From Geoffrey Anyanwu, Enugu
Nigerian born science whiz kid, Tony Okeke, has been nominated by the United States of America (USA)-based interdisciplinary Scientific Honor Society, Sigma Xi, for full membership of the society.
According to the society in a letter signed by the Executive Director and Chief Executive Officer, Jamie Vernon, and Manager of Membership and Chapters, Daniela Carlson, Okeke who is the 2018 Nigerian National Petroleum Corporation National Science Quiz Champion, got the nomination because of his scholarly achievements and contributions to the advancement of knowledge in his field, which is Biomedical Engineering.
“Dear Tony Okeke, in recognition of your scholarly achievements and contributions to the advancement of knowledge in your field, it is our pleasure to nominate you for Full Membership in Sigma Xi, The Scientific Research Honor Society,” the society said in the letter.
Founded in 1886, Sigma Xi, honours excellence in scientific investigation and recognises researchers for the values the society holds in high esteem.
More than 200 Nobel Laureates are members, “All joining together under the single mission to enhance the health of the research enterprise, foster integrity in science and engineering, and promote the public’s understanding of science for the purpose of improving the human condition.”
The letter to Okeke also said: “Membership in Sigm Xi distinguishes you as an exceptional contributor to the research community and offers a myriad of opportunities to support your career.”
It would, in addition, offer him access to programmes and initiatives that recognise innovators, support interdisciplinary research, foster responsible conduct of research, train researchers in science communication, cultivate the next generation of researchers, and promote the public understanding of science.
In 2023, during the Philly CodeFest hackathon in Philadelphia, USA, Tony led an interdisciplinary team in developing MedDibia, an AI-powered iOs application for healthcare delivery in underserved communities, especially in developing countries.
“As the project lead, he developed machine learning solutions to power core functionality. This included training a classifier to predict diseases from lists of symptoms. Additionally, he utilised transfer learning to adapt a pre-trained, “Convolutional Neural Network,” to identify skin lesions by training on over 15,000 images across 23 skin diseases. He used a FLASK API to integrate these models into a unified diagnostic platform which powered an iOS app — developed in parallel by other teammates.
“This project, out of the 40 entries submitted to Philly CodeFest, emerged the winner of Philly CodeFest 2023 Collaborative Team Award, one of the top prizes in the hackathon, affirming the innovative nature of their approach and showed, firsthand, how machine learning models can augment clinical diagnostics and make healthcare information more accessible, envisioning digital diagnostic assistants that provide reliable, interpretable guidance to augment the decisions of healthcare workers.”
His research is said to have focused on leveraging bioinformatics and computational methods to investigate molecular mechanisms related to identifying and predicting potential safety concerns in the various areas across drug development.