Erik Pautsch
Ph.D. Student
Erik Pautsch is a Ph.D. student in Computer Science at Loyola University Chicago and a Graduate Research Assistant working at the intersection of artificial intelligence, high-performance computing (HPC), and scalable software engineering. His research focuses on developing and evaluating computational methods for modern deep learning systems, with particular interests in uncertainty quantification, distributed machine learning, and emerging computing architectures.
Pautsch's research has included the development of uncertainty quantification methods for deep learning models, including Vision Transformers (ViTs), using distributed computing frameworks such as MPI for Python (mpi4py). His work has explored hyper-deep ensembles, binary evidential learning, and the effects of adversarial perturbations on AI models. He has also investigated the performance of emerging AI accelerators, including Cerebras and SambaNova systems, in comparison with traditional high-performance computing platforms.
Before joining his current research role at Loyola, Pautsch conducted research at Argonne National Laboratory, where he contributed to projects involving high-performance computing, heterogeneous architectures, and scientific software. His work included porting the marching cubes algorithm from CUDA to SYCL and contributing to educational materials for SYCL and HPC. He also co-authored a chapter for the UnoAPI book and co-developed and presented a tutorial on SYCL for high-performance computing at CARLA2024 in Santiago, Chile.
Pautsch is particularly interested in making advanced computing technologies more accessible through open-source software, educational resources, and practical applications. His work combines research and engineering, with an emphasis on translating sophisticated computational methods into scalable and usable solutions.
In addition to his academic work, Pautsch serves as an Intelligence Officer in the U.S. Navy Reserve. He previously served in the U.S. Navy and has experience in teaching, software development, wealth management, and technical research.
Major
Education
- Ph.D. in Computer Science, Loyola University Chicago — In Progres
- M.S. in Computer Science, Artificial Intelligence, Loyola University Chicago
- B.B.A. in Information Systems, Loyola University Chicago