Michael Collins (computational linguist)

Last updated

Michael J. Collins
Born (1970-03-04) 4 March 1970 (age 54)
Flag of the United Kingdom.svg London
CitizenshipUK
Alma mater Cambridge University
University of Pennsylvania
Known forStatistical parsing, Structured perceptron
Scientific career
Fields Computational linguistics, Machine learning
Institutions Columbia University
Doctoral advisor Mitch Marcus

Michael J. Collins (born 4 March 1970) is a researcher in the field of computational linguistics. He is the Vikram S. Pandit Professor of Computer Science at Columbia University. [1]

His research interests are in natural language processing as well as machine learning and he has made important contributions in statistical parsing and in statistical machine learning. In his studies Collins covers a wide range of topics such as parse re-ranking, tree kernels, semi-supervised learning, machine translation and exponentiated gradient algorithms with a general focus on discriminative models and structured prediction. One notable contribution is a state-of-the-art parser for the Penn Wall Street Journal corpus. As of 11 November 2015, his works have been cited 16,020 times, and he has an h-index of 47. [2]

Collins worked as a researcher at AT&T Labs between January 1999 and November 2002, and later held the positions of assistant and associate professor at M.I.T. Since January 2011, he has been a professor at Columbia University. [3] In 2011, he was named a fellow of the Association for Computational Linguistics. [4]

Related Research Articles

Computational linguistics is an interdisciplinary field concerned with the computational modelling of natural language, as well as the study of appropriate computational approaches to linguistic questions. In general, computational linguistics draws upon linguistics, computer science, artificial intelligence, mathematics, logic, philosophy, cognitive science, cognitive psychology, psycholinguistics, anthropology and neuroscience, among others.

Natural language processing (NLP) is an interdisciplinary subfield of computer science and information retrieval. It is primarily concerned with giving computers the ability to support and manipulate human language. It involves processing natural language datasets, such as text corpora or speech corpora, using either rule-based or probabilistic machine learning approaches. The goal is a computer capable of "understanding" the contents of documents, including the contextual nuances of the language within them. To this end, natural language processing often borrows ideas from theoretical linguistics. The technology can then accurately extract information and insights contained in the documents as well as categorize and organize the documents themselves.

Corpus linguistics is an empirical method for the study of language by way of a text corpus. Corpora are balanced, often stratified collections of authentic, "real world", text of speech or writing that aim to represent a given linguistic variety. Today, corpora are generally machine-readable data collections.

The American National Corpus (ANC) is a text corpus of American English containing 22 million words of written and spoken data produced since 1990. Currently, the ANC includes a range of genres, including emerging genres such as email, tweets, and web data that are not included in earlier corpora such as the British National Corpus. It is annotated for part of speech and lemma, shallow parse, and named entities.

<span class="mw-page-title-main">Treebank</span>

In linguistics, a treebank is a parsed text corpus that annotates syntactic or semantic sentence structure. The construction of parsed corpora in the early 1990s revolutionized computational linguistics, which benefitted from large-scale empirical data.

Martin Kay was a computer scientist, known especially for his work in computational linguistics.

Eugene Charniak was a professor of computer Science and cognitive Science at Brown University. He held an A.B. in Physics from the University of Chicago and a Ph.D. from M.I.T. in Computer Science. His research was in the area of language understanding or technologies which relate to it, such as knowledge representation, reasoning under uncertainty, and learning. Since the early 1990s he was interested in statistical techniques for language understanding. His research in this area included work in the subareas of part-of-speech tagging, probabilistic context-free grammar induction, and, more recently, syntactic disambiguation through word statistics, efficient syntactic parsing, and lexical resource acquisition through statistical means.

James Frederick Allen is an American computational linguist recognized for his contributions to temporal logic, in particular Allen's interval algebra. He is interested in knowledge representation, commonsense reasoning, and natural language understanding, believing that "deep language understanding can only currently be achieved by significant hand-engineering of semantically-rich formalisms coupled with statistical preferences". He is the John H. Dessaurer Professor of Computer Science at the University of Rochester

In natural language processing, semantic role labeling is the process that assigns labels to words or phrases in a sentence that indicates their semantic role in the sentence, such as that of an agent, goal, or result.

Jun'ichi Tsujii is a Japanese computer scientist specializing in natural language processing and text mining, particularly in the field of biology and bioinformatics.

