# Murray Kornelsen > ECE M.Sc Computer Engineering | Machine Learning Optimization Location: San Francisco Bay Area, United States Profile: https://flows.cv/murray Computer Engineer with experience in edge neural network optimization. Research focused on heterogeneous computing (ARM CPU+GPU) and quantization. Open source contributor to ARM Compute Library. Also experienced with common web technologies from personal projects and internships. Spring Boot, NodeJS, Browser HTML/CSS/JS. ## Work Experience ### Software Engineer (Android, Web, LLM Prompt Engineering) @ Forma Health Jan 2023 – Present | San Jose, California, United States Forma Health allows patients to connect with doctors in a clinical study, using AI to allow easy logging and analytics of patients' journey through the study. I delivered the following components: • Android App - Enables patients to collect and communicate specific information requested by a clinical study. • Physician Portal - Website for physicians to configure and view study data. • OpenAI LLM Processing - Developed system for LLM Prompt testing and optimization. ### ARM Compute Library Open Source Contributor @ McGill University Jan 2022 – Jan 2023 Developed multiple contributions to ARM Compute Library now included in production. • GELU Activation Function - Added new activation function in both OpenCL and NEON. This required implementation of erf (error function) using NEON intrinsics. • MeanStdDevNorm - Added int8 quantized implementation of normalization function. Added special case for F16 precision to avoid overflow issues. • CLSubTensor - Fixed/Optimized map operation which previously called clEnqueueMapBuffer unnecessarily. All changes were reviewed/optimized by myself and other ARMCL developers. https://review.mlplatform.org/q/owner:%2522murray.kornelsen%2540mail.mcgill.ca%2522 ### MSc Researcher - McGill Edge Intelligence Lab @ McGill University Jan 2020 – Jan 2023 | Montreal, Quebec, Canada Research: Optimizing neural networks, especially transformer models (BERT) on edge hardware through heterogeneous computing (CPU+GPU) and quantization. Thesis: Low-Latency BERT Inference for Heterogeneous Multi-Processor Edge Devices • Research focused on accelerating edge inference through heterogeneous computing. • Developed a genetic algorithm method for optimizing the assignment of neural network operations to CPU/GPU in edge SoC. Used HiKey970 development board for testing. • Combined heterogeneous computing with quantization. Developed an algorithm to optimize quantization configuration for pareto-optimal accuracy and latency. • Developed an ARM Compute Library implementation of BERT for latency measurements. ### Teaching Assistant @ McGill University Jan 2022 – Jan 2023 | Montreal, Quebec, Canada COMP 310 - Operating Systems (Winter 2022 & Winter 2023) • Presented tutorials on C Programming fundamentals: Introductory C Programming, Structs, Pthreads. • Answered questions about course material through Ed forums. ECSE 324 - Computer Organization (Winter 2022 & Winter 2023) • Ran labs focused on ARM (32-bit) assembly programming. • Answered student questions about ARM assembly. • Graded student demos at end of each lab. ### Software Engineering Intern @ Waterline Data Jan 2019 – Jan 2019 | San Francisco Bay Area Worked as part of the software engineering team on production code to resolve bugs and customer issues. Worked on both backend (Java) and frontend (Angular) issues. Wrote code to improve database analysis performance by taking advantage of database partitioning and parallelism. Researched and implemented for MySQL, Postgres, OracleDB, and MSSQL. ### Software QA Intern @ Numerify Jan 2018 – Jan 2018 | Cupertino, CA Worked on automation of end-to-end ETL testing. • Used Java with JUnit and REST Assured to build a test system. • Used Jenkins to automate the test job runs. • Learned about Angular and how to use Protractor to run tests on Angular pages. ### Programming Intern @ Dataguise Jan 2016 – Jan 2016 | Fremont, CA Worked on FileWalker, a Java program to traverse a Hadoop file system to discover homogeneous directories, including structure comparison. Worked on graphical displays for FileWalker output. Used HTML and Python to run FileWalker from a simple GUI and use graphs to present the data. ## Education ### Master of Science - MS in Computer Engineering McGill University ### Bachelor of Engineering - BE in Computer Engineering McGill University ## Contact & Social - LinkedIn: https://linkedin.com/in/murray-kornelsen --- Source: https://flows.cv/murray JSON Resume: https://flows.cv/murray/resume.json Last updated: 2026-03-29