTM network for a robust prediction of Blood Pressure components from reconstructed Arterial Blood Pressure waveforms using PPG and ECG signals. Biomedical Signal Processing and Control, 79, 104247.

[B3] Ibtehaz, N., & Kihara, D. (2023). Application of sequence embedding in protein sequence-based predictions. In Machine learning in bioinformatics of protein sequences: algorithms, databases and resources for modern protein bioinformatics(pp. 31-55).

[J17] Ibtehaz, N., Mahmud, S., Chowdhury, M. E., Khandakar, A., Salman Khan, M., Ayari, M. A., ... & Rahman, M. S. (2022). PPG2ABP: Translating photoplethysmogram (PPG) signals to arterial blood pressure (ABP) waveforms. Bioengineering, 9(11), 692.

[B2] Chowdhury, M. E., Khandaker, A., Qiblawey, Y., Haque, F., Ezeddin, M., Rahman, T., Ibtehaz, N. ... & Islam, K. R. (2022). Future techniques and perspectives on implanted and wearable heart failure detection devices. Predicting Heart Failure: Invasive, Non‐Invasive, Machine Learning and Artificial Intelligence Based Methods, 295-319.

[J16] Rahman, T., Ibtehaz, N., Khandakar, A., Hossain, M. S. A., Mekki, Y. M. S., Ezeddin, M., ... & Chowdhury, M. E. (2022). QUCoughScope: an intelligent application to detect COVID-19 patients using cough and breath sounds. Diagnostics, 12(4), 920.

[J15] Farheen, F., Shamil, M. S., Ibtehaz, N., & Rahman, M. S. (2022). Revisiting segmentation of lung tumors from CT images. Computers in Biology and Medicine, 144, 105385. 

[J14] Rahman, A., Chowdhury, M. E., Khandakar, A., Tahir, A. M., Ibtehaz, N., Hossain, M. S., ... & Kadir, M. A. (2022). Robust biometric system using session invariant multimodal EEG and keystroke dynamics by the ensemble of self-ONNs. Computers in Biology and Medicine, 142, 105238.

[J13] Zzaman, R. U., Nowreen, S., Khan, I. M., Islam, M. R., Ibtehaz, N., Rahman, M. S., ... & Rahman, M. S. (2022). A Machine Learning-based Approach for Groundwater Mapping. Natural Resources Research, 1-19.

[J12] Mahmud, S., Ibtehaz, N., Khandakar, A., Tahir, A. M., Rahman, T., Islam, K. R., ... & Chowdhury, M. E. (2022). A shallow U-Net architecture for reliably predicting blood pressure (BP) from photoplethysmogram (PPG) and electrocardiogram (ECG) signals. Sensors, 22(3), 919.

[P2] Afshar, P., Mohammadi, A., Plataniotis, K.N., Farahani, K., ...  Ibtehaz, N. .... , , Dev, C. and Haque, M.A., 2022. Lung-Originated Tumor Segmentation from Computed Tomography Scan (LOTUS) Benchmark. arXiv preprint arXiv:2201.00458.

[J11] Yang, Y., Xu, B., Haverstick, J., Ibtehaz, N., Muszyński, A., Chen, X., Chowdhury, M.E., Zughaier, S.M. and Zhao, Y., 2022. Differentiation and classification of bacterial endotoxins based on surface enhanced Raman scattering and advanced machine learning. Nanoscale, 14(24), pp.8806-8817.

[C3] Ibtehaz, N., & Naznin, M. (2021, December). Determining Confused Brain Activity from EEG Sensor Signals. In Proceedings of the 8th International Conference on Networking, Systems and Security (pp. 91-96).

[J10] Ibtehaz, N., Chowdhury, M. E., Khandakar, A., Kiranyaz, S., Rahman, M. S., Tahir, A., ... & Rahman, T. (2021). EDITH: ECG biometrics aided by deep learning for reliable individual authentication. IEEE Transactions on Emerging Topics in Computational Intelligence, 6(4), 928-940.

[J9] Tahir, A.M., Chowdhury, M.E., Khandakar, A., Rahman, T., Qiblawey, Y., Khurshid, U., Kiranyaz, S., Ibtehaz, N., Rahman, M.S., Al-Maadeed, S. and Mahmud, S., 2021. COVID-19 infection localization and severity grading from chest X-ray images. Computers in biology and medicine, 139, p.105002.

[J8] Hoque, I. T., Ibtehaz, N., Chakravarty, S., Rahman, M. S., & Rahman, M. S. (2021). A contour property based approach to segment nuclei in cervical cytology images. BMC Medical Imaging, 21, 1-12.

