Rejwan Bin Sulaiman

Data Scientist

Personal Profile:

Rejwan Bin Sulaiman is a highly skilled researcher in the field of artificial intelligence and cybersecurity. Currently serving as a lecturer and module leader at Northumbria University London, Rejwan specializes in the areas of cybersecurity, machine learning, and artificial intelligence. He has actively contributed to the field through his research, attending conferences and seminars to present his work and staying up to date with the latest advancements in his domain.

In addition to his teaching responsibilities, Rejwan has extensive experience supervising both full-time and part-time students at the BSc and MSc levels. He has also been involved in various professional consultancy activities, further enriching his understanding of industry requirements and practices. Rejwan’s research interests are primarily focused on the cutting-edge fields of cybersecurity, artificial intelligence, and machine learning, particularly on topics such as cyber-security and privacy, federated learning, Image processing and computational intelligence. His innovative work has been recognized and published in reputable conferences and journals, showcasing his contributions to the scientific community.

As a lecturer at Northumbria University and a lead researcher at, Rejwan is dedicated to advancing knowledge and driving innovation in his field. He actively participates in scientific meetups, sharing his insights and learning from fellow professionals, to further expand his expertise. With his deep understanding of artificial intelligence and cybersecurity, combined with his passion for teaching and research, Rejwan is committed to significantly impacting the ever-evolving landscape of computer science.

Academic and Industry Experience:

Rejwan has accumulated extensive academic and industry experience over the course of several years, enabling him to develop expertise across multiple domains. During his term at NUL, he actively contributed to the design and development of modules centred around mobile and web security, as well as AI for IoT. Additionally, he played a pivotal role as a Data Scientist in a team that successfully completed a 200k-funded Innovative UK project.

Rejwan’s involvement extends beyond his academic role, as he co-founded the Cybersecurity Club@UoB, aiming to assist students in understanding ethical hacking techniques and countermeasures at university of Bedfordshire. Furthermore, he holds a leadership position as a lead researcher at, where he oversees and guides a team of approximately 12 students, focusing on various research topics in the fields of AI, machine learning and cyber security.

Additionally, Rejwan actively participates as a reviewer and serves as a member of the Technical Program Committee at different IEEE conferences. His professional affiliations with IEEE and BCS provide him with opportunities to engage with a wide range of seminars and research workshops, enabling him to stay up to date with the latest advancements in his field.

Qualifications and Professional Memberships:

Rejwan holds multiple academic qualifications and professional certifications that demonstrate his expertise in the field. Alongside his PhD (candidate), MSc and BSc degree , he is a certified ethical hacker and possesses professional certifications such as C|EH, CCNA, and AWS. Additionally, Rejwan is a member of the IEEE (Institute of Electrical and Electronics Engineers) and BCS (British Computer Society), enabling him to stay updated with the latest advancements and network with fellow professionals.