Dragomir R. Radev was an American computer scientist who was a professor at Yale University, working on natural language processing and information retrieval. He also served as a University of Michigan computer science professor and Columbia University computer science adjunct professor, as well as a Member of the Advisory Board of Lawyaw.

Deep Linguistic Processing with HPSG - INitiative (DELPH-IN) is a collaboration where computational linguists worldwide develop natural language processing tools for deep linguistic processing of human language. The goal of DELPH-IN is to combine linguistic and statistical processing methods in order to computationally understand the meaning of texts and utterances.

Michael Justin Kearns is an American computer scientist, professor and National Center Chair at the University of Pennsylvania, the founding director of Penn's Singh Program in Networked & Social Systems Engineering (NETS), the founding director of Warren Center for Network and Data Sciences, and also holds secondary appointments in Penn's Wharton School and department of Economics. He is a leading researcher in computational learning theory and algorithmic game theory, and interested in machine learning, artificial intelligence, computational finance, algorithmic trading, computational social science and social networks. He previously led the Advisory and Research function in Morgan Stanley's Artificial Intelligence Center of Excellence team, and is currently an Amazon Scholar within Amazon Web Services.

Marilyn A. Walker is an American computer scientist. She is professor of computer science and head of the Natural Language and Dialogue Systems Lab at the University of California, Santa Cruz (UCSC). Her research includes work on computational models of dialogue interaction and conversational agents, analysis of affect, sarcasm and other social phenomena in social media dialogue, acquiring causal knowledge from text, conversational summarization, interactive story and narrative generation, and statistical methods for training the dialogue manager and the language generation engine for dialogue systems.

<span class="mw-page-title-main">Dan Roth</span> Professor of Computer Science at University of Pennsylvania

Dan Roth is the Eduardo D. Glandt Distinguished Professor of Computer and Information Science at the University of Pennsylvania.

<span class="mw-page-title-main">Pascale Fung</span> Professor

Pascale Fung (馮雁) is a professor in the Department of Electronic & Computer Engineering and the Department of Computer Science & Engineering at the Hong Kong University of Science & Technology(HKUST). She is the director of the Centre for AI Research (CAiRE) at HKUST. She is an elected Fellow of the Institute of Electrical and Electronics Engineers (IEEE) for her “contributions to human-machine interactions”, an elected Fellow of the International Speech Communication Association for “fundamental contributions to the interdisciplinary area of spoken language human-machine interactions” and an elected Fellow of the Association for Computational Linguistics (ACL) for her “significant contributions toward statistical NLP, comparable corpora, and building intelligent systems that can understand and empathize with humans”.

<span class="mw-page-title-main">Iryna Gurevych</span> German computer scientist

Iryna Gurevych, member Leopoldina, is a Ukrainian computer scientist. She is Professor at the Department of Computer Science of the Technical University of Darmstadt and Director of Ubiquitous Knowledge Processing Lab.

<span class="mw-page-title-main">Rada Mihalcea</span> American computer scientist

Rada Mihalcea is a Janice M. Jenkins Collegiate Professor of Computer Science and Engineering at the University of Michigan. She has made contributions to natural language processing, multimodal processing, and computational social science. With Paul Tarau, she is the co-inventor of TextRank Algorithm, which is widely used for text summarization.

Mona Talat Diab is a computer science professor and director of Carnegie Mellon University's Language Technologies Institute. Previously, she was a professor at George Washington University and a research scientist with Facebook AI. Her research focuses on natural language processing, computational linguistics, cross lingual/multilingual processing, computational socio-pragmatics, Arabic language processing, and applied machine learning.

Ani Nenkova is Principal Scientist at Adobe Research, currently on leave from her position as an Associate Professor of Computer and Information Science at the University of Pennsylvania. Her research focuses on computational linguistics and artificial intelligence, with an emphasis on developing computational methods for analysis of text quality and style, discourse, affect recognition, and summarization.

References

  1. "Michael Collins". www.cs.columbia.edu. Retrieved 6 June 2022.
  2. "Michael Collins - Google Scholar Citations". Google Scholar. Retrieved 11 November 2015.
  3. Collins, Michael. Collins's Columbia website.
  4. "ACL Fellows". ACL Wiki. Retrieved 15 August 2017.