SDG 4: Quality Education - Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all
My research focuses on compressed sensing, machine learning, signal processing, and the interaction between mathematics, computer science and software engineering. My interests range from theoretical results to algorithms for tackling practical applied problems, and I enjoy problems most when mathematical results lead to efficient software implementations for big data. I am looking forward to working with students at all levels and backgrounds who share an interest in mathematics, software, or data. Some problems that have captured my interest include network analysis for cyber defense, and signal processing and inference for arrays of chemical sensors. In my spare time I enjoy fencing, hiking, skiing, tennis, computer games, and spending time with my family!
Visit Digital WPI to view student projects advised by Professor Paffenroth
My research focuses on compressed sensing, machine learning, signal processing, and the interaction between mathematics, computer science and software engineering. My interests range from theoretical results to algorithms for tackling practical applied problems, and I enjoy problems most when mathematical results lead to efficient software implementations for big data. I am looking forward to working with students at all levels and backgrounds who share an interest in mathematics, software, or data. Some problems that have captured my interest include network analysis for cyber defense, and signal processing and inference for arrays of chemical sensors. In my spare time I enjoy fencing, hiking, skiing, tennis, computer games, and spending time with my family!
Visit Digital WPI to view student projects advised by Professor Paffenroth
SDG 4: Quality Education
SDG 9: Industry, Innovation, and Infrastructure
SDG 9: Industry, Innovation, and Infrastructure - Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
SDG 12: Responsible Consumption and Production
SDG 12: Responsible Consumption and Production - Ensure sustainable consumption and production patterns
SDG 13: Climate Action
SDG 13: Climate Action - Take urgent action to combat climate change and its impacts
Scholarly Work
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 Google Scholar
- Full list of publications in Scopus
- Full list of publications in DBLP
Featured works:
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