[{
  "title": "About",
  "url": "/about/",
  "content": "About Eugene Kim (김유진) Physical Human-Robot Interaction (pHRI), Korea Institute of Industrial Technology (2016) B.S. Mechanical Engineering, Nagoya Institute of Industrial Technology (2018) M.S. Mechanical System Engineering, Nagoya University (2021) Ph.D Mechanical System Engineering, Nagoya University Grants (2016~2019) 일본 아이치현 / 차세대 로봇 사회 형성 기술 개발 프로젝트 / Aichi Next-Generation Robot Social Implementation Project for Human–Robot Collaborative Automation and Safety Technologies (2020~2025) 기획재정부(KITECH) / 융복합생산기술제조혁신연구개발 / 제품 제조현장 작업파트너 로봇 기술 개발 / KITECH Convergent Manufacturing Innovation R&D Program for Partner Robot Technology Development at Manufacturing Worksites (2020~2022) 중소벤처기업부 / 광주 무인 저속 특장차(모빌리티) 규제자유특구육성 사업화지원 / Gwangju Autonomous Low-Speed Special Vehicle Mobility Regulatory-Free Zone Commercialization Support Project (2021~2021) 중소벤처기업부 / 엣지형 공공정보 데이터 수집 공유 및 실증 / Edge-Based Public Data Collection, Sharing, and Demonstration Project for Autonomous Mobility and Remote Control Systems (2021~2024) 산업통상자원부 / 저속 특수목적 전기구동 차량(모빌리티)을 위한 부품 생태계강화 기반구축 / Infrastructure Development Program for Strengthening the Component Ecosystem of Low-Speed Electric Mobility Vehicles (2021~2022) 산업통상자원부 / 친환경 자동차부품 클러스터 조성 / Eco-Friendly Automotive Parts Cluster Development Project (2022~2022) 산업통상자원부 / 자율주행분야 데이터 표준 개발 및 실증체계 구축 / Autonomous Driving Data Standardization and Demonstration Framework Development Project (2022~2023) 중소벤처기업부 / 2차 광주특구(무인저속특장차/모빌리티) 안착화..."
},{
  "title": "News",
  "url": "/allnews.html",
  "content": "News\n\n\n\n\n\n2025, 8\nSucceded autonomous driving in Busan University of Foreign Studies\n\n\n\n\n"
},{
  "title": "Blog",
  "url": "/blogs/",
  "content": "Blog\n\n\n\n\nMay 31, 2024\nGreat Mathematicians and Physicists\n\n\n\nNov 28, 1961\nSpace-Time\n\n\n\n\n"
},{
  "title": "Home",
  "url": "/",
  "content": "Eugene Kim (김유진) Physical Human-Robot Interaction (pHRI), Korea Institute of Industrial Technology End-to-End Autonomous Driving Teleoperation & Delay Compensation Physical AI for Humanoid Robotics AI-Based Autonomous Manufacturing Digital Twin & Simulation Radar Sensing & Human–Robot Safety About research field Autonomous driving and intelligent robotics are interdisciplinary fields that focus on enabling machines to perceive, understand, and interact with complex real-world environments. These fields combine robotics, artificial intelligence, control engineering, computer vision, and machine learning to develop systems capable of making decisions and performing tasks autonomously. Research in autonomous systems plays an important role in the future of mobility and manufacturing, ranging from self-driving vehicles and teleoperation to humanoid robotics and AI-driven industrial automation. It helps us design safer and more adaptive systems that can collaborate with humans, respond to uncertain environments, and continuously improve through data and learning. My research particularly focuses on end-to-end autonomous driving, physical AI for humanoid robots, communication-delay-resilient teleoperation, and AI-based autonomous manufacturing systems. Through integrating real-time control, digital twins, reinforcement learning, and multimodal sensor fusion, I aim to develop intelligent robotic systems capable of operating reliably in both industrial and everyday environments. About me I am a researcher working in the fields of autonomous driving,..."
},{
  "title": "projects",
  "url": "/projects/",
  "content": "Project Manufacturing AI Transformation Demonstration Support Project Period: 2026 Funding Agency: KITECH / Ministry of Economy and Finance Project management and operational support program for manufacturing industry AI transformation demonstration projects. Physical AI for Humanoid Autonomous Manipulation Period: 2026–2027 Funding Agency: KITECH / Ministry of Economy and Finance Development of Physical AI and core technologies for humanoid autonomous manipulation and intelligent robotic work systems. AI-Based Autonomous Multi-Process Control System Period: 2025–2028 Funding Agency: KEIT / MOTIE Development of an AI-based autonomous multi-process control system for assembly of multi-variant vehicle lighting modules. AI-Based Active Driver Assistance System and Service Period: 2025–2027 Funding Agency: KEIT / MOTIE Development of AI-based active driver assistance systems and mobility services for transportation-disadvantaged users. KITECH Advanced Robotics and Manufacturing Capability Enhancement Period: 2025 Funding Agency: KITECH / Ministry of Economy and Finance Capability enhancement project for advanced robotics and manufacturing technologies at KITECH. Regional AI-Converged Workforce Training Program Period: 2025–2026 Funding Agency: Private Contract Research Development and operation of workforce education programs for regional AI-converged mobility and smart manufacturing industries. AI-Based Nuclear Decontamination Demonstration Platform Period: 2025–2026 Funding Agency: Private Contract Research Planning project for an AI-based high-power laser application platform for nuclear decontamination and decommissioning...."
