Hongyuan Mei

Mei, Hongyuan (梅洪源)

Email: hmei [at] cs [dot] jhu [dot] edu
Google Scholar, Github

Ph.D. Student in Computer Science
Johns Hopkins University

News

19-Mar-2021 Acknowledged as ICLR 2021 Outstanding Reviewer
19-Dec-2020 Acknowledged as EMNLP 2020 Outstanding Reviewer
26-Sep-2020 Noise-Contrastive Estimation accepted to NeurIPS 2020
15-Sep-2020 Acknowledged as ICML 2020 Top 33% Reviewer
09-Sep-2020 Named as the 2020 recipient of the Jelinek Fellowship
01-Jun-2020 Neural Datalog through time accepted to ICML 2020
21-Apr-2019 Neural Hawkes particle smoothing accepted to ICML 2019
22-Feb-2019 A paper on Chinese classifiers accepted to NAACL 2019
03-Jul-2018 Acknowledged as ACL 2018 Outstanding Reviewer
14-Jun-2018 Give a Deep Learning tutorial at 2018 JHU Summer School
21-May-2018 Awarded with Bloomberg Ph.D. Fellowship
09-Apr-2018 Halo accepted to *SEM 2018
21-Nov-2017 ACL-RepL4NLP-2018 Workshop accepted
04-Sep-2017 Neural Hawkes process accepted to NeurIPS 2017
24-Jan-2017 Give a talk at NIH about neural Hawkes process
29-Dec-2016 Neural Hawkes process paper posted on arXiv
11-Nov-2016 Coherent dialogue paper accepted to AAAI 2017
28-Aug-2016 Start graduate study at CLSP-JHU
12-May-2016 Will join CLSP-JHU as Ph.D. student in August
12-May-2016 Will start summer internship at MSR at end of May
02-Mar-2016 Selective generation paper accepted to NAACL 2016
11-Dec-2015 Thanks to NeurIPS 2015 MMML for NVIDIA GPU Award
12-Nov-2015 Neural navigation paper paper accepted to AAAI 2016
01-Mar-2015 Start visiting TTI-Chicago
      [About Me]      [Research & Publications]      [Teaching]      [Professional Service]      [Life Outside Lab]

About Me

I will join TTIC as a Research Assistant Professor in September 2021.

I am a Ph.D. student (2016-2021) in Department of Computer Science at Johns Hopkins University (JHU) and also a member of the Center for Language and Speech Processing (CLSP). I am fortunately advised by Jason Eisner and supported by Bloomberg Data Science Ph.D. Fellowship.

At JHU, I have collaborated with Yanxun Xu from Dept. AMS as well as Benjamin Van Durme and Kevin Duh from Dept. CS. Befor joining JHU-CLSP, I obtained a M.S. in Physical Science at The University of Chicago and did research in natural language understanding and generation with Mohit Bansal and Matthew R. Walter at Toyota Technological Institute at Chicago. Prior to that, I obtained a B.E. in Electrical Engineering from Huazhong University of Science and Technology (HUST).

Research & Publications

I believe that good research stems from curiosity. I admire the attitude of David Blackwell to research "I've worked in so many areas – I'm sort of a dilettante. Basically, I'm not interested in doing research and I never have been. I'm interested in understanding, which is quite a different thing. And often to understand something you have to work it out yourself because no one else has done it."

My research interests are rooted in designing models and algorithms to solve challenging real-life problems. My current focus is modelling irregular time series and my work has been covered by news articles on Fortune Magazine and Tech At Bloomberg. Here is a series of my papers on this topic:

I also develop statistical and machine learning methods for other domains such as medicine, natural language processing and computer vision:

Teaching

I believe that explaining is understanding. This philosophy is summarized from the Feynman story told by David Goldstein: "Feynman was a truly great teacher. He prided himself on being able to devise ways to explain even the most profound ideas to beginning students. Once, I said to him, "Dick, explain to me, so that I can understand it, why spin one-half particles obey Fermi-Dirac statistics." Sizing up his audience perfectly, Feynman said, "I'll prepare a freshman lecture on it." But he came back a few days later to say, "I couldn't do it. I couldn't reduce it to the freshman level. That means we don't really understand it."

Here is a list of courses that I have been involved in:

Professional Service

Life Outside Lab

When I am away from my workstation, I may be:



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