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Kafayat Adeoeye

As a multifaceted individual with curiosity for technology and innovation. My Journey into AI wasn't merely a matter of following trends rather, it was a genuine fascination with the limitless possibilities of AI with the ability to create algorithms that could think, learn, and adapt, just like the human mind. I completed my undergraduate degree in electronic system engineering and I then went on to pursue a master's degree in computer science artificial intelligence at the University of Nottingham. During my master's degree, I focused on big data and machine learning analytics. Though, my interest in AI are broad and diverse and I am particularly interested in the potential of AI to improve healthcare to develop new diagnostic tools and treatments, improve the efficiency of clinical trials, and personalize care for patients. I have worked on creating models capable of diagnosing cancer types to detecting genetic hemochromatosis early, conducting clustering analysis, and performing NLP sentiment analysis. 

Responsible AI, for me, is about ensuring that AI is used for good and should involve addressing bias and fairness, ensuring transparency in decision-making processes, and developing of AI systems that are accountable to the society. Responsible AI is not just a moral imperative but also a vital component for ensuring the long-term acceptance and viability of AI solutions that not only advance but also uphold the highest ethical standards to safeguard the integrity and trustworthiness of AI in healthcare research. I am excited to be a part of the growing field of responsible AI and committed to developing new methods for making AI more responsible and educating the public about the importance of responsible AI.  

Building Responsible AI in Neuroscience
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