To know more about me Please visit

  • Islam, M., Shuvo, S.A., Nipun, M.S., Bin Sulaiman, R., Shaikh, M.M., Nayeem, J., Haque, Z., Sourav, M.S.U. and Kareem, A., 2023. Efficient Approach to Using CNN-Based Pre-trained Models in Bangla Handwritten Digit Recognition. In Computational Vision and Bio-Inspired Computing: Proceedings of ICCVBIC 2022 (pp. 697-716). Singapore: Springer Nature Singapore.
  • Nipun, M.S., Sulaiman, R.B. and Kareem, A., 2023. An Efficient Approach for Image Detection and Recognition Using Artificial Intelligence in Cyber-Physical Systems. In Computational Intelligence for Cybersecurity Management and Applications (pp. 101-119). CRC Press.
  • Kareem, A., Sulaiman, R.B., Akram, S.V., Maurya, M., Chakrapani, I.S. and Sasikala, P., 2023, May. Artificial Intelligence Based Early Diagnosis of Sepsis. In 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) (pp. 1557-1562). IEEE.
  • Nipun, M.S., Talukder, M.S.H., Butt, U.J. and Sulaiman, R.B., 2023. Influence of Artificial Intelligence in Higher Education; Impact, Risk and Counter Measure. In AI, Blockchain and Self-Sovereign Identity in Higher Education (pp. 143-166). Cham: Springer Nature Switzerland.
  • Talukder, M.S.H., Sulaiman, R.B., Chowdhury, M.R., Nipun, M.S. and Islam, T., 2023. PotatoPestNet: a CTInceptionV3-RS-based neural network for accurate identification of potato pests. Smart Agricultural Technology, 5, p.100297.
  • Talukder, M.S.H., Chowdhury, M.R., Sourav, M.S.U., Al Rakin, A., Shuvo, S.A., Sulaiman, R.B., Nipun, M.S., Islam, M., Islam, M.R., Islam, M.A. and Haque, Z., 2023. JutePestDetect: An intelligent approach for jute pest identification using fine-tuned transfer learning. Smart Agricultural Technology, 5, p.100279.
  • Sourav, M.S.U., Wang, H., Chowdhury, M.R. and Sulaiman, R.B., 2023. CNN (Convolution Neural Network) Based Intelligent Streetlight Management Using Smart CCTV Camera and Semantic Segmentation. In Technology and Talent Strategies for Sustainable Smart Cities (pp. 229-246). Emerald Publishing Limited.
  • Islam, S. A. Shuvo, M. S. Nipun, R. Bin Sulaiman, M. M. Shaikh, J. Nayeem, Z. Haque, M. S. Sourav, and A. Kareem, “Efficient approach to using CNN-based pre-trained models in Bangla handwritten digit recognition,” Computational Vision and Bio-Inspired Computing, pp. 697–716, 2023.
  • Bin Sulaiman, R., Schetinin, V. & Sant, P. Review of Machine Learning Approach on Credit Card Fraud Detection. Hum-Cent Intell Syst 2, 55–68 (2022).
  • Arora, B., Jadhav, P., Sulaiman, R.B., Kareem, A., Kunekar, P. and Pant, B., 2022, December. Integrating Artificial Intelligence and Deep Learning for Enhanced Medical Innovation. In 2022 5th International Conference on Contemporary Computing and Informatics (IC3I) (pp. 327-331). IEEE.
  • Kumar Tyagi, S. M. Beram, P. Tyagi, R. B. Sulaiman, B. Pant and P. Srivani, “Design & Implementation of Hotel Recommendation System with Intelligent Data Analytics Collaborative Filtering Based on Machine Learning,” 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 2022, pp. 350-355, doi: 10.1109/ICACITE53722.2022.9823745.
  • Sulaiman, R.B., Schetinin, V. (2022). Deep Neural-Network Prediction for Study of Informational Efficiency. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2021. Lecture Notes in Networks and Systems, vol 295. Springer, Cham.
  • Kareem and R. B. Sulaiman, “Applications of Blockchain Technology and Related Security Threats,” Security Engineering for Embedded and Cyber-Physical Systems, pp. 99–110, Jun. 2022, doi: 10.1201/9781003278207-7.
  • Bin Sulaiman, A. Kareem, and M. U. Farooq, “Algorithms and Security Concern in Blockchain Technology,” Security Engineering for Embedded and Cyber-Physical Systems, pp. 3–24, Jun. 2022, doi: 10.1201/9781003278207-2.
  • B. Sulaiman and R. L. Patel, “Statistical in-depth security analysis for vehicle to everything communication over 5G Network,” Vehicular Communications for Smart Cars, pp. 151–186, Dec. 2021, doi: 10.1201/9781315110905-7.
  • B. Sulaiman, “AI Based Chatbot: An Approach of Utilizing On Customer Service Assistance,” arXiv:2207.10573 [cs], Jun. 2022, Accessed: Sep. 18, 2022. [Online]. Available:
  • S. Nipun, R. B. Sulaiman, and A. Kareem, “Efficiency Comparison of AI classification algorithms for Image Detection and Recognition in Real-time,” arXiv:2206.05842 [cs], Jun. 2022, Accessed: Sep. 18, 2022. [Online]. Available:
  • Yousuf, R. B. Sulaiman, and M. S. Nipun, “A novel approach to increase scalability while training machine learning algorithms using Bfloat 16 in credit card fraud detection,” arXiv:2206.12415 [cs], Jun. 2022, Accessed: Sep. 18, 2022. [Online]. Available:
  • Kareem, Amer and Sulaiman, Rejwan Bin, Concepts, Technologies and Future Scope of 6G Cellular Network: A Review (November 8, 2020). The IUP Journal of Telecommunications, Vol. 13, No. 2, May 2021, pp. 7-18, Available at SSRN:
  • Bin Sulaiman, Rejwan and Masud Ahmed Rahi. “A Detailed Study on Web-Based-Honeypot To Propose Mitigation Framework in Web Application.” EngRN: Computer-Aided Engineering (Topic)(2019): n. pag.
  • Artificial Intelligence (AI)
  • Computer Vision (CV)
  • Machine Learning (ML)
  • Deep Learning (DL)
  • Medical Image Analysis
  • Ultrasound Image Analysis
  • Cancer Image Analysis
  • Health Informatics
  • Cyber Security
  • Information Security
  • Network Security
  • BlockChain


