Journal Papers: 

1. Ahmed, I., Bukkapatnam, S. T., Botcha, B., & Ding, Y. (2024). Toward Futuristic Autonomous Experimentation—A Surprise-Reacting Sequential Experiment Policy. IEEE Transactions on Automation Science and Engineering.

2. Khosravi, H., Farhadpour, S., Grandhi, M., Raihan, A. S., Das, S., & Ahmed, I. (2024). Strategic data augmentation with CTGAN for smart manufacturing: Enhancing ML predictions of paper breaks in pulp-and-paper production. Manufacturing Letters, 41, 1312-1323.

3. Raihan, A. S., Khosravi, H., Das, S., & Ahmed, I. (2024). Accelerating material discovery with a threshold-driven hybrid acquisition policy-based Bayesian optimization. Manufacturing Letters, 41, 1300-1311.

4. Haque, T., Syed, M. A. B., Das, S., & Ahmed, I. (2024). Advancing Marine Surveillance: A Hybrid Approach of Physics-Infused Neural Network for Enhanced Vessel Tracking Using Automatic Identification System Data. Journal of Marine Science and Engineering, 12(11), 1913.

5. Raihan, A.S., Khosravi, H., Bhuiyan, T.H. and Ahmed, I., (2024). An augmented surprise-guided sequential learning framework for predicting the melt pool geometry. Journal of Manufacturing Systems, 75, pp.56-77.

6. Khosravi, H., Olajire, T., Raihan, A.S. and Ahmed, I., (2024). A data driven sequential learning framework to accelerate and optimize multi-objective manufacturing decisions. Journal of Intelligent Manufacturing, pp.1-26.

7. Shafie, M. R., Khosravi, H., Farhadpour, S., Das, S., & Ahmed, I. (2024). A cluster-based human resources analytics for predicting employee turnover using optimized Artificial Neural Networks and data augmentation. Decision Analytics Journal, 11, 100461.

8. Roy, S., Ahmed, I., Saldanha, J., Medini, K. and Wuest, T., (2024). Bottleneck Management through Strategic Sequencing in Smart Manufacturing Systems. Smart and Sustainable Manufacturing Systems, 8(1), pp.59-82.

9. Bhuiyan, T.H., Walker, V., Roni, M. and Ahmed, I., (2024). Aerial drone fleet deployment optimization with endogenous battery replacements for direct delivery of time-sensitive products. Expert Systems with Applications, 252, p.124172.

10. Rahman, A., Russell, M., Zheng, W., Eckrich, D., Ahmed, I. and N3C Consortium, (2024). SARS-CoV-2 infection is associated with an increase in new diagnoses of schizophrenia spectrum and psychotic disorder: A study using the US national COVID cohort collaborative (N3C). Plos one, 19(5), p.e0295891.

11. Khosravi, H., Ahmed, I. and Choudhury, A., (2024), January. Predicting Suicidal Ideation, Planning, and Attempts among the Adolescent Population of the United States. In Healthcare (Vol. 12, No. 13, p. 1262). Multidisciplinary Digital Publishing Institute.

12. Khosravi, H., Shafie, M.R., Hajiabadi, M., Raihan, A.S. and Ahmed, I., (2024). Chatbots and ChatGPT: A bibliometric analysis and systematic review of publications in Web of Science and Scopus databases. International Journal of Data Mining, Modelling and Management.

13. Syed, M. A. B., & Ahmed, I. (2023). "A CNN-LSTM Architecture for Marine Vessel Track Association Using Automatic Identification System (AIS) Data," Sensors, 23, 6400.

14. Ahmed I., Jun, M., and Ding, Y., (2022) “A Spatio-temporal Track Association Algorithm Based on Marine Vessel Automatic Identification System Data", IEEE Transactions on Intelligent Transportation Systems.  (Accepted, available online). 

15. Ahmed I., Galoppo, T., Hu, X. and Ding, Y., (2021) “Graph Regularized Autoencoder and its Application in Unsupervised Anomaly Detection ,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol: 44, No.8, pp. 4110 – 4124. 

16.  Ahmed I., Hu, X., Acharya, M., Ding, Y., (2021) “Neighborhood Structure Assisted Non-negative Matrix Factorization and its Application in Unsupervised Point Anomaly Detection,” Journal of Machine Learning Research, Vol: 22, No.34, pp. 1 – 32. 

17. Ahmed I., Dagnino, A., Ding, Y., (2019) “Unsupervised anomaly detection based on minimum spanning tree approximated distance measures and its application to hydropower turbines,” IEEE Transactions on Automation Science and Engineering, Vol: 16, No.2, pp. 654 – 667. 

