These are some of the things I've been working on in recent years.

I'm interested in how infants learn in everyday life — following gaze, sharing attention, speaking their first words. Much of what we know about babies has come from brief, artificial moments in the lab; I'm more curious about what we find when research walks into real homes, into an ordinary day.

Toward that, my colleagues and I have built open-source, lightweight, low-cost infant wearables and data tools, so that more labs — especially those studying communities often left out — can take part in developmental research.

这里放着我近年的一些研究工作。我关注婴儿如何在日常生活中学习——跟随目光、与人共同注意、说出最初的词语。过去我们对婴儿的认识，大多来自实验室里短暂而人为的片刻；我更好奇的是，当研究走进真实的家庭、走进平凡的一天，我们会看见什么。为此，我和同事们一起做了一些开源、轻便、低成本的婴儿可穿戴设备与数据处理工具，希望让更多实验室——尤其是资源有限、常被忽略的群体——也能参与到婴儿发展的研究里来。

My dissertation, Joint Attention in the Wild, examines how infants coordinate attention with caregivers in natural, at-home settings. Lately my focus has shifted toward methods and tools — an open-source infant wearable called OpenBabyographer and its machine-learning pipeline (speech transcription, face detection) — meant to lower the barrier so that naturalistic infant research can be reproduced, adapted, and extended.

我的博士论文 Joint Attention in the Wild（真实生活中的共同注意）探讨婴儿如何在自然的家庭情境里与照护者协调注意。近来，我把重心放在方法与工具上：一套名为 OpenBabyographer 的开源婴儿可穿戴设备，以及配套的机器学习流程（语音转写、人脸检测等），希望降低门槛，让自然情境下的婴儿研究能被更多人复现、修改、拓展。