Dr. Oluwasanmi O. Adenaiye is a research scientist with about ten years of combined experience in both clinical and academic environments. His multidisciplinary background encompasses medicine, quantitative biomedical and clinical research, and machine learning, with professional roles at the University of Pittsburgh and the University of Maryland. Dr. Adenaiye earned his medical degree from the University of Ilorin in Nigeria and holds a Master of Science in Environmental Health Science from the University of Maryland, College Park.
Throughout his career, Dr. Adenaiye has been instrumental in integrating statistical methods and machine learning techniques to develop innovative models for biomedical and clinical research. He has enhanced algorithms such as Dijkstra's for network analysis to monitor the spread of infections within communities. Additionally, he has worked on developing predictive models for the pre-symptomatic stages of infections by utilizing data from smart wearable devices, employing gradient boosting machines and deep learning approaches.
His research interests include trajectory data analysis for health monitoring and supporting individuals with physical disabilities. By analyzing patient movement patterns and behaviors using advanced techniques like transformers and long short-term memory (LSTM) networks, Dr. Adenaiye's research work aims to improve the analysis and development of personalized interventions and assistive technologies that improve mobility and daily functioning for those with physical disabilities through the enhancement of quantitative tools. Furthermore, he is interested in image segmentation in medical imaging to advance diagnosis and treatment in physical medicine and rehabilitation.
In the early years of his academic career, Dr. Adenaiye was active in primary and secondary research projects focused on evaluating technology, protocols, interventions, and data associated with improving patient outcomes in infectious diseases. He has collaborated with numerous investigators on federally funded grant applications and has served as a researcher on several projects supported by organizations like the National Institutes of Health (NIH), the Bill and Melinda Gates Foundation,the Defense Advanced Research Projects Agency (DARPA), and the Biomedical Advanced Research and Development Authority (BARDA).
Dr. Adenaiye played a significant role in the Coronavirus Pandemic Intervention Project, where he collaborated with other investigators on hypothesis formulation, data management, and analysis. He also contributed to developing safety protocols and procedures for clinical staff during the COVID-19 pandemic.
- Utilizing machine learning algorithms to address biomedical and clinical challenges, with a focus on health metrics monitoring, electronic health record (EHR) data, and genomics.
- Developing innovative methods for trajectory data analysis in health monitoring and supporting individuals with physical disabilities.
- Enhancing the development of tools that support individuals with physical disabilities through the use of artificial intelligence, transformers, LSTM, and other cutting-edge techniques.
- Advancing image segmentation techniques in medical imaging to improve diagnosis and treatment within physical medicine and rehabilitation.