Qing Zhang

Qing Zhang (张清/張清)

Dr. Qing Zhang is a Project Researcher at the Ishiguro Lab within the University of Tokyo’s Interfaculty Initiative in Information Studies, and a Visiting Researcher at the Augmented Vision Lab, Institute of Science Tokyo. He previously served as a Project Assistant Professor at the Rekimoto Lab, The University of Tokyo. Drawing on a background that bridges fine art and technology—an M.F.A. from the Tokyo University of the Arts and a Ph.D. in Media Design from Keio University—his research sits at the intersection of Human-Computer Interaction, wearable computing, and human-AI co-creation. He builds smart-eyewear systems that augment and modulate human visual perception (“programmable vision”), with applications spanning inclusive design for an aging society, eye-tracking and gaze interaction, skill acquisition, and 24/7 AI assistants that empower artists through Multimodal Large Language Models (MLLMs).

news

Jun 10, 2026	I will be presenting a paper at IJCAI 2026 in Bremen, Germany. https://2026.ijcai.org/accepted-papers/?ijtrack=special-track-on-human-centred-ai
Mar 19, 2026	“OpticalAging: Real-time Presbyopia Simulation for Inclusive Design via Tunable Lenses”, Best Paper Honorable Mention @ Augmented Humans 2026.
Sep 29, 2025	Two papers were accepted by NeurIPS’25 creative ai track.
Aug 21, 2025	A demo paper has been accepted by SIGGRAPH Asia Emerging Technologies.
Jul 21, 2025	One paper, “Beyond Symbols: Motion Perception Cues Enhance Dual-Task Performance with Wearable Directional Guidance”, has been accepted by Ubicomp/ISWC 2025.

selected publications

AHs’26 Paper
OpticalAging: Real-time Presbyopia Simulation for Inclusive Design via Tunable Lenses

Qing Zhang, Zixiong Su, Yoshihito Kondoh, and 5 more authors

In Proceedings of the Augmented Humans International Conference 2026, Okinawa, Japan, 2026

Abs DOI Bib

Presbyopia, a common age-related vision condition affecting most people as they age, often remains inadequately understood by those unaffected. To help bridge the gap between abstract accessibility knowledge and a more grounded appreciation of perceptual challenges, this study presents OpticalAging, an optical see-through simulation approach. Unlike VR-based methods, OpticalAging uses dynamically controlled tunable lenses to simulate the first-person visual perspective of presbyopia’s distance-dependent blur during real-world interaction, aiming to enhance awareness. While acknowledging critiques regarding simulation’s limitations in fully capturing lived experience, we position this tool as a complement to user-centered methods. Our user study (N = 19, 18-35 years old) provides validation: quantitative measurements show statistically significant changes in near points across three age modes (40s, 50s, 60s), while qualitative results suggest increases in self-reported understanding and awareness of perceptual challenges among participants. The integration of our tool into a design task showcases its potential applicability within age-inclusive design workflows when used critically alongside direct user engagement.
@inproceedings{10.1145/3795011.3795035, author = {Zhang, Qing and Su, Zixiong and Kondoh, Yoshihito and Asada, Kazunori and Starner, Thad and Kunze, Kai and Itoh, Yuta and Rekimoto, Jun}, title = {OpticalAging: Real-time Presbyopia Simulation for Inclusive Design via Tunable Lenses}, year = {2026}, isbn = {9798400723513}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3795011.3795035}, doi = {10.1145/3795011.3795035}, booktitle = {Proceedings of the Augmented Humans International Conference 2026}, pages = {101–114}, numpages = {14}, keywords = {Visual Simulation, Presbyopia, Visual Experience Modulation, Programmable Vision, Optical See-through, Accessibility, Inclusive Design, Aged Vision, Assistive Technology, Design Toolkit}, location = {Okinawa, Japan}, series = {AHs '26}, }
NeurIPS Creative AI
Semantic Glitch: Agency and Artistry in an Autonomous Pixel Cloud

Qing Zhang, Jing Huang, Mingyang Xu, and 1 more author

In The Thirty-ninth Annual Conference on Neural Information Processing Systems Creative AI Track: Humanity, 2025

Abs Bib PDF Video

While mainstream robotics pursues metric precision and flawless performance, this paper explores the creative potential of a deliberately "lo-fi" approach. We present the "Semantic Glitch," a soft flying robotic art installation whose physical form, a 3D pixel style cloud, is a "physical glitch" derived from digital archaeology. We detail a novel autonomous pipeline that rejects conventional sensors like LiDAR and SLAM, relying solely on the qualitative, semantic understanding of a Multimodal Large Language Model to navigate. By authoring a bio-inspired personality for the robot through a natural language prompt, we create a "narrative mind" that complements the "weak," historically, loaded body. Our analysis begins with a 13-minute autonomous flight log, and a follow-up study statistically validates the framework’s robustness for authoring quantifiably distinct personas. The combined analysis reveals emergent behaviors, from landmark-based navigation to a compelling "plan to execution" gap, and a character whose unpredictable, plausible behavior stems from a lack of precise proprioception. This demonstrates a lo-fi framework for creating imperfect companions whose success is measured in character over efficiency.
@inproceedings{zhang2025semantic, title = {Semantic Glitch: Agency and Artistry in an Autonomous Pixel Cloud}, author = {Zhang, Qing and Huang, Jing and Xu, Mingyang and Rekimoto, Jun}, booktitle = {The Thirty-ninth Annual Conference on Neural Information Processing Systems Creative AI Track: Humanity}, year = {2025}, url = {https://openreview.net/forum?id=oul9LWDi9S}, }

IJCAI

Beyond “Made with AI”: Visualizing Provenance Density to Mitigate the Transparency Penalty

Qing Zhang, Yifei Huang, Juyong Lee, and 2 more authors

In Proceedings of the 35th International Joint Conference on Artificial Intelligence (IJCAI), Special Track on Human-Centred AI, Aug 2026

To appear

Bib HTML

@inproceedings{zhang2026beyond,
  title = {Beyond ``Made with AI'': Visualizing Provenance Density to Mitigate the Transparency Penalty},
  author = {Zhang, Qing and Huang, Yifei and Lee, Juyong and Starner, Thad and Rekimoto, Jun},
  booktitle = {Proceedings of the 35th International Joint Conference on Artificial Intelligence (IJCAI), Special Track on Human-Centred AI},
  year = {2026},
  month = aug,
  address = {Bremen, Germany},
  note = {To appear},
  url = {https://2026.ijcai.org/accepted-papers/?ijtrack=special-track-on-human-centred-ai},
}