• J. Wan, M. Xia, and A. Kusiak, Special Section on Internet of Things and Artificial Intelligence for Product Life-cycle Management of Complex Equipment, IEEE Transactions on Industrial Electronics, Vol. 18, No. 11, 2022, pp. 8074-8076 [Manufacturing].
• P. Li, A. Kusiak, L. Gao, and W. Shen, Editorial for the Special Issue on Intelligent Manufacturing, Engineering, Vol. 7, No. 6, 2021, pp. 704-705 [Manufacturing].
• A. Kusiak, Universal manufacturing: data, resiliency, and sustainability linkages, Journal of Intelligent Manufacturing, Vol. 33, No. 3, 2022, pp. 637-638 [Manufacturing].
• G. Liu, L. Gao, W. Shen, and A. Kusiak, A broad transfer learning algorithm for classification of bearing faults, Proceedings of the ASME 2020 15^th International Manufacturing Science and Engineering Conference, MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, September 2020, pp. V002T07A028-1 - V002T07A028-6, https://doi.org/10.1115/MSEC2020-8312 [Data science].
• A. Kusiak, Resilient Manufacturing, Journal of Intelligent Manufacturing, Vol. 31, No. 2, 2020, p. 269 [Manufacturing].
• A. Kusiak, Service manufacturing = Process-as-a-Service + Manufacturing Operations-as-a-Service, Journal of Intelligent Manufacturing, Vol. 31, No. 1, 2020, pp. 1-2  [Manufacturing].
• A. Kusiak, Intelligent Manufacturing: Bridging Two Centuries, Journal of Intelligent Manufacturing, Vol. 30, No. 1, 2019, pp. 1-2 [Manufacturing].
• A. Kusiak, A Four-part Plan for Smart Manufacturing, ISE Magazine, Vol. 49, No.7, July 2017, pp. 43-47 [Manufacturing].
• H. Francis and A. Kusiak, Prediction of Engine Demand with a Data-driven Approach, in A. Diveev, I. Zelinka, A. Kusiak, and E. Nikulchev (Eds), Procedia Computer Science, XII International Symposium Intelligent Systems 2016, INTELS 2016, Vol. 103, 2017, pp. 28-35 [Big data].
• J. Engler and A. Kusiak, Agent-Based Control of Thermostatic Appliances, Proceedings of the IEEE Green Technologies Conference, April 15-16, 2010, Grapevine, Texas, pp. 1-5 [HVAC energy].
• A. Kusiak, Innovation Science, The University of Hong Kong, Hong Kong, October 2015 [Innovation].
• A. Kusiak, Big Data in Mechanical Engineering, ME Today, March 2015 [Big data].
• A. Kusiak, Break Through with Big Data, Industrial Engineer, Vol. 47, No. 3, 2015, pp. 38-42 [Big data].
• X. Wei, X. He, A. Kusiak, Optimization of Wastewater Pumping Process with a Data-driven Approach, Proceedings of the 2013 Industrial and Systems Engineering Research Conference, San Juan, PR, May 2013, pp. 1-8  [Wastewater process energy].
• A. Kusiak, A. Verma, and X. Wei, Wind Turbine Frontier from SCADA, Wind Systems Magazine, Vol. 3, No. 9, September 2012, pp. 36-39 [Wind energy].
• X. Wei and A. Kusiak, Optimization of Biogas Production Process in a Wastewater Treatment Plant, Proceedings of the 2012 Industrial and Systems Engineering Research Conference, Orlando, FL, May 2012, pp. 1-9 [Wastewater process energy].
• A. Kusiakiak and Z. Zhang, Gearbox Fault Detection, Wind Systems Magazine, Vol. 3, No. 33, May 2012, pp. 54-59  [Wind energy].
• A. Kusiak and A. Verma, Enhanced Turbine Performance Monitoring, Wind Systems Magazine, Vol. 3, No. 24, August 2011, pp. 36-41  [Wind energy].
• A. Verma, and A. Kusiak, Predictive Analysis of Wind Turbine Faults: A Data Mining Approach, Proceedings of the 2011 Industrial Engineering Research Conference, Reno, Nevada, May 19-23, 2011, pp. 1-9 [Wind energy].
• A. Kusiak and Z. Zhang, Optimization of Power and its Variability with an Artificial Immune Network Algorithm, Power Systems Conference and Exposition (PSCE), 2011 IEEE/PES, March 2011, pp.1-8  [Wind energy].
• A. Kusiak and W. Li, Short-term Prediction of Wind Farm Power – A Data-driven Approach, Modern Energy Review, Vol. 2, No. 1, 2010, pp. 65-70  [Wind energy].
• A. Kusiak and Z. Zhang, Near Term Power Prediction, Wind Systems Magazine, Vol. 2, No. 14, October 2010, pp. 48-53 [Wind energy].
• A. Kusiak and A. Verma, The Future of Wind Turbine Diagnostics, Wind Systems Magazine, Vol. 2, No. 8, April 2010, pp. 66-71 [Wind energy].
• J. Engler and A. Kusiak, Web Mining for Innovation, ASME Mechanical Engineering,  Vol. 130, No. 11, November 2008, pp. 38-40 [Innovation]. 
• A. Kusiak, Interface Structure Matrix for Analysis of Products and Processes, Proceedings of the 15th CIRP International Conference on Life Cycle Engineering, LCE 2008, The University of New South Wales, Sydney, Australia, March 2008, pp. 444-448.
• A. Kusiak, Data Mining in Industrial Applications and Innovation, ICS News, INFORMS Computing Society, November 2007, pp. 17-21.
• A. Kusiak, Innovation of Products and Services: Bridging World's Economies, 19^th International Conference on Production Research, ICPR 19, Valparaiso, Chile, August 2007, pp. 1-6 (Plenary paper) [Innovation]. 
• A. Kusiak, Innovation: From Data to Knowledge, BONEZone, Vol. 6, No. 1, 2007, pp. 24-26 [Innovation].
• A. Kusiak, Innovation: A Data-driven Perspective, Drug Development 2007, Touch Briefings, London, UK, July 2007, pp. 55-58 [Innovation].
• A. Kusiak, Innovation Science, Proceedings of the 11th IEEE Conference on Emerging Technologies and the Factories of the Future, ETFA 2006, Prague, Czech Republic, September 2006, pp. 507-514 [Innovation]. 
• A. Kusiak, Data Mining in Design of Products and Production Systems, Proceedings of INCOM 12th IFAC/IFIP/IFORS/IEEE Symposium on Control Problems in Manufacturing,  Saint-Etienne, France, 2006, Vol. 1, pp. 49-53. 
• A. Kusiak and S. Shah, Data Mining and Warehousing in Pharma Industry, in J. Wang (Ed.), Encyclopedia of Data Warehousing and Mining, Idea Group, Inc., Hershey, PA, 2006, pp. 239-244 [Pharma]. 
• A. Kusiak and A. Burns, Mining Temporal Data: A Coal-Fired Boiler Case Study, in R. Khosla, R.J. Howlett, L.C. Jain (Eds), Knowledge-Based Intelligent Information and Engineering Systems: Vol. III, LNAI 3683, Springer, Heidelberg, Germany, 2005, pp. 953-958 [Energy]. 
• C. da Cunha, B. Agard, A. Kusiak, Improving Manufacturing Quality by Re-Sequencing Assembly Operations: A Data-Mining Approach, Proceedings of the 18th International Conference on Production Research - ICPR 18, University of Salerno, Fisciamo,  August, 2005, pp. 1-6. 
• A. Kusiak and F. Qin, Requirements Allocation, Chapter 69, in P.H. Sydenham and R. Thorn (Eds), Handbook of Measuring System Design, Wiley, New York, 2005, pp. 430-436. 
• B. Agard and A. Kusiak, Standardization of Components, Products, and Processes with Data Mining, Proceedings of the International Conference on Production Research, Americas 2004, Santiago, Chile, August  2004, pp. 1-9. 
• A. Burns, A. Kusiak, and T. Letsche, Mining Transformed Data Sets,  in M. Gh. Negoita, R.J. Howlett, and L.C. Jain (Eds), Knowledge-Based Intelligent Information and Engineering Systems, LNAI 3213, Vol. I, Springer, Heidelberg, Germany, 2004, pp. 148-154 [Energy]. 
• A. Kusiak, S. Shah, and B. Dixon, Data Mining Based Decision-Making Approach for Predicting Survival Kidney Dialysis Patients, in D.D. Feng and E.R. Carson (Eds), Modeling and Control on Biomedical Systems 2003, Proceedings of the IFAC 2003 Symposium on Modeling and Control of Biomedical Systems, Melbourne, Australia, published by Elsevier, Amsterdam, The Netherlands, August 2003, pp. 35-39 [Medical paper]. 
• A. Kusiak, C.A. Caldarone, M.D. Kelleher, F.S. Lamb, T. Persoon, Y. Gan, and A. Burns, Mining Temporal Data Sets: Hypoplastic Left Heart Syndrome Case Study, in B.V. Dasarathy (Ed.), Proceedings of the SPIE Conference on Data Mining and Knowledge Discovery: Theory, Tools, and Technology V, Vol. 5098, SPIE, Belingham, WA, April 2003, pp. 93-101 [Medical topic]. 
• S. Shah, A. Kusiak, and B. Dixon, Data Mining in Predicting Survival of Kidney Dialysis Patients, in Proceedings of Photonics West - Bios 2003, L.S. Bass  et al. (Eds),  Lasers in Surgery: Advanced Characterization, Therapeutics, and Systems XIII, Vol. 4949, SPIE, Belingham, WA, January 2003, pp.1-8 [Medical topic].   
• A. Kusiak, Data Mining and Decision Making, in B.V. Dasarathy (Ed.), Proceedings of the SPIE Conference on Data Mining and Knowledge Discovery: Theory, Tools, and Technology IV, Vol. 4730, SPIE, Orlando, FL, April 2002, pp. 155-165 . 
• A. Kusiak, Non-Traditional Applications of Data Mining, in D. Braha (Ed.), Data Mining for Design and Manufacturing, Kluwer, Boston, MA, 2001, pp. 401-416. 
• A. Kusiak, Decomposition in Data Mining: A Medical Case Study, in B.V. Dasarathy (Ed.), Proceedings of the SPIE Conference on Data Mining and Knowledge Discovery: Theory, Tools, and Technology III, Vol. 4384, SPIE, Orlando, FL, April 2001, pp. 267-277 [Medical topic]. 
• A. Kusiak, Evolutionary Computation and Data Mining, Proceedings of the SPIE Conference on Intelligent Systems and Advanced Manufacturing, B. Gopalakrishnan and A. Gunasekaran (Eds), SPIE, Vol. 4192, Boston, MA, November 2000, pp. 1-10. 
• A. Kusiak, Data Analysis: Models and Algorithms, Proceedings of the SPIE Conference on Intelligent Systems and Advanced Manufacturing, P.E. Orban and G.K. Knopf (Eds), SPIE, Vol. 4191, Boston, MA, November 2000, pp. 1-9. 
• A. Kusiak, Evolutionary Computation and Data Mining in Design of Process Models, Proceedings of the Second MIT Design Structure Matrix International Workshop, MIT, Cambridge, Mass (Power Point presentation), September 2000. 
• A. Kusiak, C.A. Caldarone, and N. Rossi, Data Mining and Computational Intelligence in Medical Decision Making, Proceedings of the Workshop on Creating a Knowledge Pool, Drug Information Association, Baltimore, MD, October 2000 (Power Point presentation) [Medical topic]. 
• A.topic Kusiak and A. Zakarian, Evolutionary Computation and Data Mining in Process Modeling, Proceedings of the Quality Engineering Conference, San Jose, Costa Rica, August 2000, pp. 49-59. 
• A. Kusiak, Integrated Product and Process Design: A Modularity Perspective, Engineering Design Conference 2000, S. Sivalogathan and P.T.J. Andrews (Eds), Professional Engineering Publishing, London, UK, pp. 73-82. 
• A. Kusiak, K.H. Kernstine, J.A. Kern, K.A. McLaughlin, and T.L. Tseng, Data Mining: Medical and Engineering Case Studies, Proceedings of the IIE Research 2000 Conference, Cleveland, OH, May 2000, pp. 1-7 [Medical topic]. 
• A. Kusiak and T.L. Tseng, Data Mining in Engineering Design: A Case Study, Proceedings of the IEEE Conference on Robotics and Automation, San Francisco, CA, April, 2000, pp. 206-211.
• A. Kusiak, Autonomous Diagnostics: A Data Mining Approach, Proceedings of the XIth Workshop on Supervising and Diagnostics of Machining Systems, Karpacz, Poland, March 2000, pp. 100-108.
• A. Kusiak, Decision Making: A Data Mining Perspective, Proceedings of the 26th International Conference on Computers and Industrial Engineering, Melbourne, Australia, Vol. 2, December 1999, pp. 145-151.
• A. Kusiak and T.L. Tseng, Data Mining: An Optimization Perspective, Proceedings of the International Conference on Industrial Engineering and Production Management, Glasgow, Scotland, Vol. 1, July 1999, pp. 1-14 [Medical topic].

