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Anam Iqbal

HDR Student
MPhil in Statistics, Allama Iqbal Open University, Pakistan, 2016 MSc in Statistics, University of Sargodha, Pakistan, 2010
UNSW Canberra
School of Science

Research areas

Statistical Machine learning, Applied Statistics, Statistical Process Control and Monitoring, Big data and Artificial Intelligence, High Dimensional Analysis, Data Mining, Generalized Linear Modelling, Data Analytics, Data Science
Email

anam.iqbal@unsw.edu.au

Location

Building 26

Iqbal, A., Wild, G., & Iqbal, K. (2026). AI-Based Flight State Identification for Aerospace Control Systems. In AIAA AVIATION 2026 Forum (p. 4755), https://doi.org/10.2514/6.2026-4755

Iqbal, A., & Mahmood, T. (2026). EWMA control charts to monitor energy output in combined cycle power plant: a new approach based on RBS profiling. Communications in Statistics-Simulation and Computation, 55(4), 13391357, https://doi.org/10.1080/03610918.2024.2439461

Wild, G., Nanyonga, A., Iqbal, A., Bano, S., Somerville, A., & Pollock, L. (2025). Lightweight and mobile artificial intelligence and immersive technologies in aviation. Visual Computing for Industry, Biomedicine, and Art, 8(1), 21, https://doi.org/10.1186/s42492-025-00203-z

Iqbal, A., & Mahmood, T. (2025). CUSUM charts utilizing reparametrized Birnbaum-saunders model for fault detection and process control. Measurement and Control, 58(9), 1183-1194, https://doi.org/10.1177/00202940241282533

Iqbal, A., Wild, G., & Iqbal, K. (2025, December). Explainable Flight State Recognition: Toward Intelligent Pilot Training Systems. In 2025 International Conference on Sustainable Technology and Engineering (i-COSTE) (pp. 1-6). IEEE, https://doi.org/10.1109/i-COSTE68047.2025.11467550

Iqbal, A., Wild, G., & Iqbal, K. (2025, November). Towards Trustworthy Flight State Identification Using Explainable Supervised Learning. In 2025 IEEE International Conference on Future Machine Learning and Data Science (FMLDS) (pp. 530-535). IEEE, https://doi.org/10.1109/FMLDS67896.2025.00091

Iqbal, A., & Wild, G. (2025, October). An Ensemble Clustering Approach to Recognize Flight State in Pilot Training. In TENCON 2025-2025 IEEE Region 10 Conference (TENCON) (pp. 1038-1042). IEEE, https://doi.org/10.1109/TENCON66050.2025.11374976

Iqbal, A., Somerville, A., & Wild, G. (2025). AI Algorithms for Dynamic Maneuver Clustering and Classification in Flight Training. In AIAA AVIATION FORUM AND ASCEND 2025 (p. 3325), https://doi.org/10.2514/6.2025-3325

Iqbal, A., Jansen, T., Somerville, A., & Wild, G. (2025). Use of artificial intelligence generated feedback in flight simulation training. In AIAA SciTech 2025 Forum (p. 2729), https://doi.org/10.2514/6.2025-2729

Iqbal, A., & Wild, G. (2024, December). Machine Learning for Phase of Flight Detection. In 2024 International Conference on Sustainable Technology and Engineering (i-COSTE) (pp. 1-6). IEEE, https://doi.org/10.1109/i-COSTE63786.2024.11024581

Awarded a Gold Medal-2016 for securing the first position in MPhil Statistics programme of the Department of Statistics in convocation 2024 of Allama Iqbal Open University.

Awarded a Bronze Medal-2010 for securing the third position in MSc Statistics programme of the Department of Statistics in convocation 2013 of University of Sargodha.

Mahmood T; Iqbal A; Kinat S, 2021, On the comparison of GLM-based charts for industrial processes presented in the 4th International Conference on Econometrics and Statistics (EcoStat 2021) held on 24-26 June 2021 virtually from the Hong Kong University of Science and Technology, Hong Kong. 

Iqbal A; Ahmad B, 2016, Goodness-of-fit statistics for generalized linear models presented in the 1st UMT International Conference on Pure and Applied Science in collaboration with Brock University, Canada, International Islamic University, Malaysia and Sharjah University, UAE held on 5-7 March 2016 in University of Management and Technology, Lahore, Pakistan