Department of Software Engineering
Dr. Mohammad Sultan Mahmud  Assistant Professor
Name :
Dr. Mohammad Sultan Mahmud
Designation
Assistant Professor  
Department
Department of Software Engineering
Faculty
Faculty of Science and Information Technology
Personal Webpage
https://faculty.daffodilvarsity.edu.bd/profile/swe/sultan-swe.html
E-mail
sultan.swe@diu.edu.bd
Phone
+8809617901233
Cell-Phone
+88 01977295641

Ph.D.  
Shenzhen University, China, 2023

M.Sc. in Information Technology 
King Mongkut’s University of Technology North Bangkok, Thailand, 2014

B.Sc. in CSE
BGC University Bangladesh, Bangladesh, 2009

  • Discrete Mathematics 

Journal articles (Selected)

[J14] M. Sadiq, Y. Zhang, Y. Zhou, M.S. Mahmud, M. Azhar, M. Durad, J. Liang(2026), “A context-aware dropout-based occlusion-adaptive network for robust facial landmark and emotion detection”,  Journal of King Saud University Computer and Information Sciences, 14,  53009-53018.  DOI:   10.1007/s44443-026-00705-7
[J13] M. Sadiq, J. Wu, Y. Geng, M.S. Mahmud, A Khelloufi, H Zheng, Y Zhang, ,  J. Liang (2026), “ADODN: Attentive dropout-based occlusion-aware deep network for facial landmark detection”, IEEE Access, 14,  53009-53018.  DOI:  10.1109/ACCESS.2026.3681267 
[J12] M.S. Mahmud, J.Z. Huang, S. García & G. Gonz´alez-Almagro (2025), “Determination of the number of clusters in high-dimensional data with subspace clusters”, IEEE Transaction on Big Data, 11(6), 3240-3254.  DOI: 10.1109/TBDATA.2025.3588027 (JCR Q1 Top, IF 5.7)
[J11] M.S. Mahmud, H. Zhang, D. Garcia-Gil, S. García & J.Z. Huang, (2025), “RSPCA: Random sample partition and clustering approximation for ensemble learning of big data”, Pattern Recognition, 161. DOI: 10.1016/j.patcog.2024.111321 (JCR Q1 Top, IF 7.5)
[J10] Y. Cai, M.S. Mahmud, J. Xu, X. Sun & J.Z. Huang (2024), “Spectral ensemble clustering with doubly stochastic co-association matrix”, Information Sciences, 686.                         DOI: 10.1016/j.ins.2024.121314 (JCR Q1, IF 6.1)
[J9] M.S. Mahmud, J.Z. Huang & S. García (2023), “Clustering approximation via a fusion of multiple random samples”, Information Fusion, 101. DOI: 10.1016/j.inffus.2023.101986 (JCR Q1 Top, IF 18.6)
[J8] M.S. Mahmud, J.Z. Huang, R. Ruby, A. Ngueilbaye & K. Wu (2023), “Approximate clustering ensemble method for big data”, IEEE Transaction on Big Data, 9(4), 1142-1155.                        DOI: 10.1109/TBDATA.2023.3255003 (JCR Q1, IF 7.2)
[J7] M.S. Mahmud, J.Z. Huang, R. Ruby & K. Wu (2023), “An ensemble method for estimating the number of clusters in a big data set using multiple random samples”, Journal of Big Data, 10(1), 1-33. DOI:10.1186/s40537-023-00709-4 (JCR Q1, IF 8.1) 
[J6] K. Sadatdiynov, L. Cui, L. Zhang, J.Z. Huang, S. Salloum & M.S. Mahmud (2022), “A review of optimization methods for computation offloading in edge computing networks”, Digital Communications and Networks, 9(2), 450-461. DOI: 10.1016/j.dcan.2022.03.003 (JCR Q1, IF 7.9)
[J5] M.S. Mahmud, J.Z. Huang, X. Fu, R. Ruby & K. Wu (2021), “An unsupervised adaptation for high-dimensional with limited-sample data classification using variational autoencoder”, Computing and Informatics, 4(1), 1-28. DOI: 10.31577/cai_2021_1_1  
[J4] M.S. Mahmud, J.Z. Huang, S. Salloum, T.Z. Emara & K. Sadatdiynov (2020), “A survey of data partitioning and sampling methods to support big data analysis”, Big Data Mining and Analytics, 3(2), 85-101. DOI: 10.26599/BDMA.2019.9020015 (JCR Q1, IF 13.6) [Excellent Paper Award]
[J3] M.S. Mahmud, J.Z. Huang & X. Fu (2020), “Variational autoencoder based dimensionality reduction for high-dimensional small-sample data classification”, International Journal of Computational Intelligence and Applications, 19(1), 1-19. DOI: 10.1142/S1469026820500029
[J2] M.S. Mahmud, M.S. Islam & M.A. Rahman (2017), “Smart fire detection system with automatic early notifications using machine learning”, International Journal of Computational Intelligence and Applications, 16(02). DOI: 10.1142/S1469026817500092
[J1] M.S. Mahmud & P. Meesad (2016), “An innovative recurrent error-based neuro-fuzzy system with momentum for stock price prediction”, Soft Computing, 20(10), 4173-4191.                     DOI: 10.1007/s00500-015-1752-z  (IF 3.1) 
[C4] M.S. Mahmud & X. Fu (2019), “Unsupervised classification of high-dimension and low-sample data with variational autoencoder based dimensionality reduction”. In 4th International Conference on Advanced Robotics and Mechatronics (ICARM2019), Osaka, Japan, 03-05 July 2019. DOI: 10.1109/ICARM.2019.8834333
[C3] M.S. Mahmud, X. Fu, J.Z. Huang & M.A. Masud (2018), “High-dimensional limited-sample biomedical data classification using variational autoencoder”. In 16th Australasian Conference on Data Mining (AusDM2018), NSW, Australia, 28-30 November 2018. (Acceptance rate 30/80 = 37.5%) DOI: 10.1007/978-981-13-6661-1_3
[C2] M.S. Mahmud, P. Meesad & S. Sodsee (2016), “An evaluation of computational intelligence in credit card fraud detection”. In 20th International Computer Science & Engineering Conference (ICSEC2016), Changmai, Thailand, 14-17 December 2016. (Acceptance rate 230/438 = 52.5%) DOI: 10.1109/ICSEC.2016.7859947
[C1] M.S. Mahmud & P. Meesad (2014), “Time series stock price prediction using recurrent error-based neuro-fuzzy system with momentum”, In International Electrical Engineering Congress (iEECON2014), Chonburi, Thailand, 19-21 March 2014. (Acceptance rate 21/163 = 13%) DOI: 10.1109/iEECON.2014.6925866   

