Scientific Conferences

INVITED TALKS

1. Machine Learning Prediction Model for Acute Organ Failure in critically ill SCD patients, Virtual symposium on Application of machine learning in sickle cell disease, Foundation for Sickle Cell Disease Research, 2022

2. Biorepository and Integrative Genomics (BIG) Initiative, Omics Symposium 2022, High-Performance Scientific Computing, UT Knoxville

3. National COVID Cohort Collaborative (N3C) data for studying COVID-19 Optimal Treatment Strategies, COVID-19 Research Study Group, Le Bonheur Children's Hospital, Memphis, Tennessee, 2021

4. Single-nucleus RNA-sequencing of human liver reveals cellular heterogeneity, Bi-weekly Translational Research Meeting, James D. Eason Transplant Institute at Methodist University Hospital, Memphis, Tennessee, 2019

5. Interactive Platform for High-Performance Computing, Research Data Management Symposium, Memphis, Tennessee, 2019

6. Using the Advanced Compute Facility of the Joint Institute of Computational Sciences, Hot Topics in Research, Memphis, Tennessee, 2019

7. Machine learning predicts early-onset acute organ failure in critically ill patients with sickle cell disease, Bi-weekly Translational Research Meeting, James D. Eason Transplant Institute at Methodist University Hospital, Memphis, Tennessee, 2019

8. Machine learning approaches for cancer prediction and potential tissue-specific cancer biomarker identification, Complex Biosystems Seminar Series, University of Nebraska Lincoln, 2017

9. Development of machine learning models for microarray data reveals potential tissue-specific cancer biomarkers, Molecular Mechanisms of Disease Seminar Series, University of Nebraska-Lincoln, 2017

10. A Comprehensive network immune system model to study the infectious diseases in humans, 18th International Conference on Systems Biology, Blacksburg, Virginia, 2017

11. A comprehensive computational model of the immune system, Complex Biosystems Seminar Series, University of Nebraska-Lincoln, 2015

12. Application of a hierarchical enzyme classification method reveals the role of gut microbiota in human metabolism, International Conference on Intelligent Biology and Medicine, San Antonio, Texas, 2014

13. Application of Hierarchical enzyme classification method reveals the role of the gut microbiome in human metabolism, Genetics Cell Biology and Anatomy Seminar Series, University of Nebraska Medical Center, 2013.

INVITED POSTER PRESENTATION

1. Machine learning predicts early onset of sepsis from continuous physiological data of critically ill patients, Healthcare Innovations and Point-of-Care Technologies, IEEE EMB, National Institutes of Health, Bethesda, Maryland, 2019

2. Identification of potential tissue-specific cancer biomarkers and development of cancer versus normal genomic classifiers, Molecular Mechanisms of Disease Annual Symposium, Lincoln, Nebraska, 2017

3. Dynamical network model of the human immune system to study infectious diseases, International Conference on Systems Biology of Human Disease, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, 2016

4. A comprehensive dynamical network model of human immune system, Keystone Symposia Conference, Systems Immunology: From molecular networks to human biology, Big Sky, Montana, 2016

5. A comprehensive dynamical network model of the human immune system, Sixteenth Annual Symposium in Virology, Lincoln, Nebraska, 2016

6. Computational systems biology efforts to better understand diseases, Molecular Mechanisms of Disease Annual Symposium, Lincoln, Nebraska, 2015

7. Hierarchical Prediction of Enzyme Classes Using Ensemble Machine Learning Approaches. 9th Annual Rocky Mountain Bioinformatics Conference, Aspen, Colorado, 2011