Scholar
Seokeon Choi
Google Scholar ID: wydV__gAAAAJ
Qualcomm AI research
Citations & Impact
Citations
2,954
H-index
14
i10-index
17
Publications
20
Co-authors
37
list available
Publications
Resume (English only)
Academic Achievements
- - Best Paper Award at ICCVW'25 LIMIT Workshop
- - Selected as Top Reviewer at NeurIPS'25
- - One paper accepted to NeurIPS'25
- - One paper accepted to ICCVW'25 (Oral)
- - Two papers accepted to ICCV'25
- - One paper accepted to NeurIPS'24
- - One paper accepted to ECCV'24
- - Promoted to Staff Research Engineer at Qualcomm
- - One paper accepted to CVPR'23
- - One paper accepted to CVPRW'23
- - One paper accepted to TPAMI'22
- - One paper accepted to ECCV'22
- - Two papers accepted to CVPR'21
- - One paper accepted to CVPRW'21
- - One paper accepted to ICCV'21
- - One paper accepted to CVPR'20
- - Two papers accepted to ECCVW'20
- - One paper accepted to CVPR'19
- - Two papers accepted to ECCVW'18
Research Experience
- - Qualcomm AI Research, Seoul, Korea
- - Staff Research Engineer (Nov. 2023 - present)
- - Senior Research Engineer (Sep. 2021 - Nov. 2023)
- - Google, Remote, Korea
- - Research Intern (Jun. 2021 - Sep. 2021)
- - Carnegie Mellon University, Pittsburgh, PA
- - Visiting Researcher (Jan. 2020 - Jul. 2020), under the guidance of Prof. Alex Hauptmann
- - KAIST, Daejeon, Korea
- - Research Assistant (Mar. 2015 - Jun. 2021)
Education
- - PhD in EE, KAIST, 2021, Advisor: Prof. Changick Kim
- - MS in EE, KAIST, 2017, Thesis: Robust Model-based Gait Recognition via Candidate Selection and Pose-aware Decision Fusion
- - BS in EEE, SKKU, 2015
Background
- Research interests: Computer vision and machine learning, focusing on generative AI and multimodality, transferability and generalizability, and computer vision applications (human understanding and machine perception). The goal is to bridge the gap between cutting-edge machine learning studies and real-world problems, providing practical solutions. Particularly dedicated to researching text-to-image/text-to-video diffusion models with a focus on personalization and efficient training/inference.
Miscellany
- Career Vision: With the rapid advancement of generative AI, the potential for groundbreaking innovation is limitless. My goal is to pioneer novel methodologies that will redefine the AI landscape, creating significant business impact in the process. Drawing on my diverse experience across multiple research domains, I am uniquely positioned as a generalist capable of applying cutting-edge research to a variety of challenges, ensuring a broader and more impactful contribution to the AI ecosystem.
