Hey there! đź‘‹

Josh Minor

I’m Josh Minor, a software engineer at Arm based in the vibrant city of Austin, Texas. When I’m not optimizing ML workloads or debugging performance bottlenecks, you’ll find me on the tennis court working on my serve or exploring Austin’s incredible food scene (especially the Tex-Mex!).

What I Do

I’m currently focused on performance analysis of ML workloads on Arm hardware, developing better work scheduling strategies for running multiple ML models concurrently on the same Arm-based machine. This work sits at the intersection of hardware optimization, machine learning inference, and systems performance.

My expertise spans:

  • Edge Computing & ML: Performance optimization, inference acceleration, edge AI deployment
  • Embedded Systems: Hardware-software co-design, IoT devices, real-time systems
  • Machine Learning: Model deployment, inference optimization, concurrent workload scheduling
  • Systems Engineering: Performance analysis, resource management, scheduling algorithms
  • Cloud-Native Technologies: Containerization, orchestration, distributed systems

Research & Publications

I’ve contributed to several research projects in edge computing and machine learning:

Background

I graduated from the University of Texas at Austin (2014-2018) with University Honors, where I was active in IEEE and Tau Beta Pi honor societies. During my studies, I placed 3rd in the Embedded Systems Design Lab Competition and worked on projects ranging from embedded face tracking cameras to IoT applications.

Some notable projects from my academic work:

  • Embedded Face Tracking Camera - Real-time computer vision on resource-constrained hardware
  • HookedIn - Class scheduling application with smart optimization algorithms
  • Embedded Flappy Bird - Game development on microcontrollers

Life in Austin

Austin isn’t just where I work—it’s where I thrive. The city’s “Keep Austin Weird” motto resonates with my approach to both life and code. Whether it’s catching live music on Red River, biking around Town Lake, or discovering the latest food truck, Austin provides the perfect backdrop for creativity and innovation.

Tennis Enthusiast

Tennis is my escape from the digital world. There’s something therapeutic about the rhythm of the game, the strategy, and the physical challenge. Much like optimizing ML workloads, tennis requires precision, timing, and strategic thinking. I’m always up for a match if you’re in the Austin area!

Current Focus

Right now, I’m diving deep into the challenges of concurrent ML model execution on Arm processors. This involves:

  • Analyzing performance characteristics of different ML frameworks on Arm architecture
  • Developing intelligent scheduling algorithms for multi-model workloads
  • Optimizing resource utilization across CPU, GPU, and NPU components
  • Benchmarking and profiling ML inference pipelines

Let’s Connect

I love connecting with fellow researchers, engineers, tennis players, and anyone who shares a passion for technology, machine learning, or Austin. Feel free to reach out through any of the social links on my homepage.

When I’m not optimizing ML workloads or playing tennis, I’m probably planning my next research project, exploring a new Austin neighborhood, or perfecting my breakfast taco order while reading the latest papers on edge computing.