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Unleashing the Power of Data through Neurosymbolic Program Synthesis
Jocelyn (Qiaochu) Chen
IRB 4105 or https://umd.zoom.us/j/95853135696?pwd=VVEwMVpxeElXeEw0ckVlSWNOMVhXdz09
Monday, April 1, 2024, 11:00 am-12:00 pm
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Abstract

In today’s data-rich world, there is a growing need for tools that can help people extract, query, and utilize this data in an effective manner. This talk will focus on programming abstractions and synthesis algorithms that help people unleash the power of data by facilitating convenient data extraction and visualization. From a technical perspective, the talk will showcase synergies between programming languages tools (such as type systems and program analysis) and modern NLP techniques, and it will shed light on how this synergy enables a new science of neurosymbolic programming.

Bio

Jocelyn (Qiaochu) Chen is a PhD candidate at the University of Texas at Austin advised by Isil Dillig and Greg Durrett. She works at the intersection of programming languages and natural language processing. She aims to develop innovative techniques that combine the convenience and transparency of programming languages with the powerful capabilities of modern deep-learning techniques.

This talk is organized by Samuel Malede Zewdu