Ziwei Gu

Hi, I'm Ziwei.

I am a first-year Ph.D. student in Computer Science at Harvard University, advised by Professor Elena Glassman. My research interests lie at the intersection of human-computer interaction and machine learning/ natural language processing.

Before coming to Harvard, I graduated with a bachelors in Mathematics and Computer Science (December 2020) and masters in Computer Science (May 2021) from Cornell University.

Interaction logs can be extremely complex yet useful. Breaking down event logs into goal-directed segments can make it easier to understand user workflow.

We ask a fundamental research question: How do core design elements of debiasing systems shape how people reason about biases? We present distinctive sensemaking patterns and surprising findings from think-aloud studies.

We present Silva, an interactive tool that utilizes a causal graph linked with quantitative metrics to help people find and reason about sources of biases in datasets and machine learning models.

We trained a deep learning model (Transformer) for open information extraction, modeled as a sequence to sequence transduction task. We showed that our model was competitive with state-of-the-art systems, but without the dependencies on other NLP tools.

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