Award listed
Original award wording
Overall 2
Project profile
Sim Francisco
Sim Francisco creates synthetic city residents from demographic data. A likely audience is researchers and product decision-makers exploring possible population reactions; this is an inference from the current README.
The README describes submitting a question or event, generating reactions from resident profiles, and aggregating responses with population weights. Map-based daily-life simulation and the prediction engine are distinct. Outputs include group opinions, votes or probability estimates, and a visual city.
The implementation description mentions Census ACS PUMS microdata, resident weights, batched profile groups, and SQLite caching. Claimed historical prediction and cost improvements were not reproduced. The current README is inconsistent about model selection, and later implementation details do not establish competition-time capabilities. Simulated reactions cannot replace a real survey; no app or API test was performed.
Creator or team (original public names)
Tanmayi Priya Dasari、Tejas Prabhune（官方结果署名）
Links & sources
Links may have changed since we checked them. Descriptions from creators have not been independently tested.
Details in the original language
Original title
Sim Francisco
Original creator credit
Tanmayi Priya Dasari、Tejas Prabhune（官方结果署名）
作品是什么
Sim Francisco 以人口数据建立合成城市居民。
给谁用
希望探索人群反应的研究者和产品决策者；依据当前 README 场景归纳。
问题或体验
在真实发布或决策前获得人群反应线索；模拟结果不能替代真实调查。
如何使用
当前 README 称输入问题或事件，按居民画像生成反应，再用人口权重聚合；地图上的生活模拟与预测引擎分开。
得到什么
群体意见、投票或概率估计及可视化城市；效果未独立复现。
关键机制
当前 README 描述 Census ACS PUMS 微数据、居民权重、画像分群批处理与 SQLite 缓存，以减少逐人模型调用。
特点
把地图居民展示与人口加权问答组合；依据公开实现描述归纳。
Events & award announcements
Read original announcement
Result listed — see original announcement
Original award wording
Finalists
Sources last checked: 2026-10-10