Name: Seth Wolfgang
Pronouns: he/him/his
Institution: Grand Valley State University
Department: School of Computing
Biography:
I am a computer science major and research assistant at Grand Valley State University. I wish to specialize in researching high performance computing, distributed systems, and numerical linear algebra. I have pre-published a paper introducing a sparse matrix compression library, as the co-first author, and am the first author of a recently published paper testing the feasibility of Raspberry Pis as edge servers in IoT projects. I am always eager to learn more, and often go above and beyond for my projects. I am passionate about becoming a scientist and have always been fascinated by space and computing. I grew up watching documentaries and reading books about both, and love to learn as much as I can. I still have a bit of that childish enthusiasm and curiosity that made me gravitate towards science when I was younger. In my free time, I enjoy playing video games, learning trivia about science, and spending time with my partner. We like to go to events, hike trails, and animal spotting in the woods. I am thrilled to continue my studies and research, and plan on making a positive impact on the world through my work.
Academic Status: Undergraduate Student
Year in program: 4th
Research Area/Department: Applied Mathematics; Computer Science; Machine Learning/AI
Other, specify:
Major/Specialty: I am a computer science major, and I am interested in numerical linear algebra and high performance computing.
Degrees Earned or in Progress: Bachelor’s computer science with a minor in mathematics (graduating in April 2024)
What courses or academic preparation have you completed to prepare for a summer internship experience?
I have taken the following courses in computer science: Computer Science 1 & 2, System level programming and utilities Data Structures and Algorithms Intro to Software Engineering Computer organization and assembly When I finish this academic year, I will have taken classes in: theory of computation HPC scientific computing data communication operating systems database Math course I’ve taken include: Discrete math 1 & 2 probability and statistics linear algebra 1 & 2 Calculus 1,2, and 3
Have you published any research or worked on research/technical projects? Yes
Where has your research been published or where have you conducted research/technical projects? I have published to IEEE International Conference on Electro Information Technology (eIT). This project focused on using Raspberry Pis as an edge server for a home cloud computing setup. We tested the feasibility using benchmarks that focused on taking large inputs and processing to small outputs. https://ieeexplore.ieee.org/document/10187384 I have also conducted work in sparse matrix compression methods for redundant data. Our initial application was for single cell/feature matrices, but similar forms of data can be compressed by our method. We created the IVSparse library which can compress redundant sparse matrix data down to a tenth of the size while keeping reasonable performance. https://arxiv.org/abs/2309.04355 My current project is in artificial genomic intelligence. There are many drugs that treat one illness, for example ADHD medication. Our primary goal is accurately predicting which drug will work best for a particular person, or predict health risks associated with a particular phenotype. The project is still in the beginning stages, but we are optimistic about the results.
Please describe your research/academic interests:
I am interested in many fields of research. I’ve worked on projects relating to machine learning, data compression, and distributed computing. Fields that I have not worked in, but would love the opportunity to, are scientific computing, high-performance computing, or more applied fields like bioinformatics and cosmology. Science offers many problems, and it difficult to pick and choose what we want to tackle. I am interested in most any field, but the listed ones are what spark my interest the most.
Computational and Data Science Areas:
Computational Science Applications, i.e., Bioscience, Cosmology, Chemistry, Environmental Science, Nanotechnology, Climate, etc.; Computer Science; High-Performance Computing; Machine Learning and AI
Research Synergy:
I am interested in machine learning, high-performance computing, and their applications because they each offer their own unique problems, and all equally revolutionary applications. Machine learning and high-performance computing are two powerful tools that have the potential to revolutionize many fields of science. In particular, I am interested in the ways that these two fields can be combined to create new and innovative applications. In particular, I am interested in machine learning because of its ability to make accurate predictions that can predict anything from health problems to creating images of black holes. There are many opportunities to tie fields like high-performance computing, cosmology, and even quantum computing. The applications are endless, and the labs are taking advantage. Like SmartTensors at Los Alamos which has scalable applications in many fields, or visualizing anomaly detection at Brookhaven, each presents their own important application. High-performance computing offers the ability to create the most complex, and important, simulations for galaxy collisions, weather models, and biology. I am interested in HPC because the the computing power required to fix or observe our biggest problems require the largest and most advanced machines. The DOE labs have a long history of exceptional work being done both in building high-performance machines, but also creating the software necessary to facilitate efficient use. The software and libraries created for these machines truly are works of art. Projects like ETHOS at Lawrence Livermore or the exascale systems being created at Oak Ridge bring new possibilities creating accurate simulations. DOE labs offer abundant resources, world-class expertise, and plenty of opportunities to each and every area. Each factor lends itself to a great work environment where any passionate scientist can flourish.
Motivation:
I am motivated to learn something new. Part of what drives me to research is no two projects are entirely the same, and I want to learn. National labs offer the resources and rigor that a university may not be able to offer. I am eager to challenge myself and learn from the best and brightest. Meeting my current mentors provided a similar push to bring me where I am today – to which I am very grateful to be closely mentored by truly gifted people. The hands-on work provided by research has taught me more than I could have imagined. SRP is a fantastic opportunity to have the extraordinary experience I’ve had being mentored while working at my dream job. I believe this program will provide me with the opportunity to gain valuable experience in these fields and to develop the skills I need to achieve my career goals of becoming a research scientist.
Lightning Talk Title: Developing Innovative High-Performance Computing Solutions to Accelerate Scientific Discovery