• A. Diveev, I. Zelinka, A. Kusiak, and E. Nikulchev (Eds), Procedia Computer Science, XII International Symposium Intelligent Systems 2016, INTELS 2016,  Vol. 103, 2017, 636 pages.
• L.-F. Wang, C. Singh, and A. Kusiak (Eds), Wind Power Systems: Applications of Computational Intelligence, Springer, Berlin, Germany, 2010, 437 pages.
• J. Wang and A. Kusiak (Eds), Computational Intelligence in Manufacturing Handbook, CRC Press, Boca Raton, FL, 2001, 512 pages.
• A. Kusiak, Computational Intelligence in Design and Manufacturing, John Wiley, New York, 2000, 535 pages.
• A. Kusiak, Engineering Design: Products, Processes, and Systems, Academic Press, San Diego, CA, 1999, 427 pages (Check Sciforma Corporation website for the for proces modeling software).
• A. Molina, J.M. Sanchez, and A. Kusiak, Handbook of Life Cycle Engineering, Kluwer, Boston, Mass., 1998, 618, pages.
• A. Kusiak and M. Bielli (Eds), Designing Innovations in Industrial Logistics Modeling, CRC Press, New York, N.Y., 1997, 268 pages.
• R. C. Dorf and A. Kusiak (Eds), Handbook of Design, Manufacturing and Automation, John Wiley, New York, N.Y., 1994, 1042 pages.
• C. Dagli and A. Kusiak, (Eds), Intelligent Systems in Design and Manufacturing, ASME Press, New York, N.Y., 1994, 487 pages.
• P. Gu and A. Kusiak, (Eds), Concurrent Engineering: Methodology and Applications, Elsevier, New York, N.Y., 1993, 330 pages.
• A. Kusiak, (Ed.), Concurrentnt Engineering: Automation, Tools, and Techniques, John Wiley, New York, N.Y., 1993, 589 pages.
• A. Kusiak, (Ed.), Intelligent Design and Manufacturing, John Wiley, New York, N.Y., 1992, 753 pages.
• A. Kusiak, Intelligent Manufacturing Systems, Prentice Hall, Englewood Cliffs, N.J., 1990, 443 pages (Published also in Chinese by Tsinghua University Publishing House, P.R. of China, 1993).

The papers that are not labeled are predominantly in manufacturing and industrial automation domain.

