Hi, my name is
Drew Graham.
AI for HPC & Surrogate Modeling
I'm a computer science researcher specializing in AI-driven and agentic machine learning for high-performance computing. Currently working on AI-driven surrogate modeling at Los Alamos National Laboratory and pursuing my PhD at Clemson University.
Get In TouchAbout Me
My journey into programming began early—I started building websites when I was 10 years old. This led me into Minecraft modding and plugin development, where I learned to manage servers and eventually started doing development work for small companies through connections I made in the Minecraft community.
My formal interest in machine learning started during my undergraduate studies at Coastal Carolina University, where I began working on applied ML research through the LANL-CCU collaboration. The LANL-CCU Collaboration is an externally-funded research effort between the Department of Computing Sciences at CCU and the High Performance Computing Design group at Los Alamos National Laboratory (LANL) with a mission of solving specific national security challenges. This effort, led by Dr. William Jones, is also part of CCU's Gupta College of Science Vertically Integrated Projects (VIP) initiative.
I was fortunate to be the first student from our team to graduate from their new VIP program, working alongside both current and former undergraduate and graduate students from CCU and other affiliated universities, CCU faculty and staff, and several scientists at LANL. You can learn more about our team and my profile at the LANL-CCU collaboration page.
I specialize in developing machine learning solutions for scientific computing challenges, with a focus on surrogate modeling and spatio-temporal approaches. My research bridges the gap between cutting-edge AI techniques and real-world scientific applications in high-performance computing environments.
Currently, I'm a PhD student in Computer Engineering at Clemson University while continuing my research collaboration with Los Alamos National Laboratory. I've published papers at IEEE conferences and presented at multiple academic venues. Outside of research, I'm learning Spanish, enjoy playing video games, and continue working on side projects involving web development, gaming, and AI/ML experimentation.
In my free time, I maintain a home lab with server infrastructure, operate a 3D printer for various projects, and continue exploring new technologies that bridge my interests in software development and scientific computing.
Some technologies I work with:
- Python
- PyTorch
- TensorFlow
- CUDA
- OpenMPI
- SLURM
- Git
- Linux
- JavaScript
- React
- Node.js
- Docker
- GLSL
- C++
Where I've Worked
Student Researcher @ Los Alamos National Laboratory
May 2024 - August 2024 & Summer 2025
- Developed machine learning models for scientific surrogate modeling using spatio-temporal approaches
- Implemented data parallelism across multiple GPUs and compute nodes on supercomputing systems
- Applied SimVP-based models to complex scientific simulations, reducing computational overhead
- Collaborated with researchers on national security challenges through computational science
Undergraduate Researcher @ Coastal Carolina University
January 2023 - Present
- Conducted applied machine learning research through the LANL-CCU collaboration
- Completed four CSCI 399 independent study courses focused on ML applications
- Published research findings at IEEE conferences and academic symposiums
- Presented work at South Carolina Academy of Science and other venues
- First student to graduate from CCU's new Vertically Integrated Projects (VIP) program as part of the LANL-CCU collaboration
Data Developer @ Standard Financial
June 2022 - March 2023
- Developed data processing pipelines and analytics solutions
- Worked with large-scale financial datasets and reporting systems
- Implemented automated data workflows to improve operational efficiency
- Collaborated with cross-functional teams on data-driven projects
Full Stack Web Developer @ Verus Operations Ltd
March 2021 - March 2022
- Built responsive web applications using modern JavaScript frameworks
- Developed backend APIs and database architectures
- Implemented user authentication and security best practices
- Worked remotely with international team members across time zones
Leadership & Service
Young Americans for Liberty
Chapter Leader & Organizer
Led campus chapter activities at CCU focused on promoting liberty and constitutional principles, and continue similar involvement at Clemson University. Organized events, coordinated with national organization, and engaged students in civic discussions.
Mission Trips
Volunteer & Team Member
Participated in service missions to Honduras, providing community support, infrastructure assistance, and educational resources to underserved communities.
