Responsible AI Innovation (RAIN) Lab, pioneering responsible and trustworthy AI that nurtures society and sustains ecosystems, is led by Cheng-Yaw Low, Assistant Professor in the Department of AI Convergence Engineering at Changwon National University.

• Core Research Areas: Computer vision and generative models; multimodal data learning; remote-sensing and applications; computational science and data-driven modeling.

• Emerging Directions: Ecological AI for biodiversity conservation and environmental monitoring; geospatial AI for spatiotemporal modeling and Earth observation; maritime AI for maritime security using remote sensing and multimodal perception; responsible AI learning frameworks (FATE principles with robustness) for real-world deployment.

News

• Jan. 20–27, 2026: I will be attending the AAAI 2026 in Singapore. I look forward to connecting with researchers and AI practitioners. Please feel free to reach out at chengyawlow@changwon.ac.kr
• Sep. 01, 2025: Establishing Responsible AI Innovation Laboratory (RAIN Lab 책임 인공지능 혁신 연구실, EON관 301호)
• Sep. 01, 2025: Joining Deparment of AI Convergence Engineering, Changwon National University, South Korea, as an Assistant Professor.
• July 31, 2025: Our conference article has been accepted by the 2025 International Conference on Information Technology for Social Good, Antwerp, Belgium.
  • Paper Title: Open-Set Classification for Rare and Unknown Urban Tree Taxa
• July 4, 2025: Delivering a Guest Lecture on Responsible AI Ruhr University Bochum (RUB), Germany.
• Mar. 27, 2025: Awarded the Amazon Research Award (ARA) – Fall 2024 Cycle (Sustainability)
• Mar. 14, 2025: Our journal article has been accepted by the Information Fusion (SCIE, IF 14.8).
  • Paper Title: Second FRCSyn-onGoing: Winning Solutions and Post-Challenge Analysis to Improve Face Recognition with Synthetic Data
• Nov. 22, 2024: Joining the Max Planck Institute for Security and Privacy (MPI-SPI), Germany, starting February 2025.
• Sep. 23, 2024: Delivering an invited talk (special lecture series in AI) with Seoul National University of Science and Technology (SeoulTech), South Korea.
  • Talk Title: Ensuring Privacy and Fairness: Face Recognition in the Era of Synthetic Data
• Sep. 07, 2024: Securing a position as one of the winning teams in the Computer Vision for Ecology - Marine Species Classification Challenge, held in conjunction with the European Conference on Computer Vision (ECCV) 2024.
• June 25, 2024: Our journal article has been accepted by the IEEE TIFS (SCIE, IF 6.3).
  • Paper Title: Uncertainty-Aware Face Embedding with Contrastive Learning for Open-Set Evaluation
• June 18, 2024: Attending the CVPR 2024 for an oral presentation.
  • Paper Title: Face Recognition Challenge in the Era of Synthetic Data
• May 13, 2024: Delivering an invited talk (online) with Anhui University, China.
  • Talk Title: Ensuring Privacy and Fairness: Face Recognition in the Era of Synthetic Data
• May 02, 2024: Visiting the Max Planck Institute for Security and Privacy, Bochum, Germany.
  • Talk Title: Unlocking Fairness: Progressing Beyond Bias in Generative Models
• Apr. 29, 2024: Attending Machine Behavior Conference, Berlin, Germany.
• Apr. 11, 2024: Securing a position as one of the winning teams in the Face Recognition Challenge in the Era of Synthetic Data, held in conjunction with the IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) 2024.
• Feb. 01, 2024: Our journal article has been published in the IEEE TIFS (SCIE, IF 6.3).
  • Paper Title: Self-Attentive Contrastive Learning for Conditioned Periocular and Face Biometrics