Lu Wang is an Assistant Professor of College of Computer and Information Science at Northeastern University since 2015. She is also affiliated with Northeastern NLP group and NULab for Texts, Maps, and Networks. She completed her Ph.D. in the Department of Computer Science at Cornell University, under supervision of Professor Claire Cardie in 2015.
Lu's research is focused on natural language processing, computational social science, and machine learning. More specifically, Lu works on algorithms for abstractive text summarization, language generation, argument mining, information extraction, and discourse analysis, as well as novel applications that apply such techniques to computational social science and other interdisciplinary subjects. Her work won outstanding short paper award at ACL 2017, and best paper nomination award at SIGDIAL 2012.
Lu's work has been mainly funded by National Science Foundation (NSF), Intelligence Advanced Research Projects Activity (IARPA), and several industry gifts (Tencent AI Lab, Toutiao AI Lab, NVIDIA GPU program, and Amazon Web Service credits).
Northeastern University, College of Computer and Information Science
Ph.D., Computer Science
Intelligence Science and Technology
My research aims at designing robust Natural Language Processing (NLP) models that can automatically understand and learn from large-scale texts of various domains and genres, and produce summaries of high quality. More specically, I endeavor building NLP systems to automatically generate high quality text summaries from disparate sources such as meeting dialogues, newswire services, and social media data, as well as to create novel applications based on text generation techniques.
The second research direction of my group is understanding social interaction via the lens of argument mining. In this direction, we focus on conversation understanding via content and social interaction modeling. We also design linguistic analysis and representation learning-based algorithms for automatic detection of salient arguments and their relations.
International Conference on Intelligent Virtual Agents (IVA) best paper nomination, 2017
Human robotics interaction (IVA'17)
Datasets for recent publications can be found at project pages (see corresponding publication entries) or Northeastern NLP group page.
- ACL (2018, 2017, 2015, 2014, 2013)
- NAACL 2015
- EMNLP (2018, 2017, 2016, 2015, 2014)
- ICML 2018
- NIPS 2018
- COLING 2016
- AISTATS 2017
- AAAI (2018, 2017, 2016)
- IJCAI 2016
- ICWSM (2018, 2017, 2014)
- WWW 2014
- Transactions of the Association for Computational Linguistics (TACL)
- Journal of Computational Linguistics (CL)
- Journal of Artificial Intelligence Research (JAIR)
- Communications of the ACM (CACM)
- Transactions on Information Systems (TOIS)
- Speech Communication
- IEEE Transactions on Knowledge and Data Engineering (TKDE)
- Transactions on Audio, Speech and Language Processing
I'm interested in doing research in natural language processing (NLP), where I design machine learning algorithms and computational models (e.g., neural networks, stochastic algorithms, probabilistic models, etc) for tasks on abstractive text summarization, language generation, argumentation mining, discourse analysis, and dialog analysis. I'm also interested in applying NLP and machine learning techniques for interdisciplinary subjects, e.g. computational social science. Specifically, there are four major ongoing research projects:
If any of these sounds interesting to you, please check out more about my research and papers at this website. My students and I are also part of Northeastern NLP group. If you find your research agenda might be aligned with mine and are interested in working with me, please fill in this external contact form and (for Ph.D. applicants) apply to College of Computer and Information Science (CCIS) at Northeastern University and mention my name in your application.
Please feel free to reach out using this external contact form . Prerequisites include being able to write code in some programming languages (e.g. Python, Java, C/C++) proficiently, and finishing courses in algorithms, multivariable calculus, probability, statistics, and linear algebra. It would be better that you have taken a course in natural language processing (CS4120/CS6120) or machine learning (CS4140/CS6140).