World Korean Scientists and Engineers Conference Award for Excellent Scientific and Engineering Paper / Professor Yoo Jin-woo (Department of Automotive IT Convergence)
- 25.08.05 / 이정민
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Professor Yoo Jin-woo (pictured) of the Department of Automotive IT Convergence at Kookmin University received the 35th Science and Technology Excellence Award (Engineering Category) at the 2025 World Korean Science and Technology Conference held at the Science and Technology Convention Center on the 10th.
The “Science and Technology Excellence Paper Award,” organized by the Korean Federation of Science and Technology Societies (KFST), is the highest academic award in the domestic science and technology community, presented to scientists and engineers who have published outstanding papers in domestic academic journals through creative research activities. This year's award received 402 nominations from Kofst academic society members for papers published last year. After a rigorous evaluation process conducted by five specialized committees and the Academic Promotion Committee, 245 papers were selected as finalists.
The paper for which Professor Yoo Jin-woo received the award is titled “A Methodology for Vehicle Path Prediction Using Deep Learning and Physics-Based Models,” published in The Transactions of the Korean Society of Automotive Engineers, a journal issued by the Korean Society of Automotive Engineers. This research is significant in that it creatively combines existing physics-based models and deep learning methods to improve the prediction performance of vehicle trajectories in the field of autonomous driving.
Professor Yoo is actively engaged in research related to autonomous driving at Kookmin University, particularly in areas such as real-vehicle and simulation-based autonomous driving performance verification, AI-applied perception/decision-making/control performance improvement, and end-to-end reinforcement learning. In particular, he has demonstrated outstanding capabilities in interdisciplinary research that integrates real vehicles, simulation, and AI to improve performance compared to existing methods in the field of autonomous driving. Based on this, he achieved the honor of winning the 35th Science and Technology Excellence Paper Award (Engineering Category) on July 10, 2025.
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World Korean Scientists and Engineers Conference Award for Excellent Scientific and Engineering Paper / Professor Yoo Jin-woo (Department of Automotive IT Convergence) |
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2025-08-05
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Professor Yoo Jin-woo (pictured) of the Department of Automotive IT Convergence at Kookmin University received the 35th Science and Technology Excellence Award (Engineering Category) at the 2025 World Korean Science and Technology Conference held at the Science and Technology Convention Center on the 10th.
The “Science and Technology Excellence Paper Award,” organized by the Korean Federation of Science and Technology Societies (KFST), is the highest academic award in the domestic science and technology community, presented to scientists and engineers who have published outstanding papers in domestic academic journals through creative research activities. This year's award received 402 nominations from Kofst academic society members for papers published last year. After a rigorous evaluation process conducted by five specialized committees and the Academic Promotion Committee, 245 papers were selected as finalists.
The paper for which Professor Yoo Jin-woo received the award is titled “A Methodology for Vehicle Path Prediction Using Deep Learning and Physics-Based Models,” published in The Transactions of the Korean Society of Automotive Engineers, a journal issued by the Korean Society of Automotive Engineers. This research is significant in that it creatively combines existing physics-based models and deep learning methods to improve the prediction performance of vehicle trajectories in the field of autonomous driving.
Professor Yoo is actively engaged in research related to autonomous driving at Kookmin University, particularly in areas such as real-vehicle and simulation-based autonomous driving performance verification, AI-applied perception/decision-making/control performance improvement, and end-to-end reinforcement learning. In particular, he has demonstrated outstanding capabilities in interdisciplinary research that integrates real vehicles, simulation, and AI to improve performance compared to existing methods in the field of autonomous driving. Based on this, he achieved the honor of winning the 35th Science and Technology Excellence Paper Award (Engineering Category) on July 10, 2025.
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