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Prof. Minhee Jun Presents Trustworthy Physical AI Research at the 2026 NIST University Research Summit.
The 2026 NIST University Research Summit, hosted by the National Institute of Standards and Technology (NIST), brought together researchers, academic institutions, and technology leaders to explore emerging scientific challenges and opportunities for collaboration in advanced technology research.
At the Summit, Dr. Minhee Jun delivered a selected oral presentation titled “Toward Trustworthy Physical AI: Human Demonstrations, Task-Centric Digital Twins, and TEVV for Robot Learning.” The presentation introduced a research vision for using privacy-aware human task demonstrations and task-centric digital twins to support the efficient training, testing, evaluation, verification, and validation of Physical AI and robotic learning systems.
By combining human demonstration data, privacy-preserving technologies, simulation-ready digital twins, reproducible benchmarks, and systematic performance evaluation, the proposed framework seeks to advance the development of safer, more reliable, and more trustworthy Physical AI. The research also highlights opportunities for collaboration with NIST in digital twin technologies, evaluation science, benchmarking, and standards development.
SIGN - MAIL System Wins Global Recognition at the 2026 SAFE Image Challenge organized by the Digital Safety Research Institute (DSRI-UL).
The Image Edit Detection and Localization Challenge, organized by the Digital Safety Research Institute (DSRI), is a global research initiative focused on advancing technologies that can identify and analyze manipulated images. The challenge brings together researchers and innovators to develop systems capable of detecting whether an image has been altered, determining the type of manipulation used, and precisely locating where edits occur within the image.
By addressing emerging threats posed by AI-generated and subtly edited media, the challenge promotes the development of more robust image forensics tools that go beyond simple “real vs. fake” detection toward deeper understanding of how and where visual content is modified.
Through collaborative competition, benchmarking, and evaluation on novel datasets, the initiative helps drive innovation in digital safety, media authenticity, and trust in visual information across industries and society.
Prof Hanseok Ko - Director MAIL AI Lab gave a keynote speech in the 9th International Conference on Image and Graphics Processing (ICIGP) Wuhan, China (March 27-29, 2026).
Prof Hanseok Ko - Director MAIL AI Lab gave a keynote speech in the 9th International Conference on Image and Graphics Processing (ICIGP) Wuhan, China (March 27-29, 2026).
The International Conference on Image and Graphics Processing (ICIGP) is a global academic conference that brings together researchers, industry professionals, and scholars to share the latest innovations in image processing, computer vision, graphics, and related technologies. The conference provides a platform for presenting research, exchanging ideas, and building international collaborations across fields such as artificial intelligence, multimedia systems, human-computer interaction, and geospatial imaging. Through keynote talks, technical sessions, and peer-reviewed publications, ICIGP fosters knowledge advancement and real-world applications in rapidly evolving digital and visual computing domains.
Prof. Minhee Jun delivered a tech talk on “Edge-Intelligent AIoT Systems for Scalable and Privacy-Aware Applications” at an IEEE Computer Society Tech Talk held on March 27, 2026, at The Catholic University of America.
The IEEE Tech Talk on Edge-Intelligent AIoT Systems explores how the integration of Artificial Intelligence (AI) and the Internet of Things (IoT) is transforming modern digital systems into smarter, autonomous, and privacy-aware solutions. The session highlights how AIoT enables devices not only to collect data but also to analyze, learn, and make real-time decisions across various applications.
Focusing on real-world use cases such as healthcare, smart homes, agriculture, transportation, and smart cities, the talk demonstrates how AI-powered IoT systems improve efficiency, enable predictive insights, and support intelligent monitoring and automation.
A key theme of the presentation is the shift toward edge intelligence, where data is processed closer to the source rather than relying solely on cloud systems. This approach enhances real-time responsiveness, scalability, and data privacy, making AIoT systems more effective for time-sensitive and secure applications.
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