I build and study interfaces for an age of generative abundance: tools that help people explore alternatives, notice consequential differences, explain tradeoffs, and build taste over time.
Cognitive Science Ph.D. student at UC San DiegoAdvised by Prof. Steven P. Dow in ProtoLab.
Scaffolding taste in an age of generative abundance.
Scaffolding for Taste asks a simple question: when AI can make ten plausible options in a minute, how do people learn to notice the difference that matters? I study interfaces that support reflective practice: making a move, seeing what changed, comparing alternatives, and building better reasons for choosing one direction over another.
I am testing this frame across creative tools, learning environments, mixed reality, everyday robotics, and community or civic design settings: places where tools can help people notice viable options, weigh tradeoffs, and choose the next move.
My work with Steven P. Dow and conversations with Don Norman and many others keep shaping how I think about taste and design judgment.
I keep testing the same loop: how to make alternatives comparable, let evidence sharpen the next question, and fit assistance to the situation where judgment happens.
Noon12:30 pm
DesignVary the alternatives, compare them, then refine.
Showing the Design motion sketch. Vary the alternatives, compare them, then refine.
Design lens
Human-AI for design thinking
I study interfaces that support design thinking beyond artifact generation: dimensional scaffolds that make the design space visible, variation mechanisms that expose alternatives, structured comparison that helps people reason across options, and staged fidelity that lets ideas mature from rough intent to defensible direction.
Externalize useful dimensions so people can see what matters.
02
Use variation and structured comparison to reason across alternatives.
03
Move from coarse ideas to committed artifact choices through staged fidelity.
Evaluate lens
Evaluation for design thinking
I evaluate AI tools with evidence between controlled psychology tasks and outcome-only benchmarks: process traces, artifact changes, rationales, preservation and explanation behavior, and learning probes that show what users carry beyond the interface.
Treat final artifact quality as one layer of evidence.
02
Connect traces and rationales to concrete design questions.
03
Measure explanation, preservation, revision, and transfer.
Situate lens
Interfaces fitted to context
I use situated work for settings where judgment depends on practice and medium: studio critique, mixed reality, everyday robotics, and civic or urban projects each change what help should do, when it should appear, and when it should stay out of the way.
Situations
01
Let practice shape what assistance should do.
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Match the interface to the medium and setting.
03
Make help fit the situation instead of interrupting it.
Exploring
Adjacent contexts for the same loop
These threads are places I test the same concern with judgment, agency, and evidence in context.
Situate Everyday roboticsIntegrating intelligence into robots so they can better assist people in everyday living and working contexts. Design Learner-centered AIScalable support that keeps agency and the learning process visible. Evaluate Post-deployment iterationUsing traces from real use to improve benefit and catch harm. Situate Community-centered toolsCoordination and sensemaking for groups with shared ownership.
Sirui Tao, Ivan Liang, Cindy Peng, Zhiqing Wang, Srishti Palani, and Steven P. Dow
In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, Apr 2025
DesignWeaver: Dimensional Scaffolding for Text-to-Image Product Design:When this paper helps.A blank prompt box is asking novices to supply design vocabulary they have not had a chance to learn.
This paper helps when a blank prompt box is asking novices to supply design vocabulary they have not had a chance to learn.
Look for
You are designing dimensional scaffolds for text-to-image exploration.
You want evidence about prompt language, visual diversity, novelty, and rising expectations.
It adds
A palette that externalizes product-design dimensions, grounded in expert practice and evaluated with 52 novice designers.
Its limit
The study used one chair-design task with novices, and richer prompts did not reliably improve satisfaction or expectation alignment.
I checked this against the paper and its official record on 2026-07-13.
