Hi! I'm Pengcheng. I am a research scientist at Google Deepmind, working on research and products (Bard, Colab) in natural language to code generation. Before that, I was a Ph.D. student at Language Technologies Institute, Carnegie Mellon University.

Outside of work, I am a student pilot based at Palo Alto Airport. I also train Coke using RLHF :)

News: I'm looking for interns at Google Deepmind for summer 2024 working on code LLMs. Please send me an email (pcyin@) if you are interested.

Research Papers

Please see my Google Scholar page for recent publications.

Past Industrial Experiences

• Researcher Intern, Microsoft Semantic Machines
• Part-time Research Collaborator, Facebook AI Research
• Research Intern, Facebook AI Research London
• Research Intern, Microsoft Research Cambridge, UK
• Research Intern, Microsoft Research
• Research Intern, Noah's Ark Lab, Huawei
• Research Intern, Microsoft Research Asia

Professional Services

• Area Chair: ICLR 2024
• Program Committee Member: ICLR 2019 Workshop on Deep Generative Models for Highly Structured Data, EMNLP 2020 Workshop on Iteractive and Executable Semantic Parsing, NeurIPS 2022/2023 workshop for table representation learning.
• Reviewer: ACL (outstanding reviewer @ ACL 2020), EMNLP, NAACL, NeurIPS, ICML (top 33% reviewer @ ICML '20), ICLR, etc.

Talks and Coding

• Recent talks in 2023: Stanford NLP seminar, Google NLP reading group, University of Wisconsin–Madison, etc.
• TranX: a general-purpose syntax-driven neural semantic parser
• Strong results on six semantic parsing benchmarks
• pytorch_basic_nmt: a basic implementation of attentional nerual seq2seq models
• Used for instructional purposes in Stanford CS224N Nautral Language Processing with Deep Learning and CMU 11-731 Machine Translation and Sequence-to-Sequence Models.