Dr. Gaurav Nanda is an Assistant Professor in the School of Engineering Technology at Purdue University with focus in Industrial Engineering Technology. He works on research problems involving Applied Machine Learning, Text Mining, and Intelligent Decision Support Systems with applications in Safety, Industry 4.0, Healthcare, Learning Technologies, and other areas. He teaches courses in the areas of Supply Chain, Operations Management, Human Factors, Warehouse and Inventory Management, and Lean and Sustainable Systems.
Dr. Nanda obtained his Ph.D. in Industrial Engineering from Purdue University and his Bachelors (B.Tech.) and Masters (M.Tech.) from Indian Institute of Technology (IIT) Kharagpur, India. He worked as a postdoctoral researcher at Purdue University for two years and in the software industry for five years.
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.
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.
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.
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.
Institute of Industrial and Systems Engineers (IISE)