  • Research Lead at “”
  • Reviewer at International Conference on Trends and Innovations in Smart Technologies
  • Reviewer at The International Conference on Advances in Communication Technology and Computer Engineering.
  • Reviewer at The Twelfth International Conference on Information and Communication Systems.


Founder and Lead Researcher – STEMResearch.Ai                                                    June 2022 – Present

  • Mentoring a group of nine – ten dedicated, detailed, and competent research fellows, in Artificial intelligence (AI), Machine learning (ML), and Deep Learning (DL). Aiming to publish High impact research papers in IEEE Xplore, ACM publication, Springer and Taylor & Francis.


Data Scientist – InnovativeUK 200k funded SAM AI project                                          June 2021 – Feb 2022

  • Developing web-based Data Science proof of concept using streamlit.
  • Using SQL, Python, and tableau, exploring the impact/ trends of weather/temperature on sales and assisting in making decisions about what to advertise in which weather conditions.
  • Developing a predictive model of sales in comparison to the advertisement where I assisted in saving 20 advertising hours each week, resulting in an expected annual savings of £26,000.
  • Building Python Script that saves at least 4-5 working hours for data cleaning.
  • Present analytical results and data visualizations in a way that is meaningful for stakeholders and provides actionable insight. Design and prepare reports and presentations in support of the company’s strategic goals.
  • ETL of data ingestion from different pipelines through API and database.
  • Funded by Innovate UK Smart Grant 2020, this project is an in-store service that measures, monitors and captures data from multiple IoT sources and analyses the data to promote the product in and out of the store. The idea is to aggregate data from various sources such as Weather, Signage, Electronic Point of Sale (EPOS), Footfall, etc. and apply machine learning and statistical techniques on the captured data to discover the relationships between parameters to maximise revenue.

Lecturer – Northumbria University London                                                             September 2022 – Present

  • Teaching Computing Modules: Information Assurance and Risk Management, Information Governance & Cyber Security, Database and Analytics Principles and Leadership in the Digital Age, AI for IoT, Big Data, Mobile and web application security and Ethical Hacking.
  • Leading modules: Ai for IoT, Mobile and web application security, Information Assurance and Risk Management.
  • Assessing students’ assessments for multiple modules, coursework, assignments, examinations, and project work.
  • Improving and Developing modules: AI for IoT, Big Data, Mobile and web application security.
  • Nominee of Student Led Teaching Award 2023 – Northumbria University 


Lecturer – University of Wales Trinity Saint David                                                          June 2022 – May 2023

  • Teaching Computing Modules like Data Analytics, Digital Skills and Knowledge and Information Management
  • Assessing students’ assessments for multiple modules, coursework, assignments, examinations, and project work.
  • Supervising 20+ Masters level students and grading assignments.


Associate Lecturer – Arden University                                                                               May 2020 – Jan 2022

  • Teaching Computing Modules like Human-Computer Interaction, Data Analytics.
  • Assessing students’ assessments for multiple modules, coursework, assignments, examinations, and project work.
  • Supervising 10+ Masters level students and grade assignments.


Visiting Lecturer – University of Bedfordshire                                                                     Feb 2020 – Jan 2023

  • Teaching modules are Security Testing and Forensic Investigation, Ethical Hacking, Intelligent system and Data mining modules to undergraduate and MSc level students.
  • Teaching Artificial Intelligence, Advanced Big Data, Intelligent system, and Data mining modules to undergraduate and Msc level students.
  • Demonstrating Practical sessions and solving students’ programming queries.
  • Supervising 10+ Masters level students and grade assignments.