Summary
Jacob Goldverg is a software engineer and PhD candidate specializing in network throughput optimization, energy-efficient networking, and applied reinforcement learning for the networking stack. With eight years of experience, he designs and ships microservices and data transfer pipelines (Java/Python/Spring Boot) that maximize TCP throughput and reduce energy use, leveraging cloud platforms like AWS, Chameleon, FABRIC, and ACCESS. He has production experience building CI/CD, containerized deployments, and distributed databases (CockroachDB, InfluxDB) and has demonstrated practical energy savings at the edge by instrumenting devices and tuning system-level parameters. Currently at Apple and previously leading research and development at the University at Buffalo and in NSF-funded projects, he blends hands-on systems engineering with academic rigor. Notably, he’s optimized JVM performance across platforms from Raspberry Pi to 128+ core HPC servers, showing a rare combination of low-power edge work and large-scale systems tuning.
8 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University at Buffalo
English, Russian