Speakers: Hesham Ali, PhD

Hesham Ali, PhD

Professor of Computer Science
Research Collaborator, Mayo Clinic
Director of UNO Bioinformatics Core Facility
College of Information Science and Technology
University of Nebraska Omaha

 

Hesham H. Ali is a Professor of Computer Science and the director of the University of Nebraska Omaha (UNO) Bioinformatics Core Facility. He served as the Lee and Wilma Seemann Distinguished Dean of the College of Information Science and Technology at UNO between 2006 and 2021. He has published numerous articles in various IT areas, including scheduling, distributed systems, data analytics, wireless networks, and Bioinformatics. He has published two books in scheduling and graph algorithms, and several book chapters in Bioinformatics. He has been serving as the PI or Co-PI of several projects funded by NSF, NIH and Nebraska Research Initiative in the areas of data analytics and Bioinformatics. He has also been leading a Research Group that focuses on developing innovative computational approaches to model complex biomedical systems and analyze big bioinformatics data using AI tools and Network models. The research group is currently developing next generation big data analytics tools for analyzing large heterogeneous biological and health data associated with various biomedical research areas, particularly projects associated with infectious diseases, microbiome studies, early childhood development and aging research. He has led several local and national outreach initiatives, including Women in IT initiatives, IT education and training programs, and IT summer internship camps.

How to obtain next generation biomarkers Using AI Tools and Network Models?

The last several years witnessed major advancements in the development of technologies with the goal of collecting various types of data in many application domains. The biomedical domain represents a clear example of such development. Every time the continuously evolving biomedical technologies make it possible for bioscience researchers to have access to new type of biological data, exciting research questions attract new studies: Would it possible for the new data to provide novel biological signals or biomarkers that can be used for supporting biomedical research and advancing healthcare? Would the biological signals or biomarkers associated with the new data be robust enough to be used for the purpose of early disease diagnosis or the assessment of different treatments for certain health conditions. We discuss how recent technologies have made it possible to generate new types of data that can be used to obtain a new generation of biomarkers. We highlight biomarkers obtained from mobile wearable devices, microbiome data, and nanoparticles profiles. We briefly discuss how the new AI tools and network models can leverage the new biomarkers in supporting biomedical research.