},{
  "title": "Publications",
  "url": "/publications/",
  "content": "Publications Journal Articles Kim, D., Lim, T. Y., Kim, E., & Park, S. (2026). Impact of High Communication Latency on Teleoperated Driving Performance Independent of Driver Experience. IEEE Access. DOI BIB @article{kim2026impact, title = {Impact of High Communication Latency on Teleoperated Driving Performance Independent of Driver Experience}, author = {Kim, Donghyun and Lim, TaeYoon and Kim, Eugene and Park, Sungjun}, journal = {IEEE Access}, year = {2026}, doi = {https://doi.org/10.1109/ACCESS.2026.3689818}, file = {https://ieeexplore.ieee.org/iel8/6287639/6514899/11505852.pdf}, publisher = {IEEE} } 양수빈, 강환희, 김영곤, 김명진, & 김유진. (2026). 동관 브레이징 용접 위치 검출을 위한 멀티클래스 YOLO 모델과 클래스별 YOLO 결정 수준 모델의 성능 비교. 제어로봇시스템학회 논문지, 32(4), 475–481. PDF DOI BIB @article{양수빈2026동관, title = {동관 브레이징 용접 위치 검출을 위한 멀티클래스 YOLO 모델과 클래스별 YOLO 결정 수준 모델의 성능 비교}, author = {양수빈 and 강환희 and 김영곤 and 김명진 and 김유진}, journal = {제어로봇시스템학회 논문지}, volume = {32}, number = {4}, pages = {475--481}, doi = {10.5302/J.ICROS.2026.26.0005}, file = {ICROS2026_Yang.pdf}, year = {2026} } Talluri, T., Kim, E., Hwang, M.-H., Angani, A., & Cha, H.-R. (2026). Collision Avoidance with the Novel Advanced Shared Smooth Control in Teleoperated Mobile Robot Vehicles. Electronics, 15(7), 1510. DOI BIB @article{talluri2026collision, title = {Collision Avoidance with the Novel Advanced..."
},{
  "title": "Research",
  "url": "/research/",
  "content": "Research End-to-End Autonomous Driving Research on AI-driven autonomous driving systems capable of directly mapping multimodal sensor inputs to driving actions. This work focuses on robust perception, behavioral learning, real-time vehicle control, and scalable data-driven architectures for intelligent mobility systems operating in complex urban environments. Teleoperation & Communication Delay Compensation Development of safe teleoperation frameworks resilient to stochastic communication delays and network outliers. The research introduces asynchronous filtering, state estimation, and AI-based compensation strategies for remotely operated vehicles and robotic systems in real-world wireless communication environments. Physical AI for Humanoid Robotics Research on physical AI architectures enabling humanoid robots to autonomously interact with dynamic industrial and human-centered environments. This work integrates reinforcement learning, imitation learning, multimodal perception, and whole-body motion control for intelligent autonomous manipulation and collaborative robotics. AI-Based Autonomous Manufacturing Development of AI-driven autonomous manufacturing systems for industrial automation and adaptive process control. The research focuses on intelligent robotic assembly, quality prediction, anomaly detection using thermal vision, and real-time optimization of manufacturing workflows through machine learning and industrial AI. Digital Twin & Simulation Construction of digital twin environments for robotics and mobility systems to enable virtual validation, reinforcement learning, and predictive system analysis. This research combines real-time synchronization, physics-based simulation,..."
},{
  "title": "Talks",
  "url": "/talks/",
  "content": "## Talks\n\n\nInvited Talks\n\n{% bibliography --query @incollection[keywords ^= invited] %}\n\nRegular Talks\n\n{% bibliography --query @incollection[keywords != invited] %}\n\n"
},{
  "title": "Teaching",
  "url": "/teaching/",
  "content": "## Teaching\n\n\n\nPhysics 1, 2, 3: The Feynman Lectures on Physics (1961–63) Textbook here!\nPhysics 219: Quantum Computing (1986)\nGraduate QED Seminar (1953–88)\nPhysics X: Informal undergraduate Q&A sessions (1961–78)\n\n\n"
},{
  "title": "Team",
  "url": "/team/",
  "content": "## Team\n\n**We are looking for new team members!**\n\n## PI\n\n\n\n\n\n{{ site.name }}\n{{ site.title }}, {{ site.institution }}\n\n{% if site.email %}{% endif %}\n{% if site.links.google_scholar and site.links.google_scholar != \"\" %}{% endif %}\n{% if site.links.cv and site.links.cv != \"\" %}{% endif %}\n{% if site.links.github and site.links.github != \"\" %}{% endif %}\n{% if site.links.researchgate and site.links.researchgate != \"\" %}{% endif %}\n\n{% if site.data.pi[0].education %}\n\n{% for education in site.data.pi[0].education %}\n{{ education | replace: \"-\",\"–\" }}\n{% endfor %}\n\n{% endif %}\n\n\n\n\n{% if site.data.team_members.size > 0 %}\n## Current Students and Postdocs\n\n\n{% for member in site.data.team_members %}\n\n\n{{ member.name }}\n{{ member.info }}\n\n{% if member.email %}{% endif %}\n{% if member.website %}{% endif %}\n{% if member.scholar %}{% endif %}\n{% if member.github %}{% endif %}\n\n\n{% endfor %}\n\n{% endif %}\n\n{% if site.data.alumni.size > 0 %}\n## Alumni\n\n\n\n\nNameDurationCurrent Position\n\n\n{% for member in site.data.alumni %}\n\n{{ member.name }}\n{{ member.duration }}\n{{ member.info }}\n\n{% endfor %}\n\n\n\n{% endif %}\n"
}]