Hello. I am an incoming Ph.D. student in the ML² Group (subset of the CILVR Group) of the Courant Institute of Mathematical Sciences of New York University. I will be advised by Prof. He He and Prof. Kyunghyun Cho.
My research focuses on natural langauge processing and machine learning. Specifically, I have been working on structured prediction algorithms, generation, and neural machine translation.
I graduated from the University of Chicago in June 2019, and I majored in mathematics and computer science. In Chicago, my advisor has been Prof. Kevin Gimpel at Toyota Technological Institute at Chicago (TTIC) and the University of Chicago. Check out the TTIC Speech and Language Group.
Research (not up-to-date)
Learning Criteria and Evaluation Metrics for Textual Transfer
between Non-Parallel Corpora
Yuanzhe Pang, Kevin Gimpel
[paper] [supplementals] [abstract] [BibTeX]
My second (completed) research project is on approximate inference for structured prediction. To learn more, please email me for detailed CV.
Presentation
Poster presentation on Learning Criteria and Evaluation Metrics for Textual Transfer between Non-Parallel Corpora (nonarchival); NAACL 2019 NeuralGen workshop in Minneapolis, USA; June 2019
Talk titled Learning Approximate Inference Networks and Structured Prediction Energy Networks with Lifu Tu and Kevin Gimpel; Midwest Speech and Language Days (MSLD) 2019 in Chicago, USA; May 2019
Poster presentation on Learning Criteria and Evaluation Metrics for Textual Transfer between Non-Parallel Corpora; UChicago STEM Research Symposium in Chicago, USA; October 2018
Teaching
Spring 2017, Course Assistant, MATH 15910: Intro to Proofs in Analysis
Winter 2017, Course Assistant, MATH 15910: Intro to Proofs in Analysis [Sol]
Winter 2017, Grader, CMSC 15200: Intro to Computer Science II
Autumn 2016, Teaching Assistant, MATH 15300: Calculus III
Relevant Coursework
UChicago (2015-2019)
CMSC 27230 - Honors Theory of Algorithms
CMSC 25025 / STAT 37601 - Machine Learning and Large-Scale Data Analysis (grad level, Lafferty)
CMSC 35400 / STAT 37710 - Machine Learning (grad level, Kondor)
TTIC 31020 - Statistical Machine Learning (grad level, Shakhnarovich)
TTIC 31190 - Natural Language Processing (grad level, Gimpel)
TTIC 41000 - Spectral Techniques (grad level, Stratos)
MATH 20300-20400 - Accelerated Real Analysis I, II, III
MATH 20250, 25400-25500 - Abstract Linear Algebra; Abstract Algebra I, II
BIOS 10602-10603 - Multiscale Modeling of Biological Systems I, II (computational biology)
Last updated in July 2019. More materials coming soon. Get in touch at yzpang at _ dot edu (where _ is uchicago or nyu)!