About
I'm a researcher at NVIDIA that develops algorithms that process and generate information in both speech and text modalities.
I used to work as an applied scientist in Amazon AWS AI Labs, where I spent two years working on products such as Amazon Translate, Amazon Q for Business, and Amazon Titan Text Embeddings. Prior to Amazon, I was a PhD student at Department of Computer Science, Johns Hopkins University. My PhD advisor was Philipp Koehn.
During my graduate studies, I was primarily affiliated with Center for Language and Speech Processing and also did research on neural machine translation. I had also spent a few memorable months either interning at Microsoft Translator, Salesforce Research, Amazon, or visiting The University of Edinburgh. Before joining Johns Hopkins, I got my Bachelor's degree in Beijing University of Posts & Telecommunications. During the last year of my undergraduate study, I worked with Weiwei Sun in the Language Computing and Web Mining Group of Institute of Computer Science & Technology, Peking University, with a focus on semantic parsing and Chinese word segmentation.
Publications
Fine-Tuned Machine Translation Metrics Struggle in Unseen Domains
Vilém Zouhar, Shuoyang Ding, Anna Currey, Tatyana Badeka, Jenyuan Wang, Brian Thompson
Annual Meeting of the Association for Computational Linguistics (ACL) 2024 (To Appear) [pdf]Doubly-Trained Adversarial Data Augmentation for Neural Machine Translation
Weiting Tan, Shuoyang Ding, Huda Khayrallah, Philipp Koehn
The 15th Conference of the Association for Machine Translation in the Americas (AMTA 2022) [pdf]Runtime Audit of Neural Sequence Models for NLP
Shuoyang Ding
PhD Thesis [pdf]The JHU-Microsoft Submission for WMT21 Quality Estimation Shared Task
Shuoyang Ding, Marcin Junczys-Dowmunt, Matt Post, Christian Federmann, Philipp Koehn
Sixth Conference on Machine Translation (WMT) 2021 [pdf][poster]Levenshtein Training for Word-level Quality Estimation
Shuoyang Ding, Marcin Junczys-Dowmunt, Matt Post, Philipp Koehn
EMNLP 2021 [pdf][code][slides][poster][talk]Evaluating Saliency Methods for Neural Language Models
Shuoyang Ding, Philipp Koehn
NAACL 2021 [pdf][code][slides][talk]Espresso: A Fast End-to-end Neural Speech Recognition Toolkit
Yiming Wang, Tongfei Chen, Hainan Xu, Shuoyang Ding, Hang Lv, Yiwen Shao, Nanyun Peng, Lei Xie, Shinji Watanabe, Sanjeev Khudanpur
ASRU 2019 [pdf][code]A Call for Prudent Choice of Subword Merge Operations in Neural Machine Translation
Shuoyang Ding, Adithya Renduchintala, Kevin Duh
MT Summit 2019 [pdf][code][poster]An Exploration of Masking for Neural Machine Translation
Matt Post, Shuoyang Ding, Marianna Martindale and Winston Wu
MT Summit 2019 [pdf]Saliency-driven Word Alignment Interpretation for Neural Machine Translation
Shuoyang Ding, Hainan Xu, Philipp Koehn
Fourth Conference on Machine Translation (WMT) 2019 [pdf][code][slides]Parallelizable Stack Long Short-Term Memory
Shuoyang Ding, Philipp Koehn
NAACL 2019 Workshop on Structured Prediction for NLP [pdf][bib][code][slides]Improving End-to-end Speech Recognition with Pronunciation-assisted Sub-word Modeling
Hainan Xu, Shuoyang Ding, Shinji Watanabe
ICASSP 2019 [pdf][bib][code]Multi-Modal Data Augmentation for End-to-end ASR
Adithya Renduchintala, Shuoyang Ding, Matthew Wiesner, Shinji Watanabe
Interspeech 2018 Best Student Paper Award (3/700+) [pdf][bib]The JHU Machine Translation Systems for WMT 2017
Shuoyang Ding, Huda Khayrallah, Philipp Koehn, Matt Post, Gaurav Kumar, and Kevin Duh
Second Conference on Machine Translation (WMT) 2017 [pdf][bib]The JHU Machine Translation Systems for WMT 2016
Shuoyang Ding, Kevin Duh, Huda Khayrallah, Philipp Koehn, and Matt Post
First Conference on Machine Translation (WMT) 2016 [pdf][bib]Grammatical Relations in Chinese: GB-Ground Extraction and Data-Driven Parsing
Weiwei Sun, Yantao Du, Xin Kou, Shuoyang Ding, Xiaojun Wan
Annual Meeting of the Association for Computational Linguistics (ACL) 2014 [pdf][bib]
Preprints
How Do Source-side Monolingual Word Embeddings Impact Neural Machine Translation?
Shuoyang Ding and Kevin Duh, 2018 [pdf]Backstitch: Counteracting Finite-sample Bias via Negative Steps
Yiming Wang, Hossein Hadian, Shuoyang Ding, Ke Li, Hainan Xu, Xiaohui Zhang, Daniel Povey, Sanjeev Khudanpur, 2017 [pdf]
Courses
- 600.465: Natural Language Processing
- 600.475: Machine Learning
- 600.468: Machine Translation
- 600.676: Machine Learning: Data to Models
- 050.620: Syntax I
- 600.615: Big Data, Small Languages, Scalable Systems
- 550.661: Nonlinear Optimization I
- 600.420: Parallel Programming
Teaching
- Nov 2021: Guest Lecture, EN.600.468/601.668 Machine Translation -- Analysis and Visualization
- Fall 2017: Graduate Teaching Assistant, EN.600.468/601.668 Machine Translation. Checkout the neural network and NMT homework I designed.
- Spring 2017: Guest Lecture, EN.600.435 Artificial Intelligence -- Markov Decision Process
- Spring 2016: Guest Lecture, EN.600.468 Machine Translation -- Syntax-Based Models