 

Editorial Roles 

# Information Fusion, Associate Editor.
# Information Fusion, Guest Editor of Special Issue on Mixture of Experts (MoE) and Ensemble Learning for Big Data, 2025.

 

Talk at Conferences and Seminar 
2026 Distributed Clustering Ensemble for Big Data, Keynote Talk, In: 2024 International Conference on Foundations and Future of Artificial Intelligence, June 15, 2026,  Nukus, Karakalpakstan, Uzbeakistan
2024 Approximate Clustering Ensemble for Big Data, Keynote Talk, In: 2024 International Conference on Artificial Intelligence and Future Education, June 29-30, 2024, Hubei, China
2022 Approximate Computing for Big Data Analysis, Invited Speaker, at BGC Trust University Bangladesh, January 31, 2022, Chittagong, Bangladesh

 

Distributed clustering ensemble, big data intelligent computing technology, multi-sample statistical theory and methods, data mining and machine learning algorithms and applications 

2020 – 2023 National Natural Science Foundation of China (NSFC), Distributed approximate computing methods and algorithms based on random sample partition for big data processing and analysis, Grant no. 61972261. Co-Investigator (PI: Prof. Joshua Zhexue Huang)
2020, 2023202120202017 – 202320182017 – 20182012 – 2014 Guangdong Government Outstanding International Student Scholarship Excellent Paper Award 2021, Big Data Mining and Analytics Fan Qi Bao Scholarship Shenzhen University Doctoral Fellowship  Shenzhen Universiade International Scholarship   Outstanding PhD Student Award  Royal Thai Govt. IT-KMUTNB full-funded Master’s Scholarship 

 

  • IEEE Senior Member

Research Assistant Professor (January 2024 – December 2025), 
Big Data Institute, College of Computer Science and Software Engineering, Shenzhen University, China

Assistant Professor (February 2021 – December 2022), 
Department of Telecommunication Engineering, Nukus branch of Tashkent University of Information Technology, Uzbekistan

Lecturer (January 2015 – February 2017), 
Department of Computer Science and Engineering, World University of Bangladesh, Bangladesh