Safety

• Divya Venkatesh, J., Jaiswal, A., & Nanda, G. (2024). Comparing human text classification performance and explainability with large language and machine learning models using eye-tracking. Scientific Reports, 14(1), 14295.
• Catchpoole, J., Nanda, G., Vallmuur, K., Nand, G., & Lehto, M. (2022). Application of a Machine Learning–Based Decision Support Tool to Improve an Injury Surveillance System Workflow. Applied clinical informatics, 13(03), 700-710.
• Nanda, G., Vallmuur, K., & Lehto, M. (2020). Intelligent human-machine approaches for assigning groups of injury codes to accident narratives. Safety science, 125, 104585. 
• Nanda, G., Vallmuur, K., & Lehto, M. (2018). Improving Autocoding Performance of Rare Categories in Injury Classification: Is More Training Data or Filtering the Solution? Accident Analysis and Prevention, 110, 115-127. 
• Nanda, G., Grattan, K. M., Chu, M. T., Davis, L. K., & Lehto, M. R. (2016). Bayesian decision support for coding occupational injury data. Journal of Safety Research, 57, 71-82. 

Smart Manufacturing

• Senarathne, L. R., Nanda, G., & Sundararajan, R. (2023). Identifying salient features of cooling energy usage of commercial buildings using explainable artificial intelligence. Advances in Building Energy Research, 17(5), 489-506.
• Han, Y., Nanda, G., & Moghaddam, M. (2023). Attribute-Sentiment-Guided Summarization of User Opinions From Online Reviews. Journal of Mechanical Design, 145(4), 041401.
• Senarathne, L. R., Nanda, G., & Sundararajan, R. (2022). Influence of building parameters on energy efficiency levels: a Bayesian network study. Advances in Building Energy Research, 16(6), 780-805.
• Richards, G., Athinarayanan, R., Balakreshnan, B., Bennett, J., Weatherly, A., Zaccaria,J., Zink, P., Yamasaki, J., Newell, B., Nanda, G., & Mao, H. (2021). A Collaboratively Developed Platform to Introduce Fundamentals of IoT and IIoT. SSRN 38596722. 
• Balakreshnan, B., Richards, G., Nanda, G., Mao, H., Athinarayanan, R., & Zaccaria, J. (2020). PPE Compliance Detection using Artificial Intelligence in Learning Factories. Procedia Manufacturing, 45, 277-282. 
• Nanda, G., Tan, J., Auyeung, P., & Lehto, M. (2013). Improving Efficiency of Organizational Reliability Engineering Knowledge using Keywords. Institute of Industrial Engineers (IIE) Annual Conference. San Juan, USA. 

STEM Education

• Nanda, G., Douglas, K. A., Waller, D. R., Merzdorf, H. E., & Goldwasser, D. (2021). Analyzing Large Collections of Open-Ended Feedback from MOOC Learners Using LDA Topic Modeling and Qualitative Analysis. IEEE Transactions on Learning Technologies, vol. 14, no. 2, pp. 146-160. 
• Nanda, G., Lehto, M., & Nof, S. (2014). User Requirement Analysis for an Online Collaboration Tool for Senior Industrial Engineering Design Course. Human Factors and Ergonomics in Manufacturing & Service Industries, Vol. 24, Issue 5, 557-573. 
• Nanda, G., Douglas, K. A. (2019). Decision Support System for Categorizing MOOC Discussion Forum Posts Using Machine Learning. Educational Data Mining (EDM 2019), Montreal, Canada. 
• Nanda, G., Hicks, N. M., Waller, D. R., Douglas, K. A., Goldwasser, D. (2018).Understanding Learners' Opinion about Participation Certificates in Online Courses using Topic Modeling. Educational Data Mining (EDM 2018), Buffalo, NY, USA. 

Healthcare

• Yin, S., Nanda, G., & Sundararajan, R. (2023). Tackling bias in the data for breast cancer prediction using machine learning-based decision support. Biostatistics & Epidemiology, 7(1), e-2207919.
• Nanda, G., Vallmuur, K., & Lehto, M. (2019). Semi-automated Text Mining Strategies for Identifying Rare Causes of Injuries from Emergency Room Triage Data. IISE Transactions on Healthcare Systems Engineering, 9 (2), 157-171. 
• Li, M., Nanda, G., & Sundararajan, R. (2021). Evaluating Different Machine Learning Models for Predicting the Likelihood of Breast Cancer. Advanced Aspects of Engineering Research Vol. 2, 132-142.