@inproceedings{tao2024designweaver,title={DesignWeaver: Dimensional Scaffolding for Text-to-Image Product Design},author={Tao, Sirui and Liang, Ivan and Peng, Cindy and Wang, Zhiqing and Palani, Srishti and Dow, Steven P.},booktitle={Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems},series={CHI '25},pages={1--26},publisher={ACM},doi={10.1145/3706598.3714211},arxiv={2502.09867},month={apr},year={2025}}
Zimo Wang, Cheng Wang, Taiki Yoshino, Sirui Tao, Ziyang Fu, and Tzu-Mao Li
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2025
CVPR 2025 Highlight
HotSpot: Signed Distance Function Optimization with an Asymptotically Sufficient Condition:When this paper helps.An implicit-surface argument needs more than the usual eikonal condition—especially around convergence, stability, topology, or surface area.
This paper helps when an implicit-surface argument needs more than the usual eikonal condition—especially around convergence, stability, topology, or surface area.
Look for
You are comparing objectives for reconstructing signed distance functions from unoriented points.
You need theoretical and experimental evidence about a screened-Poisson alternative.
It adds
A heat-loss objective with convergence and stability analysis, plus 2D and 3D reconstruction evidence and a natural surface-area penalty.
Its limit
The reported gains belong to the evaluated reconstruction settings; sparse boundaries and parameter choices can still produce failure modes.
I checked this against the paper and its official record on 2026-07-13.
@inproceedings{wang2025hotspot,title={HotSpot: Signed Distance Function Optimization with an Asymptotically Sufficient Condition},author={Wang, Zimo and Wang, Cheng and Yoshino, Taiki and Tao, Sirui and Fu, Ziyang and Li, Tzu-Mao},booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},pages={1276--1286},publisher={IEEE},doi={10.1109/CVPR52734.2025.00127},arxiv={2411.14628},url={https://openaccess.thecvf.com/content/CVPR2025/html/Wang_HotSpot_Signed_Distance_Function_Optimization_with_an_Asymptotically_Sufficient_Condition_CVPR_2025_paper.html},note={Highlight},month={jun},year={2025}}
Daniel Bear, Elias Wang, Damian Mrowca, Felix Binder, Hsiao-Yu Tung, Pramod RT, Cameron Holdaway, Sirui Tao, Kevin Smith, Fan-Yun Sun, Fei-Fei Li, Nancy Kanwisher, Josh Tenenbaum, Dan Yamins, and Judith Fan
In Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks, Dec 2021
Physion: Evaluating Physical Prediction from Vision in Humans and Machines:When this paper helps.You need a reproducible benchmark for asking whether a model predicts physical outcomes in human-like ways.
This paper helps when you need a reproducible benchmark for asking whether a model predicts physical outcomes in human-like ways.
Look for
You are comparing object-centric and non-object-centric visual models with human judgments.
You need a common contact-prediction task across several simulated physical scenarios.
It adds
Eight scenario families, matched human and model evaluation, and released data and code for systematic comparison.
Its limit
Synthetic scenes and binary contact prediction do not establish broad real-world physical understanding.
I checked this against the paper and its official record on 2026-07-13.
@inproceedings{bear2021physion,title={Physion: Evaluating Physical Prediction from Vision in Humans and Machines},author={Bear, Daniel and Wang, Elias and Mrowca, Damian and Binder, Felix and Tung, Hsiao-Yu and RT, Pramod and Holdaway, Cameron and Tao, Sirui and Smith, Kevin and Sun, Fan-Yun and Li, Fei-Fei and Kanwisher, Nancy and Tenenbaum, Josh and Yamins, Dan and Fan, Judith},booktitle={Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks},editor={Vanschoren, J. and Yeung, S.},volume={1},arxiv={2106.08261},url={https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/hash/d09bf41544a3365a46c9077ebb5e35c3-Abstract-round1.html},month={dec},year={2021}}
Had a really fun time at the Design Lab retreat! Nadir shared The Last Gift and brought the documentary’s Emmy along, so I got to hold it and take a photo!
I like working with curious, motivated, and kind undergraduate and master's students, especially people who have a question they cannot stop poking at.
You do not need to show up as a polished researcher. It helps if you like reading carefully, making small prototypes, testing claims, looking honestly at evidence, and writing clearly about what changed.
The best fit is someone with real stake in a domain or problem, plus enough patience to turn that interest into a concrete study.
