Mumenin N., Yousuf M.A., Nashiry M.A., Azad A,K.M., Alyemi S.A., Lio P., Moni M.A. (2023). ASDNet: A Robust Involution‑based Novel Architecture of Eye‑tracking based Diagnosis for Autism Spectrum Disorder. IET Computer Vision (Scopus Indexed, Q3).
Ghosh T., Abedin M. M.H.Z., Al Banna M.H., Mumenin N., Yousuf M.A. (2020). Performance Analysis of State of the Art Convolutional Neural Network Architectures in Bangla Handwritten Character Recognition. PATTERN RECOGNITION AND IMAGE ANALYSIS, 31. Springer (Scopus Indexed, Q2).
Mumenin N., Hossain ABM. K, Hossain M.A., Debnath P.P., Della M.N., Rashed M.M.H., Hossen A., Basar M.R., Hossain M.S (2024). Screening Depression Among University Students Utilizing GHQ‑12 and Machine Learning. Heliyon (Scopus Indexed, Q1).
Akhi, A.J., Rani, F. P., Mumenin, N., & Hossain, ABM. K. (2024, December). An Explainable Ensemble Model for Depression Detection from Social Platform Data. In 27th International Conference on Computer and Information Technology (ICCIT), December 2024, Cox’s Bazar, Bangladesh. IEEE. (Accepted)
Mumenin, N. (2023, September). Suicidal Ideation Detection from Social Media Texts Using an Interpretable Hybrid Model. 6th International Conference on Electrical Information and Communication Technology. in 6th International Conference on Electrical Information and Communication Technology (EICT), IEEE.
Mumenin, N., Islam, F., Zaman, R. and Yousuf, M.A., 2022 Diagnosis of Autism Spectrum Disorder Through Eye Movement Tracking Using Deep Learning. In 2022 1st International Conference on Information and Communication Technology for Development (ICICTD). Springer, Singapore.
Hussain, N., Hossain, M. A., Mumenin, N., & Snigdho, A. S. A. (2022, December). Characteristics of Energy in the Coulomb Island of Single Electron Transistor. In 2022 International Conference on Recent Progresses in Science, Engineering and Technology (ICRPSET) (pp. 1‑5). IEEE.
Singha, A., Mumenin, N., Akhter, N.I. and Ahmed, M.U., 2021, September. A New Stegano‑Cryptographic Approach for Enhancing Text Data Communication Security. In 2021 International Conference on Electronics, Communications and Information Technology (ICECIT) (pp. 1‑4). IEEE.
Chowdhury, M.A.H., Mumenin, N., Taus, M. and Yousuf, M.A., 2021, January. Detection of Compatibility, Proximity and Expectancy of Bengali Sentences using Long Short Term Memory. In 2021 2nd International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST) (pp. 233‑237). IEEE.
Singha, A., Mumenin, N., Akhter, N.I., Moon, M., Hossain, S. and Ahmed, M.U., 2022. A Lightweight Cryptographic Scheme to Secure WSNs in Agriculture. In Proceedings of Trends in Electronics and Health Informatics (pp. 615‑624). Springer, Singapore.
Mumenin N., Rahman M.M., Rahman R., Yousuf M.A., Ahmed M.U., Uddin M.Z. (2024). MCCNet: Malware Category Classification Utilizing Uncertainty‑aware and Interpretable Ensemble Model. IEEE Access, IEEE. (Scopus Indexed, Q1) (1st Revision Completed - November 25, 2024 ‑ Submitted on September 24, 2024).
Mumenin N., Rahman M.M., Yousuf M.A., Uddin M.Z. (2024). Early Diagnosis of Autism Across Developmental Stages Through Scalable and Interpretable Ensemble Model. Frontiers in Artificial Intelligence. (Scopus Indexed, Q2) (1st Revision Completed ‑ Submitted on October 10, 2024).
Mumenin N., Yousuf M.A., Alasaffi M.0., Monowar M.M., Hamid M.A. (2024). DDNet: A Robust, and Reliable Hybrid Machine Learning Model for Effective Detection of Depression Among University Students. IEEE Access, IEEE. (Scopus Indexed, Q1) (Under Review ‑ Submitted on November 9, 2024).
Title: "A Transparent and Reliable Framework for Detection of Anxiety Among University Students of Bangladesh."
Short Description: Anxiety has recently been highly prevalent among university students. A current research of ours has shown that around 60% of the university students in Bangladesh are suffering from anxiety. We are working to develop a transparent and reliable framework for the detection of anxiety utilizing state-of-the-art Machine Learning techniques, Manifold Learning, Representation Learning, and Explainable AI.
Title: "An Attention-based Explainable Framework for Suicidal Thoughts Detection From Bilingual Social Media Posts."
Short Description: The rate and tendency of committing suicide has grabbed much attention in recent times. People tend to share their thoughts through social media, which can play a crucial role in identifying the state of the mind of that user. We intend to utilize this data for the early detection of suicidal thoughts among social media users. We are working to develop a reliable system for detecting suicidal thoughts utilizing state-of-the-art Machine Learning techniques, Manifold Learning, Representation Learning, and Explainable AI.
Title: "A Clinically Usable Framework for Binary and Multi-class Classification of Endometrial Cancer from Histopathology Images ."
Short Description: Coming Soon..