• A. Kusiak, Generative artificial intelligence in smart manufacturing, Journal of Intelligent Manufacturing, Vol. 36, No. 1, 2025, https://doi.org/10.1007/s10845-024-02480-6 [Editorial].
• Pennathur, P.R., V. Boksa, A. Pennathur, A. Kusiak, B. Livingston (2024), The Future of Office and Administrative Support Occupations in the Era of Artificial Intelligence: A State-of-the-Art Review and Future Research Directions, International Journal of Industrial Ergonomics_, Vol. 104, November 2024, pp. 1-13, 103665, https://doi.org/10.1016/j.ergon.2024.103665.  
• Pothini, T., C. D. Wilmot, J. K. Waters, M. A. Wait, S. I. Reznik, K. G. Jordan, J. T. Caire, J. M. Ashworth, L. C. Cady, J. R. Lysikowski, C. F. Yen, R. C. Weinschenk, R. Samade, M. E. Jessen, A. Kusiak, and K.H. Kernstine, Clinical and Radiological Septic Joint Analysis of Spontaneous Sternoclavicular Joint Infections: Achieving the Best Outcomes- A Systems Engineering Approach, Thoracic non-oncologic, European Journal of Cardio-Thoracic Surgery, Vol. 65, No. 4, 2024, ezae128.
• A. Kusiak, Federated Explainable Artificial Intelligence (fXAI): A Digital Manufacturing Perspective, International Journal of Production Research, Vol. 62, No. 1-2, 2024, pp. 171-182 [Data science].
• A. Kusiak, Hyper-automation in Manufacturing, Journal of Intelligent Manufacturing, Vol. 35, No. 1, 2024, pp. 1-2 [Data science].
• A. Kusiak, Predictive Models in Digital Manufacturing: Research, Applications, and Future Outlook, International Journal of Production Research, Vo. 61, No. 17, pp. 6052-6062, 2023 [Data science]. 
• A. Kusiak, Manufacturing Metaverse, Journal of Intelligent Manufacturing, Vol. 34, No. 6, 2023, pp. 2511-2512.
• G. Liu, W. Shen, L. Gao, and A. Kusiak, Active Federated Transfer Algorithm Based on Broad Learning for Fault Diagnosis, Measurement, Vol. 208, February 2023, pp. 1-10, 112452 [Data science].
• G. Liu, W. Shen, L. Gao, and A. Kusiak, Automated Broad Transfer Learning for Cross-domain Fault Diagnosis, SME Journal of Manufacturing Systems, Vol. 66, February 2023, pp. 27-41 [Data science].
• Y. Shen, Z. Song, A. Kusiak, and Z. Zhan, Prognosis of Rotor Parts Fly-off Based on Cascade Classification and Online Prediction Ability Index, Measurement Science and Technology, Vol. 34, No. 1, 2023, 12022 [Digital manufacturing].
• G. Liu, W. Shen, L. Gao, and A. Kusiak, Active Broad-Transfer Learning Algorithm for Class-imbalanced Fault Diagnosis, IEEE Transactions on Instrumentation & Measurement, Vol. 72, pp. 1-16, 2023, 3502216 [Data science]. 
• A. Sheth and A. Kusiak, Resiliency of Smart Manufacturing Enterprises via Information, Journal of Industrial Information Integration, Vol. 28, July 2022, 100370 [Smart manufacturing].
• A. Kusiak, From Digital to Universal Manufacturing, International Journal of Production Research, Vol. 60, No. 1, 2022, pp. 349-360 [Digital manufacturing]. 
• G. Liu, W. Shen, L. Gao, and A. Kusiak, An Active Label-denoising Algorithm Based on Broad Learning for Annotation of Machine Health Status, Science China: Technological Sciences, Vol. 65, No. 9, 2022, pp. 2089-2104 [Data science].
• G. Liu, W. Shen, L. Gao, and A. Kusiak, Knowledge Transfer in Fault Diagnosis of Rotary Machines, IET Collaborative Intelligent Manufacturing, Vol. 4, No. 1, 2022, pp. 17-34 [Data science].  
• A. Kusiak, Universal Manufacturing: Enablers, Properties, and Models, International Journal of Production Research, Vol. 60, No. 8, 2022, pp. 2497-2513 [Digital manufacturing]. 
• A. Dhini, I. Surjandari, B. Kusumoputro, A. Kusiak, Extreme Learning Machine–Radial Basis Function (ELM-RBF) Networks for Diagnosing Faults in a Steam Turbine, Journal of Industrial and Production Engineering, Vol. 39, No. 7, 2022, pp. 572-580 [Energy]. 
• S. Lu, Q. Xu, Y. Liu, C. Jiang, Y. Liu, and A. Kusiak, Probabilistic Load Forecasting with a Non-Crossing Sparse-Group Lasso-Quantile Regression Deep Neural Network, Energy, Vol. 242, March 1, 2022 [Energy].
• G. Liu, W. Shen, L. Gao, and A. Kusiak, Predictive Modeling with an Adaptive Unsupervised Broad Transfer Algorithm, IEEE Transactions on Instrumentation and Measurement, Vol. 70, pp. 1-12, 2021, 3520212 [Data science]. 
• T. Qin, R. Du, A. Kusiak, H. Tao, and Y. Zhong, Designing a Resilient Production System with Reconfigurable Machines and Movable Buffers, International Journal of Production Research,Vol. 60, No.17, 2022, pp. 5277-5292 [Manufacturing].  
• D. Wang, W. Tang, Y. Liu, X. Qu, Z. Ma, and A. Kusiak, An Opportunistic Maintenance Strategy for Wind Turbines, IET Renewable Power Generation, Vol. 15, No. 16, 2021, pp. 3793-3805 [Energy].
• J. Wan, X. Li, H.-N. Dai, A. Kusiak, M. Martinez-Garcia, and D. Li, Artificial Intelligence-Driven Customized Manufacturing Factory: Key Technologies, Applications, and Challenges, Proceedings of the IEEE, Vol. 109, No. 4, 2021, pp. 377-398 [Intelligent manufacturing].
• A. Kusiak, Extreme Engineering: Polarization in Product Development and Manufacturing, Engineering, Vol. 7, No. 3, 2021, pp. 282-284 [Engineering science].
• W. Chen, Y. Qiu, Y. Feng, Y. Li, and A. Kusiak, Diagnosis of Wind Turbine Faults with Transfer Learning Algorithms, Renewable Energy, Vol. 163, 2021, pp. 2053-2067 [Wind energy].  
• A. Kusiak, Extreme Science and Engineering, Journal of Intelligent Manufacturing, Vol. 31, No. 7, 2020, pp. 1607-1610 [Science].
• A. Kusiak, Open Manufacturing: A Design-for-Resilience Approach, International Journal of Production Research, Vol. 58, No. 15, 2020, pp. 4647-4658 [Manufacturing]. 
• T. Wuest, A. Kusiak, T. Dai, and S.R. Tayur, Impact of COVID-19 on Manufacturing and Supply Networks — The Case for AI-inspired Digital Transformation, ORMS Today, Vol. 47, No. 3, 2020, pp. 1-16 [Manufacturing].
• A. Kusiak, Convolutional and Generative Adversarial Neural Networks in Manufacturing, International Journal of Production Research, Vol. 58, No. 5, 2020, pp. 1594-1604 [Manufacturing].
• Z. Tang, Y. Li, and A. Kusiak, A Deep Learning Model for Measuring Oxygen Content of Boiler Flue Gas, IEEE Access, Vol. 8, No. 1, 2020, pp. 12268-12278 [Energy].
• A. Dhini, A. Faqih, B. Kusumoputro, I. Surjandari, and A. Kusiak, Data-driven Fault Diagnosis of Power Transformers using Dissolved Gas Analysis (DGA), International Journal of Technology, Vol. 11, No. 2, 2020, pp. 388-399 [Condition monitoring].
• A. Kusiak, Service Manufacturing: Basic Concepts and Technologies, SME Journal of Manufacturing Systems, Vol. 52, Part A, 2019, pp. 198-204 [Manufacturing]
• A. Kusiak, Fundamentals of Smart Manufacturing: A Multi-Tread Perspective, IFAC Annual Reviews in Control, Vol. 47, 2019, pp. 214-220 [Manufacturing].
• Y.H. Kuo and A. Kusiak, From Data to Big Data in Production Research: The Past and Future Trends, International Journal of Production Research, Vol. 57, Nos 15-16, 2019, pp. 4228-4853 [Manufacturing].
• J. Zhu, Y. Shen, Z. Song, D. Zhou, Z. Zhang, and A. Kusiak, Data-Driven Building Load Profiling and Energy Management, Sustainable Cities and Society, Vol. 49, 2019, pp. 1-15 [Sustainability].
• A. Kusiak, Create Jobs in Cleaning up the Environment, Nature, Vol. 558, No. 7708 (June 6), 2018, p. 30 [Sustainability].
