Daniel Schultz
About Daniel Schultz
Daniel Schultz is an AI researcher currently serving as a PhD intern at Oak Ridge National Laboratory, where he specializes in data analytics, machine learning, and parallel algorithms. He holds a Master of Science in Computer Science from Eastern Washington University and is pursuing a Doctor of Philosophy at the University of Tennessee.
Work at Oak Ridge National Laboratory
Daniel Schultz has been working as an AI Researcher (PhD intern) at Oak Ridge National Laboratory since 2019. In this role, he engages in advanced research initiatives that leverage his expertise in data analytics, machine learning, and parallel algorithms. His contributions include working on projects that utilize technologies such as MPI, CUDA, and FFTW3, focusing on developing efficient algorithms for large-scale heterogeneous systems.
Education and Expertise
Daniel Schultz holds a Bachelor of Science (B.Sc.) in Computer Science from Eastern Washington University, which he completed from 2012 to 2015. He furthered his education with a Master of Science (MS) in Computer Science at the same institution from 2015 to 2017. Currently, he is pursuing a Doctor of Philosophy (PhD) in Computer Science at the Tickle College of Engineering at the University of Tennessee, which he has been studying since 2018. His academic background provides a strong foundation in data mining, machine learning, and parallel algorithms.
Background in Teaching and Research
Prior to his current role, Daniel Schultz served as a Graduate Teaching Assistant at Eastern Washington University from 2015 to 2017. In this position, he supported faculty in delivering course content and assisted students in understanding complex concepts in computer science. His experience in teaching complements his research work, where he has published findings as part of both independent and collaborative research initiatives.
Technical Skills and Proficiencies
Daniel Schultz possesses a diverse skill set in programming and systems development. He is proficient in multiple operating systems, including Linux, OSX, and Windows, and has command line and scripting capabilities. His programming expertise includes languages such as C, C++, Java, Python, and C# .NET. Additionally, he has experience with Amazon AWS cloud EC2 for data analytics, enhancing his ability to work with large datasets and complex computational tasks.
Contributions to Research Projects
Daniel Schultz has made significant contributions to various research projects, including the FFTECP project, where he focused on designing and implementing a fast and robust 2-D and 3-D FFT library for large-scale heterogeneous systems. His work in this area highlights his ability to apply theoretical knowledge to practical challenges in computational science, utilizing advanced technologies to improve performance and efficiency.