CSCI Peer Mentoring
Unofficial Student Mentor
Informally tutored and mentored incoming computer science students at CCU, providing academic guidance, research opportunities, and career advice to help them navigate their undergraduate experience.
Recognition & Awards
Clemson University PhD Assistantship
Competitive graduate research assistantship for Computer Engineering PhD program.
New Mexico Consortium "Student Highlight"
Featured student researcher highlighting work in machine learning and scientific computing applications.
Some Things I've Published
Applied Machine Learning for Surrogate Modeling: A Spatio-Temporal Approach
This paper explores the use of machine learning techniques as substitutes for direct numerical model simulation in scientific computing. We implemented spatio-temporal models to solve complex computational problems for Los Alamos National Laboratory.
- PyTorch
- CUDA
- HPC
- SimVP
- Scientific Computing
Incorporating Staggered Planned Maintenance Reservations to Improve Performance in Computational Clusters
Research on optimizing cluster maintenance scheduling to minimize downtime while maintaining system security and performance requirements in large-scale HPC environments.
- HPC Systems
- SLURM
- Cluster Computing
- Resource Management
Machine Learning for Surrogate Modeling of Scientific Codes: Practice and Experience
Poster presentation at the Conference on Data Analysis (CoDA 2025) showcasing practical applications of machine learning in scientific computing workflows and lessons learned from real-world deployments on the Venado supercomputer system.
- Machine Learning
- Scientific Computing
- Surrogate Modeling
- Data Analysis
In the News
LANL-CCU Graduate, Drew Graham, Starts PhD at Clemson University Fall 2025
From Undergraduate Researcher to Future Innovator: CCU's Drew Graham accepted into Clemson Ph.D. program with full funding under Dr. Jon Calhoun.
NMC Student Drew Graham Presents on Applied Machine Learning
Drew Graham gave a presentation on applied machine learning in his work with Los Alamos National Laboratory as part of the LANL-CCU Collaboration.
USRC Student Highlights at the New Mexico Consortium
The New Mexico Consortium highlights Drew Graham and Chris Stokes for their incredible work in machine learning and computer science, including CoDA 2025 presentations.
Jones and Graham AIML Talks
Dr. William Jones and Drew Graham gave talks on applied machine learning work with Los Alamos National Laboratory, with Drew focusing on surrogate modeling.
1000 Scientist AI Jam Session 2025
LANL-CCU team members including Drew Graham attended the DOE 1000 Scientist AI Jam Session hosted by OpenAI, Anthropic, and the US Department of Energy.
Supercomputing Conference 2024
Drew Graham presented "AIML For Science: Surrogate Modeling using SimVP" at the South Carolina Research Computing Consortium booth at SC24 in Atlanta.
ICMLA 2024
LANL-CCU Collaboration publishes "Applied Machine Learning for Surrogate Modeling: A Spatio-Temporal Approach" with Drew Graham presenting at IEEE ICMLA 2024 in Miami.
Drew Graham Presents at the 2024 HPC Intern Showcase
Drew Graham presented poster on summer research in applied machine learning at the 2024 LANL HPC Intern Showcase, forming foundation for ICMLA conference paper.
SCAS 2024
CCU students Drew Graham and Luke Beirne present their research work at the 2024 South Carolina Academy of Science conference.
Drew Invited LANL Internship 2023
LANL-CCU student collaborator Drew Graham invited to participate in in-person internship at LANL for summer 2024, exploring machine learning surrogate modeling.
LANL-CCU Students Celebrate Semester's End Spring 2023
The LANL-CCU Collaboration team members including Drew Graham celebrate the end of semester with past and present team members at Buffalo Wild Wings.
What's Next?
Get In Touch
I'm currently pursuing my PhD and always interested in discussing research opportunities, collaborations, or just connecting with fellow researchers in machine learning and HPC. Whether you have a question or just want to say hi, feel free to reach out!
Say Hello