Liam Seidel

B.S. Computer Science, Minor in Applied Mathematics at San Diego State University

About Me

Liam Seidel headshot

Hi! My name is Liam Seidel. I am a student at San Diego State University, majoring in Computer Science with a Minor in Applied Mathematics. I'm currently working as a Machine Learning Engineer Intern at Isola Group and conducting research on diffusion-based spatio-temporal generative models at SDSU Urban Computing. With experience in AI/ML, cloud development, and research, I'm passionate about applying cutting-edge technology to solve real-world problems. My commitment to continually challenging myself and embracing new skills makes me a dedicated and adaptable team member. Feel free to explore my experience, projects, and reach out with any questions or opportunities.

Experience

Machine Learning Engineer Intern

Isola Group July 2025 - Present
  • Developed a cloud-based customer inquiry automation system using Azure Functions, Power Automate, and Large Language Model APIs, improving scalability and removing manual triage.
  • Developed web pages supporting automated inquiry workflows and internal triage systems.

Technical Ambassador

July AI March 2025 - June 2025
  • Leveraged professional networks, delivered presentations to audiences of 500+, and worked closely with an AI-driven team with an emphasis on LLMs, Prompt Engineering, and Red Teaming.
  • Increased user base by over 20% in one month, and developed a reimplantable playbook for future ambassadors.

Research Assistant

SDSU Urban Computing September 2024 - Present
  • Conducted research under the supervision of Dr. Xin Zhang on diffusion-based spatio-temporal generative models (STGAIL) using PyTorch and GCNs to enhance urban traffic prediction.
  • Designed custom evaluation metrics and optimized encoder-decoder performance through GPU-accelerated training.

Instructor

Coding Minds April 2024 - July 2025
  • Instructed on Java, C++, Python languages, and topics like Web Development and Generative AI.

Projects

Brain Tumor Segmentation

Built a U-Net-based medical image segmentation pipeline using PyTorch and HuggingFace datasets, achieving high Dice coefficients in CT tumor detection.

Multi-threaded Delivery Service

Created a C++ multi-threaded delivery simulator implementing WSClock page replacement and multilevel page tables for virtual memory optimization.

AI Voice Clone

Designed and trained an RNN-based voice cloning model using spectrogram embeddings; integrated data preprocessing and post-processing pipelines, achieving ~85% MOS similarity score.

liamseidel.com

Built from scratch using HTML, CSS, and JavaScript.

Education

San Diego State University

B.S. in Computer Science, Minor in Applied Mathematics

GPA: 3.5

Skills

Languages

Python C++ Java C SQL

AI/ML Frameworks

PyTorch Tensorflow HuggingFace

Tools

Git MongoDB

Contact Me