CharlesCharles C Onu

MSc/PhD student, Computer Science, McGill University (2016 - 2020)
charles.onu { at } mail.mcgill.ca

I conduct my research at the intersection of artificial intelligence and medicine at McGill’s Reasoning and Learning lab, under the supervision of lab co-director and director of the DeepMind lab in Montreal, Prof. Doina Precup.

I am the founder of Ubenwa, a social venture aiming to save newborn lives through low-cost, cry-based diagnostic technology powered by AI.

I am interested in healthcare applications of machine learning such as diagnostic and intelligence-based decision support systems.

Curriculum Vitae

Conferences and Papers

2018

  1. Undersampling and Bagging of Decision Trees in the Analysis of
    Cardiorespiratory Behavior for the Prediction of Extubation
    Readiness in Extremely Preterm Infants (under review)
    Kanbar L. J.*, Onu C. C.*, Shalish W., Brown K., Sant’Anna G. M., Kearney R. E., Precup D.
    40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), 2018
  2. Saving Newborn lives at Birth Using Machine Learning
    Onu C C, Udeogu I, Ndiomu E, Kengni U , Precup D , Sant’anna G M , Alikor E , Opara P
    UNESCO Chair in Technologies for Development (Tech4Dev), 2018
  3. Bringing diversity of experience into decision-making about surgery: developing an app for that (Link)
    Ilja Ormel, Susan Law, Michel Lortie, Charles C Onu, Donna Tataryn
    International Journal of Whole Person Care, Vol 5 No 1, 2018

2017

  1. Ubenwa: Cry-based Diagnosis of Birth Asphyxia (Link)
    Onu C C, Udeogu I, Ndiomu E, Kengni U , Precup D , Sant’anna G M , Alikor E , Opara P
    NIPS 2017 Workshop on Machine Learning for the Developing World
  2. Predicting Extubation Readiness in Extreme Preterm Infants based on Patterns of Breathing (Link)
    Onu C. C., Kanbar L. J., Shalish W., Brown K., Sant’Anna G. M., Kearney R. E., Precup D.
    10th IEEE Symposium Series on Computational Intelligence (SSCI), 2017
  3. Visualizing Research Productivity in Sub-Saharan Africa: The Case of Computer Science
    Meikleham, A.; Negro, L. M.; Onu, C. C.; Harsh, M.; Bal, R.
    15th International Globelics Conference, 2017
  4. A Semi-Markov Chain Approach to Modeling Respiratory Patterns Prior to Extubation in Preterm Infants (Link)
    Onu C. C.*, Kanbar L. J.*, Shalish W., Brown K., Sant’Anna G. M., Kearney R. E., Precup D.
    39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), 2017

2015

  1. SVM Approach to Cry-based diagnosis of Birth Asphyxia
    Charles C Onu, Innocent Udeogu, Eyenimi Ndiomu
    Award: Best Paper, Workshop on Machine Learning in Healthcare
    Neural Information and Processing Systems (NIPS), 2015

2014

  1. Harnessing Infant Cry for Swift, Cost-effective Diagnosis of Perinatal Asphyxia in Low Resource Settings
    Charles C Onu
    International Humanitarian Technology Conference (IHTC), 2014
    Paper on IEEE Explore
  2. Harnessing Mobile Technology in the Diagnosis of Perinatal Asphyxia
    Charles C Onu
    UNESCO Chair in Technologies for Development (Tech4Dev), 2014

*Equal contribution

Current Projects

  1. Apex
    An interdisciplinary project amongst researchers in McGill’s departments of Computer Science, Biomedical Engineering and Neonatology. The Apex project is aimed at developing (ml-based) methodologies for predicting extubation readiness in extremely preterm newborns.
  2. Ubenwa
    Supported by the NGO – Fisher Foundation for Sustainable Development in Africa, this is project is aimed at developing reliable (mobile) system for diagnosing perinatal asphyxia in infant though analysis of their cry.
  3. Health Experiences Canada
    Meeting information, social and psychological needs of patients preparing for breast cancer surgery. Involves development of machine-learning based recommender system for delivery of care videos.

 

 

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