Alvin C. Grissom II
I am a computational linguist who does research at the intersection of computational linguistics and machine learning. Currently, my research focuses on machine learning approaches to incremental language processing and understanding the cognitive processes that enable humans to incrementally process language. Most of my recent work has focused on tackling the problem of machine learning-based simultaneous translation between distant language pairs and incremental verb prediction in verb-final languages, such as Japanese. I’m general, I’m enthusiastic about cross-disciplinary collaboration.
When possible, I make an effort to integrate my research into my courses and take advantage of our small classes to work with students to give them the opportunity to do cutting edge work. For example, students in my artificial intelligence class use state-of-the-art machine learning algorithms (e.g., deep learning and probabilistic models) to tackle real problems for their final projects. I encourage interested students who have time to ask me about contributing to one of my research projects.
Title
Department
Degrees
B.A., Hendrix College
M.S., Emory University
Ph.D., University of Colorado Boulder
Teaching
Spring 2019:
- CS-374 Principles of Programming Languages
- CS-371W Data Structures and Algorithms
- CS-174 Object-oriented Programming
Fall 2018:
- Deep Computer Vision and Language
- CS-373 Theory of Computation
Spring 2018:
- CS-174 Object-oriented Programming
- CS-474 Human-Computer Interaction
Fall 2017:
- CS-173 Introduction to Computer Science
- CS-477 Artificial Intelligence
Professional Experience
Research Interests
Much of my recent research has focused on machine learning-based approaches to incremental language processing with applications to simultaneous machine translation and computational psycholinguistics.
I am also interested in Japanese language processing, corpus linguistics, and modeling bias.
Since I’m at a liberal arts institution, I’m also interested in having conversations about how machine learning can be applied to other areas of inquiry.
Recent Work
Shi Feng, Eric Wallace, Alvin Grissom II, Mohit Iyyer, Pedro Rodriguez, and Jordan Boyd-Graber. Pathologies of Neural Models Make Interpretations Difficult. EMNLP 2018 (24%), Brussels, Belgium.
Yoshinari Fujinuma and Alvin C. Grissom II. Substring Frequency Features for Segmentation of Japanese Katakana Words with Unlabeled Corpora. IJCNLP 2017, Taipei, Taiwan. (31%)
Alvin C. Grissom II, Naho Orita, and Jordan Boyd-Graber. Incremental Prediction of Sentence-final Verbs. CoNLL 2016, Berlin, Germany. (20%) [Video]
He He, Alvin C. Grissom II, Jordan Boyd-Graber, and Hal Daumé III. Syntax-based Reordering for Simultaneous Machine Translation. EMNLP 2015, Lisbon, Protrugal. (24%) [Video] [Slides]
Alvin C. Grissom II, He He, Jordan Boyd-Graber, John Morgan, and Hal Daumé III. Don’t Until the Final Verb Wait: Reinforcement Learning for Simultaneous Machine Translation. EMNLP 2014., Doha, Qatar. (30%) [Video][Slides]