[J7] Ibtehaz, N., Ahmed, I., Ahmed, M. S., Rahman, M. S., Azad, R. K., & Bayzid, M. S. (2021). SSG-LUGIA: single sequence based genome level unsupervised genomic Island prediction algorithm. Briefings in Bioinformatics, 22(6), bbab116.

[J6] Rahman, T., Khandakar, A., Hoque, M.E., Ibtehaz, N., Kashem, S.B., Masud, R., Shampa, L., Hasan, M.M., Islam, M.T., Al-Maadeed, S. and Zughaier, S.M., 2021. Development and validation of an early scoring system for prediction of disease severity in COVID-19 using complete blood count parameters. Ieee Access, 9, pp.120422-120441.

[J5] Qiblawey, Y., Tahir, A., Chowdhury, M.E., Khandakar, A., Kiranyaz, S., Rahman, T., Ibtehaz, N., Mahmud, S., Maadeed, S.A., Musharavati, F. and Ayari, M.A., 2021. Detection and severity classification of COVID-19 in CT images using deep learning. Diagnostics, 11(5), p.893.

[B1] Chowdhury, M. E., Rahman, T., Khandakar, A., Ibtehaz, N., Khan, A. U., Khan, M. S., ... & Ali, S. H. M. (2021). Tomato leaf diseases detection using deep learning technique. Technology in Agriculture, 453.

[W1] Tomar, N. K., Ibtehaz, N., Jha, D., Halvorsen, P., & Ali, S. (2021, April). Improving Generalizability in Polyp Segmentation using Ensemble Convolutional Neural Network. In ISBI 2021 Workshop on Computer Vision in Endoscopy (EndoCV) (pp. 49-58).

[J4] Shamil, M. S., Farheen, F., Ibtehaz, N., Khan, I. M., & Rahman, M. S. (2021). An agent-based modeling of COVID-19: validation, analysis, and recommendations. Cognitive computation, 1-12.

[J3] Ibtehaz, N., Kaykobad, M., & Rahman, M. S. (2021). Multidimensional segment trees can do range updates in poly-logarithmic time. Theoretical Computer Science, 854, 30-43.

[J2] Ibtehaz, N., & Rahman, M. S. (2020). MultiResUNet: Rethinking the U-Net architecture for multimodal biomedical image segmentation. Neural networks, 121, 74-87.  

[J1]  Ibtehaz, N., Rahman, M. S., & Rahman, M. S. (2019). VFPred: A fusion of signal processing and machine learning techniques in detecting ventricular fibrillation from ECG signals. Biomedical Signal Processing and Control, 49, 349-359.

[P1] Ibtehaz, N., Ahmed, S., Saha, B., Rahman, M. S., & Bayzid, M. S. (2019). NORTH: a highly accurate and scalable Naive Bayes based ORTHologous gene clustering algorithm. bioRxiv, 528323.

[C2] Ibtehaz, N., Haque, M. S. U., Shaan, M. N., Hoque, A. H., Dipta, A. S., Rahman, A., ... & Bhattacharjee, A. (2018, December). IMPACT: Image processing based Maze solver, Persistent Autonomous object Carrying boT. In 2018 10th International Conference on Electrical and Computer Engineering (ICECE) (pp. 197-200). IEEE.

[C1] Al-Hussaini, I., Humayun, A.I., Alam, S., Foysal, S.I., Al Masud, A., Mahmud, A., Chowdhury, R.I., Ibtehaz, N., Zaman, S.U., Hyder, R. and Chowdhury, S.S., 2018, April. Predictive real-time beat tracking from music for embedded application. In 2018 IEEE Conference on multimedia information processing and retrieval (MIPR) (pp. 297-300). IEEE.

1. Method and apparatus for monitoring physical activity

US20210279554A1 , WO2021177694A1 , KR20210111948A · Filed Feb 26, 2021

2. Wearable device and method for controlling therefor (웨어러블 장치 및 그 제어 방법)

US20230229260A1, WO2022065682A1 , KR20220040277A · Filed Sep 23, 2020

3. Electronic apparatus and controlling method therefor (전자 장치 및 그 제어 방법)

US20230205923A1, WO2022050558A1 , KR20220029212A · Filed Jun 29, 2023

4. Electronic apparatus and controlling method thereof

US20230164482A1, WO2023096085A1, KR20230075908A · Filed Oct 12, 2022

5. Audio-visual information system for smart eyewear  

WO2024031109A2 · Filed Feb 08, 2024