Wisdom O. Ikezogwo

Email  |  CV  |  Google Scholar  |  GitHub |  LinkedIn 

I am a 2nd year PhD student at Graphics and Imaging Laboratory at the Paul G. Allen School for Computer Science & Engineering, where I work with Professor Linda Shapiro.

Working on machine learning for medical image analysis, with a focus on tackling open problems on clinical development and deployement of models.

profile photo

My research interest lies in developing state-of-the-art machine learning techniques for medical image analysis with a special focus on tackling challenges of clinical deployment of ml models such as distributional shift, and explainability, enabling robustness and trust of these deployed models.

clean-usnob Multi-modal Masked Autoencoders Learn Compositional Histopathological Representations.
W.O. Ikezogwo, Mehmet Saygin Seyfioglu, Linda Shapiro
Extended abstract: Machine Learning for Health (ML4H), Dec 2022.
clean-usnob Supervised domain generalization for integration of disparate scalp EEG datasets for automatic epileptic seizure detection
K.P. Ayodele, W.O. Ikezogwo, M.A. Komolafe, P. Ogunbona
Computers in Biology and Medicine Volume 120, May 2020, 103757

We use supervised domain generalization to combine disparate EEG datasets and a recurrent convolutional neural network detector to test the generalizability of the trained model on an out-of-distribution private epilepsy seizure dataset.

clean-usnob Empirical Characterization of the Temporal Dynamics of EEG Spectral Components.
K.P. Ayodele, W.O. Ikezogwo, Anthony A. Osuntunyi
International Journal of Online and Biomedical Engineering (iJOE) Volume 16, Dec 2020.
cs188 {TA} CSE 160: Data Programming, Fall 2021 & Winter 2022.

{TA} EEE 203/201: Fundamentals of Electronic & Electrical Engr, First Semester 2019.


Summer Schools : IBRO-SIMONS Computational neuroscience summer school | 2020 | CAPETOWN

Website credits: Jon Barron