Kevin De Angeli
About Kevin De Angeli
Kevin De Angeli is a Research Assistant at Oak Ridge National Laboratory, where he has worked since 2019. He holds a PhD in Data Science and Engineering from the University of Tennessee, Knoxville, and has experience in deep learning models for clinical text analysis.
Work at Oak Ridge National Laboratory
Kevin De Angeli has been employed as a Research Assistant at Oak Ridge National Laboratory since 2019. In this role, he focuses on applying deep learning techniques to clinical text analysis. His work contributes to advancements in extracting valuable information from unstructured clinical data, which is crucial for improving healthcare outcomes.
Previous Experience at Texas A&M University-Kingsville
Before joining Oak Ridge National Laboratory, Kevin De Angeli worked at Texas A&M University-Kingsville in various capacities. He served as a Programming Team Member from 2017 to 2018 and as a Math Tutor from 2018 to 2019. Additionally, he held the position of Grading Assistant from 2017 to 2018, where he supported the academic success of students.
Education and Expertise in Mathematics and Data Science
Kevin De Angeli earned a Bachelor of Science in Mathematics from Texas A&M University-Kingsville, completing his studies from 2017 to 2019. He further pursued his education at the University of Tennessee, Knoxville, where he obtained a Doctor of Philosophy in Data Science and Engineering from 2019 to 2023. He also holds an Associate of Science in Mathematics and Computer Science from Del Mar College, which he completed from 2014 to 2017.
Research Experience at NIMBioS
In 2018, Kevin De Angeli gained research experience as a Summer Undergraduate Researcher at the National Institute for Mathematical and Biological Synthesis (NIMBioS) in Knoxville, Tennessee. This position allowed him to engage in interdisciplinary research, further enhancing his skills in applying mathematical concepts to biological problems.
Deep Learning Applications in Clinical Text Analysis
Since 2019, Kevin De Angeli has been actively applying deep learning techniques in the field of clinical text analysis. His work involves developing models that extract information from unstructured clinical text, which is essential for improving data utilization in healthcare settings.