Rahmat Adesunkanmi

Research Focus: Robust Machine Learning Algorithms

BS EE, University of Ibadan, Nigeria
MS EE, Iowa State University, 2020

I am pursuing noise robust machine learning for my PhD, where information about data distributions is incorporated into the algorithms to reduce outliers’ impact. I am working as a graduate teaching assistant, where I have had the privilege of mentoring and academically impacting the lives of over 400 undergraduates. I am also an active member of my professional society by being a participating member of the IEEE (Institute for Electrical and Electronics Engineering), NSBE (National Society for Black Engineers), and gradSWE (Graduate students Society for Women in Engineering). I have kept my passion for contributing to women’s and minorities’ diversity and inclusion in society by being a member of the Diversity and Inclusion committee of the ISU Student Union Board (SUB).

Publications

Adesunkanmi, Rahmat, and Ratnesh Kumar. “Expectation Distance-Based Distributional Clustering for Noise-Robustness.” IEEE Transactions on Knowledge and Data Engineering, 2024.
BibTeX
Link

@article{10502316,
  author = {Adesunkanmi, Rahmat and Kumar, Ratnesh},
  journal = {IEEE Transactions on Knowledge and Data Engineering},
  title = {Expectation Distance-Based Distributional Clustering for Noise-Robustness},
  year = {2024},
  volume = {},
  number = {},
  pages = {1-12},
  keywords = {Meteorology;Temperature distribution;Costs;Precipitation;Noise;Clustering algorithms;Noise measurement;Clustering algorithms;expectation distance;Wasserstein distance;uncertain data},
  doi = {10.1109/TKDE.2024.3386401}
}

Hossain, Ramij Raja, Rahmat Adesunkanmi, and Ratnesh Kumar. “Data-Driven Linear Koopman Embedding for Networked Systems: Model-Predictive Grid Control.” IEEE Systems Journal, 2023.
BibTeX
Link

@article{hossain2023koopman,
  author = {Hossain, Ramij Raja and Adesunkanmi, Rahmat and Kumar, Ratnesh},
  journal = {IEEE Systems Journal},
  title = {Data-Driven Linear Koopman Embedding for Networked Systems: Model-Predictive Grid Control},
  year = {2023},
  area = {Energy},
  subarea = {Energy Systems},
  doi = {10.1109/JSYST.2023.3253041}
}