Contact Dr Desmond Bisandu
- Email: Desmond.Bisandu@cranfield.ac.uk
- Twitter: @bisandud
- ORCID
- Google Scholar
- ResearchGate
Background
Dr Desmond Bisandu (he/him) is an Assistant Professor in Digital Technologies and Lead for the Digital Technologies and DTS Apprentices Open Cohorts. He holds a PhD in Artificial Intelligence (Data Science) from Cranfield University, as well as an MSc and BSc in Computer Science from the University of Jos and the American University of Nigeria, respectively.
Following the completion of his PhD, Dr Bisandu served as a Postdoctoral Research & Teaching Fellow in Artificial Intelligence (AI) and Scientific Computing at Cranfield University, where he combined research and teaching with applied work on advanced computational methods. His research has focused particularly on artificial intelligence, data science, machine learning, explainable AI, scientific computing, and data-driven modelling, with applications to complex challenges across aviation, aerospace and other data-intensive domains.
Dr Bisandu's academic work sits at the intersection of artificial intelligence, advanced computational methods, digital transformation and real-world application. His research seeks to translate emerging computational and digital technologies into practical solutions for complex socio-economic and industry-driven challenges. He has contributed to research involving AI-enabled modelling, prediction, optimisation and decision-support, with an emphasis on developing robust, intelligent and explainable approaches to real-world problems.
In his current academic role as an Assistant Professor & Lead, Open Cohort Apprenticeship in Digital Technology; he contributes to teaching, curriculum development, apprenticeship education, research supervision and academic leadership. His approach to education emphasises the integration of theoretical foundations with practical, industry-relevant skills, preparing learners to apply computational and digital technologies effectively in professional environments.
Through his combined experience in research, higher education and applied digital technologies, Dr Bisandu is committed to advancing the responsible and impactful application of AI and data-driven technologies while supporting the development of the next generation of digital technology professionals and researchers.
Research opportunities
Computer Science
Deep Learning
Machine Learning
Design and Analysis of Novel Algorithms
Data Science
Digital Technologies
Current activities
Computer Science, Machine Learning, Deep Learning, Artificial Intelligence, Data Science, Computational Science and Engineering, Novel algorithms development for solving real-world problems.
Clients
- UK Research and Innovation
- Petroleum Trust Development Fund
- Thales SA
- Airbus SE
- BAE Systems PLC
Publications
Articles In Journals
- Bisandu DB, Chandrakumar M & Moulitsas I. (2026). Deep liquid neural network for prediction of weather-impacted flight delay. Intelligent Systems with Applications, 30
- Chai DM, Moulitsas I & Bisandu DB. (2026). DAFN: A Dual Attention Fusion Network for Textual Data Classification. Knowledge-Based Systems
- Umar GN & Bisandu DB. (2025). Body Forces and Fluid Stability: A Theoretical Framework for Energy Transformation and Stratified Atmospheres. Science World Journal, 20(4)
- Umar GN & Bisandu DB. (2025). Body forces and fluid stability: a theoretical framework for energy transformation and stratified atmospheres. Science World Journal, 20(4)
- Bisandu DB & Moulitsas I. (2024). Prediction of flight delay using deep operator network with gradient-mayfly optimisation algorithm. Expert Systems with Applications, 247
- Bisandu DB, Soviani-Sitoiu DA & Moulitsas I. (2024). An enhanced deep autoencoder for flight delay prediction. Journal of Aviation/Aerospace Education and Research, 33(4)
- Bisandu DB & Moulitsas I. (2023). A deep BiLSTM machine learning method for flight delay prediction classification. Journal of Aviation/Aerospace Education & Research, 32(2)
- Alreshidi I, Bisandu DB & Moulitsas I. (2023). Illuminating the neural landscape of pilot mental states: a convolutional neural network approach with Shapley Additive explanations interpretability. Sensors, 23(22)
- Bisandu DB, Moulitsas I & Filippone S. (2022). Social ski driver conditional autoregressive-based deep learning classifier for flight delay prediction. Neural Computing and Applications, 34(11)
- Homaid MS, Bisandu DB, Moulitsas I & Jenkins KW. (2022). Analysing the sentiment of air-traveller: a comparative analysis. International Journal of Computer Theory and Engineering, 14(2)
- Gambo FL, Wajiga GM, Shuib L, Garba EJ, Abdullahi AA, .... (2022). Performance Comparison of Convolutional and Multiclass Neural Network for Learning Style Detection from Facial Images. ICST Transactions on Scalable Information Systems, 9(35)
- Bisandu DB, Prasad R & Liman MM. (2019). Data clustering using efficient similarity measures. Journal of Statistics and Management Systems, 22(5)
- Prasad R, Bisandu D & Liman M. (2018). Clustering News Articles using Efficient Similarity Measure and N-grams. International Journal of Knowledge Engineering and Data Mining, 5(1)
- Bisandu DB, Prasad R & Liman MM. (2018). Clustering news articles using efficient similarity measure and N-grams. International Journal of Knowledge Engineering and Data Mining, 5(4)
- Gurumdimma NY, Bisandu DB & Ojedayo E. Event extraction from textual data. Journal of Computer Science and Its Application, 26(1)
- Bisandu DB, Shalom A & LawanGambo F. MULTIMODAL BIOMETRIC AUTHENTICATION FOR A COMPUTER-BASED TEST (CBT) APPLICATION. International Research Journal of Computer Science, 7(7)
- Bisandu DB, Adedotun OJ & Gambo FL. A Reliable Mobile Application Package Picker and Delivery System. International Journal of Computer Science and Mobile Applications, 10(2)
- Eva O, Desmond B & Simon I. Sudoku Solving Ability and Intelligence. International Journal of Computer Applications, 178(43)
- Eva O, Desmond B & Dunka B. A Hybrid Backtracking and Pencil and Paper Sudoku Solver. International Journal of Computer Applications, 181(47)
- Bisandu DB, Datiri DD, Onokpasa E, Alams MT, Thomas GA, .... An Enhanced Text Mining Approach using Dynamic Programming. International Journal of Information Systems and Computer Sciences, 7(5)
- Umar GN & Bisandu DB. Existence and smoothness of Navier–Stokes solutions: A complete mathematical proof. Science World Journal, 20(4)
Conference Papers
- Chai DM, Moulitsas I & Bisandu DB. (2024). Understanding the relevance of parallelising machine learning algorithms using CUDA for sentiment analysis
- Bisandu DB & Moulitsas I. (2023). A hybrid ensemble machine learning approach for arrival flight delay classification prediction using voting aggregation technique
- Bisandu DB & Moulitsas I. (2022). A bidirectional deep LSTM machine learning method for flight delay modelling and analysis
- Bisandu DB, Homaid M, Moulitsas I & Filippone S. (2021). A Deep Feedforward Neural Network and Shallow Architectures Effectiveness Comparison: Flight Delays Classification Perspective
Books
- Gambo FL, Wajiga GM, Garba EJ, Abdullahi AA & Bisandu DB. Ouaissa M, Ouaissa M, Himer SE & Boulouard Z (eds). (2021). A Deep Learning Solution for Learning Style Detection using Cognitive - Affective Features
- Gambo FL, Wajiga GM, Etemi Joshua G, Abdullahi AA & Bisandu DB. (2021). A deep learning solution for learning style detection using cognitive-affective features