• A. Kusiak, Smart Manufacturing, International Journal of Production Research, Vol. 56, Nos. 1–2, 2018, pp. 508-517 [Manufacturing].
• F. Tao, Q. Qi, A. Liu, and A. Kusiak, Data-Driven Smart Manufacturing, Journal of Manufacturing Systems, Vol. 48, Part C, 2018, pp. 157-169 [Manufacturing].
• Y. He and A. Kusiak, Performance Assessment of Wind Turbines: Data-Derived Quantitative Metrics, IEEE Transactions on Sustainable Energy, Vol. 9, No. 1, 2018, pp. 65-73 [Wind energy].
• A. Kusiak, Smart Manufacturing Must Embrace Big Data, Nature, Vol. 544, No. 7648 (April 6), 2017, pp. 23-25 [Manufacturing].
• H. Long, Z. Zhang, Z. Song, and A. Kusiak, Formulation and Analysis of Grid and Coordinate Models for Planning Wind Farm Layouts, IEEE Access, Vol. 5, No. 1, 2017, pp. 1810-1819 [Wind energy]. 
• T. Quyang, X.M. Zha, L. Quin, and A. Kusiak, Optimization of Time Window Size for Wind Power Ramps Prediction, IET Renewable Power Generation, Vol. 11, No. 8, 2017, pp. 1270-1277 [Wind energy].
• M.T. Sattari, A.R. Joudi, and A. Kusiak, Assessment of Different Methods for Estimation of Missing Data in Precipitation Studies, Hydrology Research,  Vol. 48, No. 4, 2017, pp. 1032-1044 [Environmental engineering].
• Y. He, A. Kusiak, T. Ouyang, and W. Teng, Data-driven Modeling of Truck Engine Exhaust Valve Failures: A Case Study, Journal of Mechanical Science and Technology, Vol. 31, No. 6, 2017, pp 2747-2757 [Condition monitoring].
• Z. Ma, W. Teng, Y. Liu, D. Wang, and A. Kusiak, Application of the Multi-Scale Enveloping Spectrogram to Detection of Weak Faults in a Wind Turbine Gearbox, IET Renewable Power Generation, Vol. 11, No. 5, 2017, pp. 578-584 [Condition monitoring].
• Z. Ma, Y. Liu, D. Wang, W. Teng, and A. Kusiak,  Cyclostationary Analysis of a Faulty Bearing in the Wind Turbine, ASME Transactions: Journal of Solar Energy Engineering, Vol. 139, No. 3,  2017, pp. 031006-1 - 031006-12 [Condition monitoring].
• W. Teng, X. Ding, Y. Zhang, Y. Liu, Z, Ma, and A. Kusiak, Application of Cyclic Coherence Function to Bearing Fault Detection in a Wind Turbine Generator under Electromagnetic Vibration, Mechanical Systems and Signal Processing, Vol. 87, Part A, March 2017, pp. 279-293 [Condition monitoring].
• T. Ouyang, A. Kusiak, and Y. He, Modeling Wind-Turbine Power Curve: A Data Partitioning and Mining Approach, Renewable Energy, Vol. 102 (Part A), 2017, pp. 1-8 [Wind energy].
• T. Ouyang, A. Kusiak, and Y. He, Predictive Model of Yaw Error in a Wind Turbine, Energy, Vol. 123, No. 1, 2017, pp. 119-130 [Wind energy].
• W. Teng, Y. Zhang, Y. Liu, A. Kusiak, and Z. Ma, Prognosis of the Remaining Useful Life of Bearings in a Wind Turbine Gearbox, Energies, Vol. 10, No. 1, 2017, pp.1-16 [Condition monitoring].
• S. Altunas, T. Dereli, and A. Kusiak, Assessment of Corporate Innovation Capability with a Data-mining Approach: Industrial Case Studies, Computers and Industrial Engineering, Vol 102, December 2016, pp. 58-68 [Innovation].
• Y. Zeng, Z. Zhang, A. Kusiak, F. Tang, and X. Wei, Optimizing Wastewater Pumping system with Data-Driven Models and a Greedy Electromagnetism-like Algorithm, Stochastic Environmental Research and Risk Assessment, Vol. 30, No. 4, 2016, pp. 1263-1275 [Wastewater process energy]. 
• M.T. Sattari, A.R. Joudi, and A. Kusiak, Estimation of Water Quality Parameters with Data-driven Models, Journal of American Water Works Association, Vol. 108, No. 4, 2016, pp. E232-E239 [Sustainability].
• A. Kusiak, Put Innovation Science at the Heart of Discovery, Nature, Vol. 530, No. 7590 (February 18), 2016, p. 255 [Innovation].
• A. Kusiak, Share Data on Wind Energy, Nature, Vol. 529, No. 7584 (January 7), 2016, pp. 19-21 [Wind energy].
• Z. Zhang, A. Kusiak, Y. Zeng, and X. Wei, Modeling and Optimization of a Wastewater Pumping System with Data-mining Methods, Applied Energy, Vol. 164, No. 2, 2016, 303-311 [Wastewater process energy]. 
• Y. Zeng, Z. Zhang, and A. Kusiak, Predictive Modeling and Optimization of a Multi-zone HVAC System with Data Mining and Firefly Algorithms, Energy, Vol. 86, No. 1, 2015, pp. 393-402 [HVAC energy].
• S. Altunas, T. Dereli, and A. Kusiak, Forecasting Technology Success Based on Patent Data, Technological Forecasting and Social Change, Vol. 96, No. 1, 2015, pp. 202-214 [Innovation].
• S. Altunas, T. Dereli, and A. Kusiak, Analysis of Patent Documents with Weighted Association Rules, Technological Forecasting and Social Change, Vol. 92, No. 1, 2015, pp. 249-262 [Innovation].
• X. Wei, A. Kusiak, M. Li, F. Tang, and Y. Zeng, Multi-objective Optimization of the HVAC (Heating, Ventilation, and Air Conditioning) System Performance, Energy, Vol. 83,  No. 1, 2015, pp. 294-306 [HVAC energy].
• Z. Zhang, X. Wei, and A. Kusiak, Data-driven Cost Minimization of Pump Operations and Maintenance, Engineering Applications of Artificial Intelligence, Vol. 40, No. 1, 2015, pp 37-46 [Wastewater process energy]. 
• X. Wei and A. Kusiak, Short-term Prediction of Influent Flow in Wastewater Treatment Plant, Stochastic Environmental Research and Risk Assessment, Vol. 29, No. 1, 2015, pp 241-249  [Wastewater process energy]. 
• X. Wei, G. Xu, A. Kusiak, Modeling and Optimization of a Chiller Plant, Energy, Vol. 73, No. 1, 2014, 898-907 [HVAC energy].
• F. Tang, A. Kusiak, X. Wei, Modeling and Short-term Prediction of HVAC System with a Clustering Algorithm, Energy and Buildings, Vol. 82, No. 1, 2014, pp. 310-321 [HVAC energy].
• A. Kusiak, G.L. Xu, and Z. Zhang, Minimization of Energy Consumption in HVAC Systems with Data-driven Models and an Interior-point Method, Energy Conversion and Management, Vol. 85, No. 1, 2014 pp. 146-153 [HVAC energy].  
• X. He, Z. Zhang, and A. Kusiak, Performance Optimization of HVAC Systems with Computational Intelligence Algorithms, Energy and Buildings, Vol. 81, No. 1, 2014, pp. 371-380 [HVAC energy].  
• A. Kusiak and X. Wei, Prediction of Methane Production in Wastewater Treatment Facility: A Data-Mining Approach, Annals of Operations Research, Vol. 216, No. 1, 2014, pp. 71-81 [Wastewater process energy]. 
• Z. Zhang, Q. Zhou, and A. Kusiak, Optimization of Wind Power and its Variability with a Computational Intelligence Approach, IEEE Transactions on Sustainable Energy, Vol. 5, No. 1, 2014, pp.  228-236  [Wind energy].
• A. Kusiak, Z. Zhang, and A. Verma, Prediction, Operations, and Condition Monitoring in Wind Energy, Energy, Vol. 60, No. 1, 2013, pp. 1-12 [Wind energy].
• A. Kusiak, Z. Zhang, and G. Xu, Minimization of Wind Farm Operational Cost Based on Data-driven  Models, IEEE Transactions on Sustainable Energy, Vol. 4, No. 3, 2013, pp. 756-764 [Wind energy].
• M.V. Muste, D.A. Bennett, S.Secchi, J.L. Schnoor, A. Kusiak, N.J. Arnold, S.K. Mishra, D. Ding, and U. Rapolu, End-to-End Cyberinfrastructure for Decision-Making Support in Watershed Management, ASCE Journal of Water Resources Planning and Management, Vol. 139, No. 5, 2013, pp. 565-573 [Water quality]. 
• A. Kusiak, Y. Zeng, Z. Zhang, Modeling and Analysis of Pumps in a Wastewater Treatment Plant: A Data-Mining Approach, Engineering Applications of Artificial Intelligence, Vol. 26, No. 7, 2013, pp. 1643-1651 [Wastewater process energy]. 