18. Aziz, R.A., Paul, H.K., Karim, T.M., Ahmed I., Azeem, A., (2018) “Modeling and Optimization of Multilayer Aggregate Production Planning,” Journal of Operations and Supply Chain Management (JOSCM), Vol: 11, No.2, pp. 1 – 15.

19. Ahmed, I., Sultana, I., Azeem, A., (2017) “Development of an inventory model for two suppliers with random capacity considering supply disruption”, International Journal of Logistics and Systems Management (Inderscience), Vol: 26, No.1, pp. 57 – 84.

20. Sultana, I., Ahmed, I., Azeem, A., (2015) “An Integrated Approach for Multiple Criteria Supplier Selection combining Fuzzy Delphi, Fuzzy AHP and Fuzzy TOPSIS”, Journal of Intelligent and Fuzzy Systems (IOS Press) Vol 29, No. 4, PP. 1273-1287.

21. Sultana, I., Ahmed, I., Paul, S.K., Chowdhury, A.H., (2014) “Economic Design of X- bar control chart using Genetic Algorithm and Simulated Annealing Algorithm”, International Journal of Productivity and Quality Management (Inderscience) Vol. 14,No.3, pp:352-372.

22. Ahmed, I., Sultana, I., (2014) “A Literature review on Inventory modeling with reliability consideration”, International Journal of Industrial Engineering Computations (Growing Science), Vol: 5, No. 1, pp: 169-178.

23. Sultana, I., Ahmed, I., (2014) “A State of Art Review on Optimization Techniques in Just In Time”, Uncertain Supply Chain Management (Growing Science), Vol: 2, No. 1, pp: 15-26.

24. Ahmed, I., Sultana, I., Paul, S.K., Azeem, A., (2014) “Performance Evaluation of Control Chart for Multiple Assignable Causes Using Genetic Algorithm”, International Journal of Advanced Manufacturing Technology (Springer), Vol. 70, pp:1889–1902.

25. Ahmed, I., Sultana, I., Paul, S.K., Azeem, A., (2013) “Employee Performance Evaluation: A Fuzzy Approach”, International Journal of Productivity and Performance Management (Emerald), Vol: 62, No. 7, pp: 718-734.

26. Bhuiyan T., Ahmed, I., (2013) “Optimization of Cutting Parameters in Turning Process”, SAE International Journal of Materials and Manufacturing (SAE International), Vol: 7, No. 1, pp. 233-239.

27. Sultana, I., Ahmed, I., Azeem, A., Sarker, N.R., (2013) “Economic Design of Exponentially Weighted Moving Average (EWMA) Chart with Variable Sampling Interval at Fixed Times (VSIFT) Scheme incorporating Taguchi Loss Function”, International Journal of Industrial & Systems Engineering (Inderscience) , Vol: 29, No.4, pp. 428 – 452. 

Conference Papers: 

1. Raihan, A. S., & Ahmed, I. (2023, August). A Bi-LSTM Autoencoder Framework for Anomaly Detection-A Case Study of a Wind Power Dataset. In 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE) (pp. 1-6). IEEE.

2. Islam, F., Raihan, A., & Ahmed, I. (2023, June). Applications of Federated Learning in Manufacturing: Identifying the Challenges and Exploring the Future Directions with Industry 4.0 and 5.0 Visions. In 8th North America Conference on Industrial Engineering and Operations Management , https://doi.org/10.46254/NA8.20230219.

3. Syed, M. A. B., & Ahmed, I. (2023). Multi model LSTM architecture for Track Association based on Automatic Identification System Data. Proceedings of the IISE Annual Conference & Expo 2023.

4. Raihan, A. S., & Ahmed, I. (2023). Guiding the Sequential Experiments in Autonomous Experimentation Platforms through EI-based Bayesian Optimization and Bayesian Model Averaging. Proceedings of the IISE Annual Conference & Expo 2023.

5. Ahmed, I., Galoppo, T. and Ding, Y., "O-LoMST: An Online Anomaly Detection Approach And Its Application In A Hydropower Generation Plant," 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE), Vancouver, BC, Canada, 2019, pp. 762-767. 

6. Ahmed, I., Dagnino, A., Bongiovi, A. and Ding, Y., “Outlier detection for hydropower generation plant,” in Proceedings of the 14th IEEE International Conference on Automation Science and Engineering (CASE 2018), August 2018