Professor Paffenroth's research focuses on is focused on applications of mathematically principled machine learning techniques to problems in several application domains including manufacturing, chemical sensors, cyber-defense, chemical engineering, and nanomaterials.Full list of publications in [SITE NAME] --->
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Cheng, F., Belden, E. R., Li, W., Shahabuddin, M., Paffenroth, R. C., & Timko, M. T. (2022). Accuracy of predictions made by machine learned models for biocrude yields obtained from hydrothermal liquefaction of organic wastes.Chemical Engineering Journal, 442, . https://doi.org/10.1016/j.cej.2022.136013
Bahadur, N., Lewandowski, B., and Paffenroth, R. (2022). Dimension Estimation Using Autoencoders and Application.Deep Learning Applications, (3rd ed.). Springer Nature.
Mahindre, Karkare, R., Paffenroth, R., & Jayasumana, A. (2021, December 15-18). A Pre-training Oracle for Predicting Distances in Social Networks. 2021 IEEE International Conference on Big Data (Big Data), 4126–4135. https://doi.org/10.1109/BigData52589.2021.9671784
Zhou, C., Paffenroth, R.C. (2017, August 13-17). Anomaly detection with robust deep autoencoders. Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 665-674. https://doi.org/10.1145/3097983.3098052