Byung Joo (BJ) Kim

▷ Responsible for safety feature development/ performance readiness considering the latest test protocols on safety regulations and consumer information ratings. ▷ Responsible for leading the high level automated driving feature roadmap, use case design and sensor configuration targets for Gen2 and Gen3 Autonomy platform. ▷ Responsible for autonomy sensor software development

The founder of Mando R&D Silicon Valley and a leader of ADAS projects in North America ▷ Lead local engineering tasks of ADAS (Radar/Camera) mass production projects (SOP: YR2021) ▷ Initiate partnership and R&D project with startups and tech companies ▷ Hands-on experience of building a test vehicle for ADAS and autonomous driving ● Major achievement: - Obtained a license for autonomous vehicle by California DMV. The first winning among Korean-based automotive industry companies - Won the ADAS (Level 2) mass production project in US region and led local application engineering activities for the development vehicle, model year 2021 - Led an advanced project for Rear-AEB (Autonomous Emergency Braking) system collaborating with an AI vision software company in the Silicon Valley - Led an engagement with a self-driving truck startup (‘TuSimple’ based in Arizona)

▷ Responsible for the entire ADAS mass production projects with Mando Radar (in-house model) and Camera (working with Mobileye) such as Adaptive Cruise Control, Autonomous Emergency Braking, Lane Keeping Assist and Highway Driving Assist etc. ※Fast revenue growth in Mando ADAS (Around +30% CAGR from 2017 to 2019) ▷ Focusing on enhancing each function performance and developing new features to the next level autonomy. Also, executing project task process in compliance with ISO26262. ● Major achievement: - Successfully developed and delivered production of HDA system (Highway Driving Assist, Level 2 Semi-autonomous Driving System) collaborating with Hyundai-Kia Motors (Deployed in Genesis brand EQ90, Model Year 2016) - Led the software development for AEB for junction turning & crossing and for cyclist target in order to increase the level of vehicle safety responding to an updated NCAP test protocol (Deployed in the Model Year 2019). - Established the next generation software architecture for the Level 3 autonomous driving platform utilizing multiple Radars & Cameras and Centralized Domain Compute Unit

Analyzing vehicle dynamic stability characteristics and designing a corresponding controller based on the motion prediction model. ● Major achievement: Granted US Patent, “Method and system for stability control,” US9120359B2, 2013

● Research interests include: Vehicle dynamics & control; Optimal control theory; Modeling and control of active safety functions in vehicle systems ● PhD Thesis: “Optimal Vehicle Motion Control to Mitigate Secondary Crashes after an Initial Impact” ● Awards: - Best Paper Award Winner, 2014 ASME Dynamic Systems and Control Conference (DSCC'14), “Optimal Vehicle Motion Control to Mitigate Secondary Crashes After an Initial Impact” - Best Paper Award Finalist, 11st International Symp. on Advanced Vehicle Control (AVEC'12) “Vehicle stability control of heading angle and lateral deviation to mitigate secondary collisions”