• A. Kusiak, X. Wei, A. Verma, and E. Roz, Modeling and Prediction of Rainfall Using Radar Reflectivity Data: A Data-Mining Approach, IEEE Transactions on Geoscience and Remote Sensing, Vol. 51, No. 4, 2013, pp. 2337-2342 [Water quality].
• A. Verma, Z. Zhang, and A. Kusiak, Modeling and Prediction of Gearbox Faults with Data-Mining Algorithms, ASME Transactions: Journal of Solar Energy Engineering, Vol. 135, No. 3,  2013, pp. 031007-1 - 031007-11 [Wind energy].
• A. Verma, X. Wei, and A. Kusiak, Predicting the Total Suspended Solids in Wastewater: A Data-Mining Approach, Engineering Applications of Artificial Intelligence, Vol. 26, No. 4, 2013, pp. 1366-1372 [Wastewater process energy]. 
• A. Kusiak and X. Wei, Optimization of the Activated Sludge Process, ASCE Journal of Energy Engineering, Vol. 139, No. 1, 2013, pp. 12-17 [Wastewater process energy]. 
• A. Kusiak, Y. Zeng, and G. Xu, Minimizing Energy Consumption of an Air Handling Unit with a Computational Intelligence Approach, Energy and Buildings, Vol. 60, No. 1, 2013, pp. 355-363 [HVAC energy].
• A. Kusiak and A. Verma, Monitoring Wind Farms with Performance Curves, IEEE Transactions on Energy Conversion, Vol. 4, No. 1, 2013, pp. 192-199 [Wind energy]. 
• A. Kusiak, A. Verma, and X. Wei, A Data-Mining Approach to Predict Influent Quality, Environmental Monitoring and Assessment, Vol. 185, No. 3, 2013, pp. 2197-2210 [Wastewater process energy].
• Y. Jiang, Z. Song, and A. Kusiak, Very Short-term Wind Speed Forecasting with Bayesian Structural Break Model, Renewable Energy, Vol. 50, 2013, pp. 637-647 [Wind energy].
•  Z. Zhang, A. Kusiak, and Z. Song, Scheduling Electric Power Production at a Wind Farm, European Journal of Operational Research, Vol. 224, No. 1, 2013, pp. 227-238 [Wind energy]. 
• Z. Zhang, Y. Zeng, and A. Kusiak, Minimizing Pump Energy in a Wastewater Processing Plant, Energy, Vol. 47,  No. 1, 2012, pp. 505-514 [Wastewater process energy].     
• A. Kusiak and A. Verma, Analyzing Bearing Faults in Wind Turbines: A Data-Mining Approach, Renewable Energy, Vol. 48, No. 1, 2012, pp.110-116 [Wind energy].
• Z. Zhang, and A. Kusiak, Monitoring Wind Turbine Vibration Based on SCADA Data, ASMETransactions: Journal of Solar Energy Engineering, Vol. 134, No. 2, 2012, pp. 021004-1-021004-12.
• Z. Zhang, A. Verma, and A. Kusiak, Fault Analysis of the Wind Turbine Gearbox, IEEE Transactions on Energy Conversion, Vol. 27, No. 2, 2012, pp. 526-535 [Wind energy]. 
• A. Kusiak and G.L. Xu, Modeling and Optimization of HVAC Systems Using a Dynamic Neural Network, Energy, Vol. 42, No. 1,  2012, pp. 241-250 [HVAC energy].
• A. Verma and A. Kusiak, Fault Monitoring Wind Turbine Generator Brushes: A Data Mining Approach, ASME Transactions: Journal of Solar Energy Engineering, Vol. 134, No. 2, 2012, pp. 021001-1-021001-9 [Wind energy]. 
• A. Kusiak and X. Wei, A Data-Driven Model for Maximization of Methane Production in a Wastewater Treatment Plant, Water Science and Technology, Vol. 65, No. 6, 2012, pp. 1116-1122 [Wastewater process energy].  
• A. Kusiak and Z. Zhang, Control of Wind Turbine Power and Vibration with a Data-Driven Approach, Renewable Energy, Vol. 43, Vol. 7, 2012, pp. 73-82 [Wind energy]. 
• A. Kusiak and A. Verma, A Data-Mining Approach to Monitoring Wind Turbines, IEEE Transactions on Sustainable Energy, Vol. 3, No.1, 2012, pp. 150-157 [Wind energy]. 
• Z. Zhang and A. Kusiak, Optimization of Energy Consumption of Pumps in a Wastewater Processing Plant, ASCE Journal of Energy Engineering, Vol. 137, No. 4, 2011, pp. 159-168 [Wastewater process energy].
• A. Kusiak, G.L. Xu, and F. Tang, Optimization of an HVAC System with a Strength Multi-objective Particle-Swarm Algorithm, Energy, Vol. 36, No. 10, 2011, pp. 5935-5943 [HVAC energy].
• A. Kusiak, H.Y. Zheng, and Z. Zhang, A Wind Speed Virtual Sensor for Wind Turbines, ASCE Journal of Energy Engineering, Vol. 137, No. 2, 2011, pp. 60-69 [Wind energy]. 
• J. Engler and A. Kusiak, Modeling an Innovation Ecosystem with Adaptive Agents, International Journal of Innovation Science, Vol. 3, No. 2, 2011, pp. 55-68 [Innovation science].
• A. Kusiak, F. Tang, and G.L. Xu, Multi-Objective Optimization of HVAC System with an Evolutionary Computation Algorithm, Energy, Vol. 36, No. 5, 2011, pp. 2440-2449 [HVAC energy].
• Z. Song, X. Geng, A. Kusiak, and C. Xu, Mining Markov Chain Transition Matrix from Wind Speed Time Series Data, Expert Systems with Applications, Vol. 38, No. 8, 2011, pp. 10229-10239 [Wind energy]. 
• A. Kusiak and A. Verma, Prediction of Status Patterns of Wind Turbines: A Data-Mining Approach, ASMETransactions: Journal of Solar Energy Engineering, Vol. 133, No. 1,  2011, pp. 011008-1 - 011008-10 [Wind energy]. 
• A. Kusiak and A. Verma, A Data-driven Approach for Monitoring Blade Pitch Faults in Wind Turbines, IEEE Transactions on Sustainable Energy, Vol. 2, No.1, 2011, pp. 87-96 [Wind energy].
• A. Kusiak and Z. Zhang, Adaptive Control of a Wind Turbine with Data Mining and Swarm Intelligence, IEEE Transactions on Sustainable Energy, Vol. 2, No. 1, 2011, pp. 28-36 [Wind energy].
•  A. Kusiak and W.Y. Li, The Prediction and Diagnosis of Wind Turbine Faults, Renewable Energy, Vol. 36, No. 1, 2011, pp. 16-23 [Wind energy].
•  A. Kusiak and Z. Zhang, Short-Horizon Prediction of Wind Power: A Data-Driven Approach, IEEE Transactions on Energy Conversion, Vol. 25, No. 4, 2010, pp. 1112-1122 [Wind energy].
• A. Kusiak, Z. Zhang, and M.Y. Li, Optimization of Wind Turbine Performance with Data-Driven Models, IEEE Transactions on Sustainable Energy, Vol. 1, No. 2, 2010, pp. 66-76 [Wind energy].
•  A. Kusiak, M.Y. Li, F. Tang, Modeling and Optimization of HVAC Energy Consumption, Applied Energy, Vol. 87, No. 10, 2010, pp. 3092-3102 [HVAC energy].
•  A. Kusiak and W.Y. Li, Estimation of Wind Speed with Wind Turbine Affinity: A Data-Driven Approach, Journal of Wind Engineering & Industrial Aerodynamics, Vol. 98, No. 10-11, 2010, pp. 559-567 [Wind energy].
• A. Kusiak and Z. Zhang, Analysis of Wind Turbine Vibrations Based on SCADA Data, ASME Transactions: Journal of Solar Energy Engineering, Vol. 132, No. 3, 2010, pp. 031008-1 - 031008-12 [Wind energy].
• A. Kusiak and W.Y. Li, Short-Term Prediction of Wind Power with a Clustering Approach, Renewable Energy, Vol. 30, No. 10, 2010, pp. 2362-2369 [Wind energy].
• A. Kusiak, M.Y. Li, and H.-Y. Zheng, Virtual Models of Indoor-Air-Quality Sensors, Applied Energy, Vol. 87, No. 6, 2010, pp. 2087-2094 [HVAC energy].
• A. Kusiak and M.Y. Li, Reheat Optimization of the Variable-Air-Volume Box, Energy, Vol. 35, No. 5, 2010, pp. 1997-2005 [HVAC energy].
• A. Kusiak and W. Li, Virtual Models for Prediction of Wind Turbine Parameters, IEEE Transactions on Energy Conversion, Vol. 25, No. 1, 2010, pp. 245-252 [Wind energy].
• A. Kusiak and H.-Y. Zheng, Optimization of Wind Turbine Energy and Power Factor with an Evolutionary Computation Algorithm, Energy, Vol. 35, No. 3, 2010, pp. 1324–1332 [Wind energy].
