基本信息
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个人简介
My research lies in the intersection of programming languages (PL) and machine learning (ML). Through a synthesis of ideas from PL and ML, I aim to help create a new generation of intelligent systems that are reliable, transparent, and secure, and can perform complex tasks that are beyond the scope of contemporary AI.
A recurring theme in my recent work is to represent learning-enabled systems as neurosymbolic programs that model high-level reasoning using PL primitives and lower-level pattern recognition using neural networks. The learning of such models is an instance of program synthesis, the problem of automatically discovering programs from user-provided specifications. We approach this problem using a combination of statistical ML techniques and language-directed, solver-driven algorithms from PL and formal methods.
Here are some of the concrete contexts in which my students, collaborators, and I are exploring these ideas.
A recurring theme in my recent work is to represent learning-enabled systems as neurosymbolic programs that model high-level reasoning using PL primitives and lower-level pattern recognition using neural networks. The learning of such models is an instance of program synthesis, the problem of automatically discovering programs from user-provided specifications. We approach this problem using a combination of statistical ML techniques and language-directed, solver-driven algorithms from PL and formal methods.
Here are some of the concrete contexts in which my students, collaborators, and I are exploring these ideas.
研究兴趣
论文共 131 篇作者统计合作学者相似作者
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CoRR (2024)
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ICLR 2024 (2024)
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Divyanshu Saxena, Nihal Sharma, Donghyun Kim, Rohit Dwivedula,Jiayi Chen, Chenxi Yang, Sriram Ravula, Zichao Hu,Aditya Akella, Sebastian Angel,Joydeep Biswas,Swarat Chaudhuri,
CoRR (2023)
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arXiv (Cornell University) (2023)
arxiv(2023)
CoRR (2023)
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