기술경쟁 시대의 전문가 인재 양성
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IT기술력을 갖춘 창의적이고 혁신적인 인재양성 유비쿼터스 시대를 앞당기기 위한 핵심기술, 이론 실무교육 실시 IT산업현장의 실무교육과 더불어 대학원 진학을 통한 미래 전문기술인 양성
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주요경력 |
Stanford University 공학박사(컴퓨터공학) |
담당과목 |
컴퓨터비전개론 |
연락처 |
02-944-5114 |
교수진소개 상세보기이며 학력, 경력, 주요연구실적, 담당교과목을 나타내는 표입니다.
학력 |
- Stanford University 공학박사 (컴퓨터공학 전공) - Stanford University 공학석사 (컴퓨터공학 전공) - University of Illinois at Urbana-Champaign 공학학사 (컴퓨터공학 전공, 수학 부전공) |
경력 |
- Meta 연구 인턴 - NVIDIA 연구 인턴 - 구글 맵 개발 인턴 - 구글 드라이브 개발 인턴 - 구글 클라우드 개발 인턴 - Skydio 자율주행 드론 AI 연구 인턴 - National Center for Supercomputing Applications 연구원 - 씨앤에이아이 AI개발팀 |
주요연구실적 |
*수상실적 - 2020 Human-Centered Artificial Intelligence AWS grant - Illinois Engineering Achievement Scholarship - Jeffrey P. Blahut Memorial Scholarship - Spin Research Fellowship - 1st place, ECE Pulse - Software - 3rd place, Midwest Facebook Hackathon
*특허 실적 - Systems and methods for semantic segmentation of 3D point clouds (US Patent 11004202)
* 논문 실적 - JRDB: A Dataset and Benchmark for Visual Perception for Navigation in Human Environments(IEEE transactions on pattern analysis and machine intelligence (PAMI),2021) - Jrmot: A real-time 3d multi-object tracker and a new large-scale dataset(IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS)],2020) - Generative sparse detection networks for 3d single-shot object detection(Computer Vision-ECCV2020: 16th European Conference,2020) - 3d scene graph: A structure for unified semantics, 3d space, and camera(Proceedings of the IEEE/CVF international conference on computer vision,2019) - 4d spatio-temporal convnets: Minkowski convolutional neural networks(Proceedings of the IEEE/CVF conference on computer vision and pattern recognition,2019) - Generalized intersection over union: A metric and a loss for bounding box regression(Proceedings of the IEEE/CVF conference on computer vision and pattern recognition,2019) - Deformnet: Free-form deformation network for 3d shape reconstruction from a single image(2018 IEEE Winter Conference on Applications ofComputer Vision (WACV),2018) - Segcloud: Semantic segmentation of 3d point clouds(2017 international conference on 3D vision (3DV),2017) - Weakly supervised 3D Reconstruction with Adversarial Constraint(3D Vision (3DV), 2017 Fifth International Conference on 3D Vision,2017) - Universal Correspondence Network(Advances in Neural Information Processing Systems 29 (NIPS 2016),2016) - 3d-r2n2: A unified approach for single and multi-view 3d object reconstruction(Computer Vision-ECCV2016: 14th European Conference,2016)
* 논문 심사 실적 - Reviewer of AAAI 2023 - Reviewer of CVPR, NeurIPS 2021 - Reviewer of AAAI, ICRA, CVPR, ECCV, NeurIPS 2020 - Reviewer of CVPR, ICCV, NeurIPS, IMAVIS, and two workshops 2019 - Reviewer of NeurIPS 2016 - Student volunteer at 3DV Conference and ONR workshop 2016 |
담당교과목 |
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상기 콘텐츠 담당부서 교무팀 (Tel : 02-944-5224)