• Z. Song and A. Kusiak, Multi-Objective Optimization of Temporal Processes, IEEE Transactions on Systems, Man, and Cybernetics: Part B, Vol. 40, No. 3, 2010, pp. 845-856 [Wind energy].
• A. Kusiak, M.Y. Li, and Z. Zhang, A Data-driven Approach for Steam-Load Prediction in Buildings, Applied Energy, Vol. 87, No. 3, 2010, pp. 925-933 [HVAC energy].
• A. Kusiak, Z. Song, and H.-Y. Zheng, Power Optimization of Wind Turbines with Data Mining and Evolutionary Computation, Renewable Energy, Vol. 35, No. 3, 2010, pp. 695-702 [Wind energy].
•  A. Kusiak and M.Y. Li, Cooling Output Optimization of an Air Handling Unit, Applied Energy, Vol. 87, 2010, No. 3, pp. 901-909 [HVAC energy].
• A. Kusiak and Zeng. Song, Design of Wind Farm Layout for Maximum Wind Energy Capture, Renewable Energy, Vol. 35, No. 3, 2010, pp. 685-694 [Wind energy].
• J. Engler and A. Kusiak, Mining Authoritativeness of Collaborative Innovation Partners, International Journal of Computers, Communications & Control, Vol. 5, No. 1, 2010, pp. 45-54 [Innovation science].
• C. Da-Cunha, B. Agard, and A. Kusiak, Selection of Modules for Mass Customization, International Journal of Production Research, Vol. 48, No. 5, 2010, pp. 1439-1454 [Mass customization].
• S. Shah and A. Kusiak, Relabeling Algorithm for Retrieval of Noisy Instances and Improving Prediction Quality, Computers in Biology and  Medicine, Vol. 4, No. 3, 2010, pp. 288-299  [Medical topic].
• A. Kusiak and Z. Song, Sensor Fault Detection in Power Plants, ASCE Journal of Energy Engineering, Vol. 135, No. 4, 2009,  pp. 127-137 [Energy].
• A. Kusiak, W. Li, and Z. Song, Dynamic Control of Wind Turbines, Renewable Energy, Vol. 35, No. 2, 2010, pp. 456–463 [Wind energy].
• A. Kusiak and M.Y. Li, Optimal Decision Making in Ventilation Control, Energy, Vol. 34, No. 11,  2009, pp. 1835-1845 [HVAC energy].
• Z. Song and A. Kusiak, Mining Pareto-Optimal Modules for Delayed Product Differentiation, European Journal of Operational Research, Vol. 201, No. 1,  2010, pp. 123–128 [Manufacturing].
• A. Kusiak, Z. Song, and H.-Y. Zheng, Anticipatory Control of Wind Turbines with Data-Driven Predictive Models, IEEE Transactions on Energy Conversion, Vol. 24, No. 3, 2009, pp. 766-774 [Energy].
• H.-Y. Zheng and A. Kusiak, Prediction of Wind Farm Power Ramp Rates: A Data-Mining Approach, ASME Journal of Solar Engineering, Vol. 131, No. 3, 2009, pp. 031011-1-031011-8 [Wind energy]. 
• A. Kusiak, H.-Y. Zheng, and Z. Song, Wind Farm Power Prediction: A Data-Mining Approach, Wind Energy, Vol. 12, No. 3, 2009, pp. 275-293 [Wind energy].
• A. Kusiak, H.-Y. Zheng, and Z. Song, Short-Term Prediction of Wind Farm Power: A Data-Mining Approach, IEEE Transactions on Energy Conversion, Vol. 24, No. 1, 2009, pp. 125-136 [Wind energy].
• A. Kusiak, H.-Y. Zheng, and Z. Song, On-line Monitoring of Power Curves, Renewable Energy, Vol. 34, No. 6, 2009, pp. 1487-1493 [Wind energy].
• Z. Song and A. Kusiak, Optimizing Product Configurations with a Data-Mining Approach, International Journal of Production Research, Vol. 47, No 7, 2009, pp. 1733-1751 [Manufacturing].
• A. Kusiak, Innovation: A Data-Driven Approach, International Journal of Production Economics, Vol. 122, No. 1, 2009, pp. 440-448 [Innovation acience].
• Z. Song and A. Kusiak, Optimization of Temporal Processes: A Model-Predictive Control Approach, IEEE Transactions on Evolutionary Computation, Vol. 13, No. 1, 2009, pp. 169-179  [Energy].
• A. Kusiak, H.-Y. Zheng, and Z. Song, Models for Monitoring Wind Farm Power, Renewable Energy, Vol. 34, No. 3, 2009, pp. 583-590  [Wind energy].
• A. Kusiak and Z. Song, Clustering-Based Performance Optimization of the Boiler-Turbine System, IEEE Transactions on Energy Conversion, Vol. 23,  No. 2,  2008, pp. 651-658 [Energy topic].
• A. Kusiak and A. Salustri, Computational Intelligence in Product Design Engineering: Review and Trends, IEEE Transactions on Systems, Man, and Cybernetics: Part C, Vol. 37, No. 5, 2007, pp. 766 -778  [Engineering design].
• C. da Cunha, B. Agard, and A. Kusiak, Design for Cost: Module-Based Mass Customization, IEEE Transactions in Automation Science and Engineering, Vol. 4, No. 3, 2007, pp. 350-359 [Mass customization].
• A. Kusiak, M.R. Smith, and Z. Song, Planning Product Configurations Based on Sales Data, IEEE Transactions on Systems, Man, and Cybernetics: Part C, Vol. 37, No. 4, 2007, pp. 602-609 [Mass customization].
• A. Kusiak, Innovation: The Living Laboratory Perspective, Computer-Aided Design and Applications, Vol. 4, No. 6, 2007, pp. 863-876  [Innovation science].
• A. Kusiak and M. Smith, Data Mining in Design of Products and Production Systems, IFAC Annual Reviews in Control, Vol. 31, No. 1, 2007, pp. 147-156 [Design and manufacturing].
• A. Kusiak, Innovation Science: A Primer, International Journal of Computer Applications in Technology, Vol. 28, No. 2-3, 2007, pp. 140-149 [Innovation science].
• Z. Song and A. Kusiak, Constraint-Based Control of Boiler Efficiency:  A Data-Mining Approach,IEEE Transactions on Industrial Informatics, Vol. 3, No. 1, 2007, pp. 73-83 [Energy].
• S. Shah and A. Kusiak, Cancer Gene Search with Data-Mining and Genetic Algorithms, Computers in Biology and Medicine,  Vol. 37, No. 2, 2007, pp. 251-261 [Genetics].
• A. Kusiak, Data Mining: Manufacturing and Service Applications, International Journal of Production Research, Vol. 44, No. 18-19, 2006, pp. 4175-4191 [Manufacturing].
• J.A. Harding, M. Shahbaz, S. Srinivas, and A. Kusiak, Data Mining in Manufacturing: A Review, ASME Transactions: Journal of Manufacturing Science and Engineering, Vol. 128, No. 4, 2006, pp. 969-976 [Manufacturing].
• C. Da Cunha, B. Agard, and A. Kusiak, Data Mining for Improvement of Product Quality, International Journal of Production Research, Vol. 44, No. 18-19, 2006, pp. 4027-4041 [Quality].
• A. Kusiak and Z. Song, Combustion Efficiency Optimization and Virtual Testing: A Data-Mining Approach, IEEE Transactions on Industrial Informatics, Vol. 2, No. 3, 2006, pp. 176-184 [Energy topic].
• A. Kusiak and S. Shah, A Data-Mining-Based System for Prediction of Water Chemistry Faults, IEEE Transactions on Industrial Electronics, Vol. 53, No. 2, 2006, pp. 593-603 [Energy].
• A. Kusiak, C.A. Caldarone, M.D. Kelleher, F.S. Lamb, T.J. Persoon, and A. Burns, Hypoplastic Left Heart Syndrome: Knowledge Discovery with a Data Mining Approach, Computers in Biology and Medicine, Vol. 36, No. 1, 2006, pp.  21-40 [Medical topic].
• J. Feng, Z.-G. Yu, and A. Kusiak, Selection and Validation of Predictive Regression and Neural Networks Models Based on Designed Experiments, IIE Transactions: Design and Manufacturing, Vol. 38, No. 1, 2006, pp. 13-23 [Quality]. 
• S. Shah, A. Kusiak, and M. O’Donnell, Patient-Recognition Data-Mining Model for BCG-plus Interferon Immunotherapy Bladder Cancer Treatment, Computers in Biology and Medicine, Vol. 36, No. 6, 2006, 634-655 [Medical topic].
• A. Kusiak, Data Farming: A Primer, International Journal of Operations Research, Vol. 2, No. 2, 2005, pp. 48-57 [Data farming].
• A. Kusiak, A. Burns, and F. Milster, Optimizing Combustion Efficiency of a Circulating Fluidized Boiler: A Data Mining Approach, International Journal of Knowledge-Based and Intelligent Engineering Systems, Vol. 9, No. 4, 2005, pp. 263-274 [Energy topic].
