Xiang Zhang, Ph.D. Student
Computer Science Department
Courant Institute of Mathematical Sciences
New York University
xiang.zhang [a t] nyu.edu
Room 1231, 715 Broadway, New York, NY 10003

I am a third year Ph.D. student under the advisement of professor Yann LeCun with an interest in machine learning, including deep learning, numerical optimization, and some learning theory. Before being a Ph.D. student, I already spent 2 years as an M.S. student at NYU, during which time I participate in some research projects. Before coming to the U.S., I was an undergraduate student at the School of Computer Science and Technology, Tianjin University, conducting research in computational photography advised by professor Shiguang Liu.

If you need more information, my resume is available by email.


Refereed Publications

Google Scholar profile

Technical Reports


Blog Posts

    On the Emperor's New Mind

    Sun, Jul 12, 2015
    Finally finished reading Roger Penrose’s classic book “The Emperor’s New Mind: Concerning Computers, Minds and The Laws of Physics”. As a junior Ph.D. student who hopes to have a career in the research of artificial intelligence (machine learning or deep learning more precisely), I was reading this book as a touch on the opposite of the belief that intelligence is achievable by machines. Apart from several of his dramatic tones towards mocking A.I.

    One Precondition for Intelligence

    Tue, Apr 21, 2015
    Medical study shows that two consciousness could exist in the same body, if the connection between the left and the right brain hemispheres are damaged. Does this medical fact tells us something more about intelligence? My opinion is, it is an evidence for the hypothesis that certain deficiency in low-level communication is a precondition for intelligence. I know that sounds crazy or perhaps hard to understand, but please allow me to explain.

    Dataset Duplication Issues for Text Understanding from Scratch (Resolved)

    Tue, Apr 7, 2015
    Update June 8th 2015: The dataset duplication issues are fixed in the latest revision of our technical report. Some of our large-scale datasets became smaller than before, but the general conclusion in the technical report still holds. The information below is retained for your reference, although they are no longer valid. We are working on extending comparisons with stronger baseline models and releasing the datasets as soon as possible. Update April 9th 2015: In wake of dataset duplication issues for the Amazon reviews dataset, professor Julian McAuley updated their SNAP Amazon reviews dataset distribution webpage with an extra note and an extra data duplication file.

    On April Fool's: What is Wrong with RNN?

    Wed, Apr 1, 2015
    Google’s April fool surprise: reading characters in reverse order (https://com.google/). It happened to be the case that the character order in Crepe (https://github.com/zhangxiangxiao/Crepe) is also reversed. The original thought was that aligning the end of a document to a fixed position (in this case at the beginning) could make it easier for the fully-connected layers to associate meaning with the ending context window. This may have the effect of biasing classification towards the end reading of a text, which has a somewhat distant relationship with how recurrent neural network representation can be used for classification, since it decays the influence of document at the beginning but not so much at the end.

    The Landscape of Deep Learning

    Tue, Jan 27, 2015
    This blog summarizes an answer I posted to a question regarding what kinds of research are there for deep learning, in Zhihu, a Chinese equivalence of Quora. Surprisingly, that answer drew a lot of attention from many students and young researchers in China and it is currently ranked the second best answer in the subcategory of “deep learning”. I hope the summarization here could offer my bit of thought to a broader audience by translating that answer to English.