Jun Hu Email & Phone Number

Fremont, California, Us

𝐋𝐚𝐫𝐠𝐞-𝐒𝐜𝐚𝐥𝐞 𝐃𝐢𝐬𝐭𝐫𝐢𝐛𝐮𝐭𝐞𝐝 𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 & 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧-- Played a key role in design and implementing of simulation framework in 𝐂++ and 𝐏𝐲𝐭𝐡𝐨𝐧 for algorithm validation. Supported closed-loop validation (SIL & HIL), reducing development time by 50%.--Designed and implemented a scalable simulation infrastructure on 𝐀𝐖𝐒 using 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬, 𝐆𝐢𝐭𝐋𝐚𝐛 𝐂𝐈/𝐂𝐃, and 𝐀𝐫𝐠𝐨 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰, including cloud data management, test case generation, simulation triggers, metrics analytics, and automated reporting. Achieved 10,000+ concurrent simulations, cutting in-vehicle testing costs by 70%.--Implemented an end-to-end simulation pipeline (𝐏𝐲𝐭𝐡𝐨𝐧, 𝐆𝐢𝐭𝐋𝐚𝐛 𝐂𝐈/𝐂𝐃, 𝐀𝐖𝐒), automating code submission, compiling, regression testing, and reporting, reducing validation time by 80%.𝐖𝐨𝐫𝐥𝐝𝐒𝐢𝐦 𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐟𝐨𝐫 𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐄𝐧𝐠𝐢𝐧𝐞 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭--Developed static simulation agent behaviors in 𝐂++, focusing on traffic light logic.𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐓𝐨𝐨𝐥𝐜𝐡𝐚𝐢𝐧 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭--Led the IDL upgrade process, coordinating 8 teams and tracking milestones.--Designed and implemented auto-generation of IDL migrator in 𝐂++ and integrated it into 𝐃𝐨𝐜𝐤𝐞𝐫 pipelines using 𝐆𝐢𝐭𝐋𝐚𝐛 𝐂𝐈/𝐂𝐃 and JFrog, supporting 4+ micro-service.𝐄𝐧𝐝-𝐭𝐨-𝐄𝐧𝐝 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞 & 𝐌𝐨𝐝𝐞𝐥 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭--Designed and maintained ML pipelines to train and evaluate modules for accident scenario generation, reducing release time by 50%.--Automated critical ML lifecycle steps: data prep, training, tuning, packaging, versioning, deployment, monitoring, and reporting.--𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬: 𝐆𝐢𝐭𝐇𝐮𝐛 𝐀𝐜𝐭𝐢𝐨𝐧𝐬, 𝐌𝐋𝐟𝐥𝐨𝐰, 𝐀𝐫𝐠𝐨 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬, 𝐆𝐢𝐭𝐋𝐚𝐛 𝐂𝐈/𝐂𝐃, 𝐆𝐫𝐚𝐟𝐚𝐧𝐚, 𝐉𝐅𝐫𝐨𝐠, 𝐂𝐨𝐧𝐟𝐥𝐮𝐞𝐧𝐜𝐞, 𝐉𝐢𝐫𝐚 𝐀𝐏𝐈.

Veldhoven, Nl

𝐒𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐝𝐞𝐬𝐢𝐠𝐧 𝐚𝐧𝐝 𝐢𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐩𝐚𝐭𝐭𝐞𝐫𝐧 𝐦𝐚𝐭𝐜𝐡 𝐚𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦 𝐟𝐨𝐫 𝐥𝐚𝐫𝐠𝐞-𝐬𝐜𝐚𝐥𝐞, 𝐝𝐢𝐬𝐭𝐫𝐢𝐛𝐮𝐭𝐞𝐝 𝐬𝐲𝐬𝐭𝐞𝐦-- Key contributor to architecture design and implementation of DP(Distributed Processing) based pattern match algorithm using 𝐂++ for simulation software running on High Performance Computing cluster. Responsible for software architecture, implementation and maintenance. The high performance computation is based on 𝐌𝐚𝐩𝐑𝐞𝐝𝐮𝐜𝐞 𝐢𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞.--Led pattern library project for visualization tool development by following 𝐀𝐠𝐢𝐥𝐞 methodology with Jira. Collaborated with GUI team and implemented C-API engine on server side to fulfill front-endʼs Java RPC functionalities.-- Optimized runtime and memory performance by profiling and analyzing subroutine calls, reducing file I/O, and analyzing memory usage for High Performance Computing(HPC).-- Collaborated with over 25 engineers among multidisciplinary teams spanning backend software, testing, design, and operations, ensured over 20 releases with high quality for fast-paced customer facing product.-- Architected test bank frameworks by following Test Driven Development process, using 𝐌𝐲𝐒𝐐𝐋 and 𝐏𝐲𝐭𝐡𝐨𝐧 with continuous integration and code version control tools such as Jenkins -- Conducted new hire training, resource planning, code review, changelist risk evaluation, and post-release retrospective.

Washington, Dc, Us

𝐒𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐝𝐞𝐬𝐢𝐠𝐧 𝐚𝐧𝐝 𝐢𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 𝐮𝐬𝐢𝐧𝐠 𝐂++ 𝐟𝐨𝐫 𝐍𝐚𝐧𝐨𝐰𝐢𝐫𝐞 𝐬𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧-- Selected to work with top scientists at NASA on cutting-edge research project on nanowire based laser simulation.-- Collaborated with Stanford University and implemented a software using C++ and 𝐌𝐀𝐓𝐋𝐀𝐁 to simulate nanowire properties.

Doctoral, Electrical Engineering

B.S., Electrical Engineering