Robin Jia

E-mail: robinjia at stanford dot edu

I am a fourth-year Ph.D. student in Computer Science at Stanford University. My advisor is Percy Liang, and my current research focus is on natural language processing and machine learning. In the past, I have also worked on various projects in computational biology. I am supported by an NSF Graduate Research Fellowship.

Previously, I was an undergraduate at Stanford University, from which I received a B.S. with Honors in Computer Science and a Minor in Biology in June 2014.


Adversarial Examples for Evaluating Reading Comprehension Systems.
Robin Jia and Percy Liang.
Empirical Methods in Natural Language Processing (EMNLP), 2017.
Outstanding Paper Award.
(pdf) (bib) (codalab)

Learning Concepts through Conversations in Spoken Dialogue Systems.
Robin Jia, Larry Heck, Dilek Hakkani-Tür, and Georgi Nikolov.
International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2017.
(pdf) (bib) (data)

Data Recombination for Neural Semantic Parsing.
Robin Jia and Percy Liang.
Association for Computational Linguistics (ACL), 2016.
(pdf) (bib) (codalab)

"Reverse genomics" predicts function of human conserved noncoding elements.
Amir Marcovitz, Robin Jia, and Gill Bejerano.
Molecular Biology and Evolution, 2016.

Mx1 and Mx2 key antiviral proteins are surprisingly lost in toothed whales.
Benjamin A. Braun, Amir Marcovitz, J. Gray Camp, Robin Jia, and Gill Bejerano.
Proceedings of the National Academy of Sciences (PNAS), 2015.

Other Research



When I'm not coding, I spend a good amount of my time playing the piano. For a long time, I studied piano with with Angela Wright of Oak Park, Illinois. Since coming to Stanford in 2010, my teacher has been Laura Dahl.

Here are some of my recordings:

The next four recordings are from my Stanford senior recital on April 12, 2014. Some parts of this recital could have definitely gone better, but I'm also quite happy with many aspects of my performance. If you're going to listen to one thing here, I think the Debussy probably came out the best.