• A. Kusiak, A. Burns, S. Shah, and N. Novotny, Detection of Events Causing Pluggage of a Coal-Fired Boiler: A Data Mining Approach, Combustion Science and Technology, Vol. 177, No. 12, 2005, pp. 2327-2348 [Energy topic].
• C.-C. Huang, T.-L. Tseng, and A. Kusiak, XML-Based Modeling of Corporate Memory, IEEE Transactions on Systems, Man, and Cybernetics: Part A, Vol. 35,  No. 5,  2005, pp. 629-640 [Knowledge management].
• K. Park and A. Kusiak, Enterprise Resource Planning (ERP) Operations Support System for Maintaining Process Integration, International Journal of Production Research, Vol. 49, No. 43, 2005, pp. 3959-3982 [Manufacturing].
• A. Kusiak, B. Dixon, and S. Shah, Predicting Survival Time for Kidney Dialysis Patients: A Data Mining Approach, Computers in Biology and Medicine, Vol. 35, No. 4, 2005, pp. 311-327 [Medical topic].
• B. Agard and A. Kusiak, Data Mining for Subassembly Selection, ASME Transactions: Journal of Manufacturing Science and Engineering, Vol. 126, No. 3, 2004, pp. 627-631. 
• S.Shah and A. Kusiak, Data Mining and Genetic Programming Based Gene/SNP Selection, Artificial Intelligence in Medicine, 2004, Vol. 31, No. 3, pp. 183-196 [Genetics].
• B. Agard and A. Kusiak, A Data-Mining Based Methodology for the Design of Product Families, International Journal of Production Research, 2004, Vol. 42, No. 15, pp. 2955-2969.
• A. Kusiak, A Data Mining Approach for Generation of Control Signatures, ASME Transactions: Journal of Manufacturing Science and Engineering, Vol. 124, No. 4, 2002, pp. 923-926.
• A. Kusiak, Integrated Product and Process Design: A Modularity Perspective, Journal of Engineering Design, Vol. 13, No. 3, 2002, pp. 223-231. 
• A. Kusiak, Feature Transformation Methods in Data Mining, IEEE Transactions on Electronics Packaging Manufacturing, Vol. 24, No. 3, 2001, pp. 214 -221.
• A. Kusiak, I.H. Law, M.D. Dick, The G-Algorithm for Extraction of Robust Decision Rules: Children’s Postoperative Intra-atrial Arrhythmia Case Study, IEEE Transactions on Information Technology in Biomedicine, Vol. 5, No. 3, 2001, pp. 225-235 [Medical topic].
• A. Kusiak and C. Kurasek, Data Mining of Printed-Circuit Board Defects, IEEE Transactions on Robotics and Automation, Vol. 17, No. 2, 2001, pp. 191-196
• A. Kusiak, Rough Set Theory: A Data Mining Tool for Semiconductor Manufacturing, IEEE Transactions on Electronics Packaging Manufacturing, Vol. 24, No. 1, 2001, pp. 44-50.
• A. Zakarian and A. Kusiak, Process Analysis and Reengineering, Computers and Industrial Engineering, Vol. 41, No. 2, 2001, pp. 135-150.
• D. He, A. Babayan, and A. Kusiak, Scheduling Manufacturing Systems in an Agile Environment, Robotics and Computer Integrated Manufacturing, Vol. 17, No. 1-2, 2001, pp. 87-97.
• A. Kusiak, Decomposition in Data Mining: An Industrial Case Study, IEEE Transactions on Electronics Packaging Manufacturing, Vol. 23, No. 4, 2000, pp. 345-353.
• A. Kusiak, J.A. Kern, K.H. Kernstine, and T.L. Tseng, Autonomous Decision-Making: A Data Mining Approach, IEEE Transactions on Information Technology in Biomedicine, Vol. 4, No. 4, 2000, pp. 274-284 [Medical topic].
• A. Kusiak, Evolutionary Computation in Process Modeling and Programming, Robotica, Vol. 40, No. 3, 2000, pp. 15-19.
• A. Zakarian and A. Kusiak, Analysis of Process Models, IEEE Transactions on Electronics Packaging Manufacturing, Vol. 23, No. 2, 2000, pp. 137- 147.
• A. Kusiak, Evolutionary Computation in Generation of Process Models, International Journal of Agile Manufacturing, Vol. 3, No. 2, 2000, pp. 53-70.
• L. Al-Hakim, A. Kusiak, and J. Mathew, A Graph-theoretic Approach to Conceptual Design with Functional Perspectives, Computer-Aided Design, Vol. 32, No. 14, 2000, pp. 867-875.
• C.X. Feng and A. Kusiak, Robust Tolerance Synthesis with the Design of Experiments Approach, ASME Transactions: Journal of Manufacturing Science and Engineering, Vol. 122, No. 3, 2000, pp. 520-528.
• D.W. He, B. Strege, H. Tolle, and A. Kusiak, Decomposition in Automatic Generation of Petri Nets for Manufacturing System Control and Scheduling, International Journal of Production Research, Vol. 38, No. 6, 2000,  pp. 1437-1457.
• C.C. Huang and A. Kusiak, Synthesis of Modular Mechatronic Products: A Testability Perspective, IEEE/ASME Transactions on Mechatronics, Vol. 4, No. 2, 1999, pp. 119-132.
• A. Zakarian and A. Kusiak, Forming Teams: An Analytical Approach, IIE Transactions on Design and Manufacturing, Vol. 31, No. 1, 1999, pp. 85-97.
• C.C. Huang and A. Kusiak, Modularity in Design of Products and Systems, IEEE Transactions on Systems, Man, and Cybernetics: Part A, Vol. 28, No.1, 1998, 66-77.
• A. Kusiak and D. He, Design for Agility: A Scheduling Perspective, Robotics and Computer-Integrated Manufacturing Systems, Vol. 14, No. 4, 1998, pp. 415-427.
• D. He, A. Kusiak, and T. L. Tseng, Delayed Product Differentiation: A Design and Manufacturing Perspective, Computer-Aided Design, Vol. 30, No. 2, 1998, pp. 105-113.
• D. He and A. Kusiak, Designing an Assembly System for Modular Products, Computers and Industrial Engineering, Vol. 31, No. 1, 1998, pp. 37-52.
• C.C. Huang and A. Kusiak, Manufacturing Control withh a Push-pull Control, International Journal of Production Research, Vol. 36, No. 1, 1998, pp. 251-275.
• D. He and A. Kusiak, Design of Assembly Systems for Modular Products, IEEE Transactions on Robotics and Automation, Vol. 13, No. 5, 1997, pp. 646-655.
• C.X. Feng and A. Kusiak, Design of Tolerances with the Extended Quality Loss Function, ASME Transactions: Journal of Manufacturing Science and Engineering, Vol. 119, No. 4 (A), 1997, pp. 603-610.
• C.X. Feng, A. Kusiak, and C.C. Huang, A Scheduling Model for Setup Time Reduction, ASME Transactions: Journal of Manufacturing Science and Engineering, Vol. 119, No. 4 (A), 1997, pp. 571-579.
• A. Kusiak, T. Letsche, and A. Zakarian, Data Modeling with IDEF1x, International Journal of Computer Integrated Manufacturing, Vol. 10, No. 6, 1997, pp. 470-486.
• A. Kusiak and C.C. Huang, Design of Modular Digital Circuits for Testability, IEEE Transactions on Components, Packaging, and Manufacturing Technology, Part C, Vol. 20, No. 1, 1997, pp. 48-57.
• T. N. Larson, H. March, and A. Kusiak, A Heuristic Approach to Warehouse Layout with Class-Based Storage, IIE Transactions: Design and Manufacturing, Vol. 29, No. 4, 1997, pp. 337-348.
• A. Zakarian and A. Kusiak, Modeling Manufacturing Dependability, IEEE Transactions on Robotics and Automation, Vol. 13, No. 2, 1997, pp. 161-168.
• A. Kusiak and G.H. Lee, Design of Parts and Manufacturing Systems for Reliability and Maintainability, International Journal of Advanced Manufacturing Technology, Vol. 13, No. 1, 1997, pp. 67-76.
• U. Belhe and A. Kusiak, Dynamic Scheduling of Design Activities with Resource Constraints, IEEE Transactions on Systems, Man, and Cybernetics: Part A, Vol. 27, No. 1, 1997, pp. 105-111.
• A. Kusiak and D. He, Design for Agile Assembly: An Operationsl Perspective, International Journal of Production Research, Vol. 35, No. 1, 1997, pp. 157-178.

Publications prior to 1991 are available upon request.

1996 Publications

• Modeling Relationships Among Design Activities, U. Belhe and A. Kusiak, ASME Transactions: Journal of Mechanical Design, Vol. 118, No. 4, pp. 454-460, 1996.
• Managing Design Processes: A Risk Assessment Approach, N. Larson and A. Kusiak, IEEE Transactions on Systems, Man, and Cybernetics: Part A, Vol. 26, No. 6, pp. 749-759, 1996.
• Negotiation in Constraint-Based Design, A. Kusiak, J. Wang, and D.W. He, ASME Transactions: Journal of Mechanical Design, Vol. 118, No. 4, pp. 470-477, 1996.
• System Reliability Modeling for Analysis of Process Models, N. Larson and A. Kusiak, International Journal of Computer-Aided Engineering, Vol. 3, No. 4, 1996, pp. 279-290.
• Development of Modular Products, A. Kusiak and C.C. Huang, IEEE Transactions on Components, Packaging, and Manufacturing Technology: Part A, Vol. 19, No. 4, pp. 523-538, 1996.
• Representation of Functions and Features in Detail Design, C.X. Feng, C.C. Huang, A. Kusiak, and P.G. Li, Computer-Aided Design, Vol. 28, No. 12, pp. 961-971, 1996.
• Cost Evaluation in Development with Form Features, C.X. Feng, A. Kusiak, and C.C. Huang, Computer-Aided Design, 28(11), pp. 879-885, 1996.
• Risk Assessment of Process Models, A. Kusiak and A. Zakarian, Computers and Industrial Enginering, 30(4), pp. 599-610, 1996.
• The House of Quality in a Design Process, U. Belhe and A. Kusiak, International Journal of Production Research, 34(8), pp. 2119-2131, 1996.
• Reliability Evaluation of Process Models, by A. Kusiak and A. Zakarian, IEEE Transactions on Components, Packaging, and Manufacturing Technology - Part A, 19(2), pp. 268-275, 1996.
• Scheduling Design Activities with a Pull System Approach, by U.D. Belhe and A. Kusiak, IEEE Transactions on Robotics and Automation, 12(1), pp. 15-21, 1996.
• A Scheduling Problem in Glass Manufacturing, by D.W. He, A. Kusiak, and A. Artiba, IIE Transactions, 28(2), pp. 129-139, 1996.
• Overview of Kanban Systems, by C.C. Huang and A. Kusiak, International Journal of Computer Integrated Manufaturing, 9(3), pp. 169-189, 1996.
• Performance Analysis of Modular Products, by D.ModularW. He and A. Kusiak, International Journal of Production Research, 34(1), pp. 253-272 ,1996.
• Robust Tolerance Design for Quality, by A. Kusiak and C.X. Feng, ASME Transactions: Journal of Engineering for Industry,118(1), pp. 166-169, 1996.

1995 Publications

• Decomposition and Representation Methods in Mechanical Design, by Andrew Kusiak and Nick Larson, Transactions of the ASME, Special 50th Anniversary Design Issue, 117(June), pp. 17-24, 1995.
• Work-In-Process Space Allocation: A Model and an Industrial Application, by Nick Larson and Andrew Kusiak, IIE Transactions: Design and Manufacturing, 27, pp. 497-506, 1995  
• Constraint-Based Design of Parts, by A. Kusiak and C.X. Feng, Computer-Aided Design, 27(5), pp. 343-352, 1995.
• Deterministic Tolerance Synthesis: A Comparative Study, by A. Kusiak and C.X. Feng, Computer-Aided Design, 27(10), pp. 759-768, 1995.
• A Structured Approach for Analysis of Designign Processes, by A. Kusiak, J. Wang, D.W. He, and C.X. Feng, IEEE Transactions on Components, Packaging, and Manufacturing Technology - Part A, 18(3), pp. 664-673, 1995.
• Dependency Analysis in Constraint Negotiation, by A. Kusiak and J. Wang, IEEE Transactions on Systems, Man, and Cybernetics, 25(9), pp. 1301-1313, 1995.
• Resource Constrained Schedulingg of Hierarchically Structured Design Activity Networks, by U. Belhe and A. Kusiak, IEEE Transactions on Engineering Management, 42(2), pp. 150-158, 1995.
• Reason Maintenance in Product Modeling, by R. Vujosevic, A. Kusiak, and E. Szczerbicki, ASME Transactions: Journal of Engineering for Industry, 117(2), pp. 223-231, 1995.

1994 Publications

• Constraint-Based Design of Parts, by C.X. Feng and A. Kusiak, Computer-Aided Design, 27(5), pp. 343-352, 1995.
• Reengineering of Design and Manufacturing Processes, by Andrew Kusiak, Nick Larson, and Juite Wang, Computers and Industrial Engineering, 26(3), pp. 521-536, 1994.
• Grouping Parts with a Neural Network, by Y.K. Chung and A. Kusiak, SME Journal of Manufacturing Systems, 13(4), pp. 262-275, 1994.
• Layout of Machines in Cellular Manufacturing Systems, by A. Kusiak and K. Park, International Journal of Manufacturing System Design, 1(1), pp. 31-39, 1994.
• Computer-Aided Fixture Design: A Review, by S.K. Hargrove and A. Kusiak, International Journal of Production Research, 32(4), pp. 733-753, 1994.  
• Design of Components for Schedulability, by A. Kusiak and W. He, European Journal of Operational Research, 76(1), pp. 49-59, 1994.
• Concurrent Engineering: Modeling the Negotiation Process, by A. Kusiak and J. Wang, Group Decision and Negotiation, 3(1), pp. 69-91, 1994.

1993 Publications

• A Knowledge-Based System for Building of Models, by A. Kusiak and J. Wang, Revue des systemes de decision, 2(3-4), pp. 293-311, 1993.
• Decomposition of the Design Process, by A. Kusiak and J. Wang, ASME Transactions: Journal of Mechanical Design, 115(4), pp. 687-695, 1993.
• Performance Analysis of Design Process Using Timed Petri Nets, by U. Belhe and A. Kusiak, Concurrrent Engineering: Research and Applications, 1(3), pp. 147-152, 1993.
• Scheduling with Alternative Operations, by J. Ahn, W. He, and A. Kusiak, IEEE Transactions on Robotics and Automation, 9(3), pp. 297-303, 1993.
• Transformation from Conceptual to Embodiment Design, by A. Kusiak and E. Szczerbicki, IIE Transactions: Design and Manufacturing, 25(4), pp. 6-12, 1993.
• Designing Cellular Manufacturing Systems: Branch-and-bound and A* Approaches, by A. Kusiak, W.J. Boe, and C.H. Cheng, IIE Transactions: Design and Manufacturing, 25(4), pp. 46-56, 1993.
• Efficient Organizing of Design Activities, by A. Kusiak and J. Wang, International Journal of Production Research, 31(4), pp. 753-769, 1993.

1992 Publications

• A Formal Approach to Specifications in Conceptual Design, by A. Kusiak and E. Szczerbicki, ASME Transactions: Journal of Mechanical Design, 114(4), pp. 659-666, 1992.
• Similarity Coefficient Algorithms for Solving the Group Technology Problem, by A. Kusiak and M. Cho, International Journal of Production Research, 30(11), pp. 2633-2646, 1992.
• Scheduling Manufacturing Systems, by W. He and A. Kusiak, Computers in Industry, 20, pp. 163-175, 1992.
• Intelligent Scheduling of Automated Machining Systems, by A. Kusiak and J. Ahn, Computer-Integrated Manufacturing Systems, 5(1), pp. 3-14, 1992 (Reprinted in A. Kusiak (Ed.), Intelligent Design and Manufacturing, John Wiley, New York, N.Y., pp. 421-447, 1992).
• Selection of Machinable Volumes: an Object-Oriented Approach, by R. Vujosevic and A. Kusiak, Expert Systems With Applications, 4(3), pp. 273-283, 1992.

1991 Publications

• GT/ART: Using Neural Networks to Form Machine Cells, by A. Kusiak and Y.-K. Chung, ASME Manufacturing Review, 4(4), pp. 293-301, 1991.
• Branching Algorithms for Solving the Group Technologyogy Problem, by A. Kusiak, SME Journal of Manufacturing Systems, 10(4), pp. 332-343, 1991.
• Process Planning: A Knowledgee-Based and Optimization Perspective, by A. Kusiak, IEEE Transactions on Robotics and Automation, 7(3), pp. 257-266, 1991.
• Intelligent Design Synthesis: An Object-Oriented Approach, byy A. Kusiak, E. Szczerbicki, and R. Vujosevic, International Journal of Production Research, 29(7), pp. 1291-1308, 1991.
• Automation Novel Approach to Decomposition of Design Specifications and Search for Solutions, by A. Kusiak and E. Szczerbicki, and K. Park, International Journal of Production Research, 29(7), pp. 1391-1406, 1991.