Director

  • Andrew McCallum Professor

    The main goal of my research is to dramatically increase our ability to mine actionable knowledge from unstructured text. I am especially interested in information extraction from the Web, understanding the connections between people and between organizations, expert finding, social network analysis, and mining the scientific literature & community. Toward this end my group develops and employs various methods in statistical machine learning, natural language processing, information retrieval and data mining---tending toward probabilistic approaches and graphical models.

Postdocs

  • Pedram Rooshenas Postdoc, started 2017

    Currently, I'm working on tractable learning and inference algorithms and probabilistic graphical models.

  • Jeffrey Flanigan Postdoc, started 2017

    My research interests lie in the areas of structured prediction, machine learning, and natural language processing. I work to make computers understand and generate natural language better (semantic parsing and generation) and to help people who speak different languages communicate (machine translation).

  • Xun Wang Postdoc, started 2018

    I am interested in using linguistic insights to design algorithms for solving practical problems. Currently I am working on entity-based text representation, and inferring and translating using these entities.

  • Michael Boratko Postdoc, started 2018

    My current research focuses on box embeddings and structured prediction. Broadly speaking, I am interested in information extraction, program synthesis, deep learning and optimization.

PhD Students

  • Ari Kobren PhD, started 2012

    Currently, I'm working on interactive data integration--or combining multiple, heterogeneous sources of data into a single, consistent knowledge base with a human in the loop.

  • Luke Vilnis PhD, started 2012

    I am broadly interested in machine learning, natural language processing and knowledge base construction. Areas of interest include common sense knowledge, representation learning, structured prediction, coreference, and optimization.

  • Emma Strubell PhD, started 2012

    I am interested in developing new machine learning techniques to facilitate fast, accurate and robust natural language processing of text.

  • Patrick Verga PhD, started 2012

    My research is broadly in the areas of information extraction, natural language processing, and machine learning. I primarily work on extracting and representing entities and their relations for constructing embedded knowledge bases.

  • Nicholas Monath PhD, started 2014

    The focus of my research is on scalable methods for entity resolution, the task of determining the underlying entities referred to by a set of ambiguous mentions. I am interested in two settings of this problem, with and without an existing knowledge base.

  • Craig Greenberg PhD, started 2014

    I'm generally interested in artificial intelligence, machine learning, and reasoning under uncertainty, especially as it applies human language technology. My research focuses on compact representation of uncertainty, as well as its transmission, measurement, and calibration.

  • Rajarshi Das PhD, started 2016 (spring)

    Rajarshi's research interest lies in open domain question answering and in reasoning on large knowledge bases and on anything in the interesection of those two.

  • Trapit Bansal PhD, started 2015

    My current research is on knowledge representation and reasoning. Broadly, I am interested in deep learning and reinforcement learning.

  • Javier Burroni PhD, started 2015

    My current research is on Probabilistic Programming Languages. In particular, the relation between programming languages and gradient-based inference.

  • Haw-Shiuan Chang PhD, started 2015

    My current interests include knowledge representation, text entailment, relation extraction, graph embedding, and active learning.

  • Dung Thai PhD, started 2016

    My research focus on structured predictions which involve deep learning and probabilistic graphical models. I am also interested in generative models and tasks concern both language model and vision model.

  • Xiang Li (Lorraine) PhD, started 2016

    My research interests involve Natural Language Processing, especially commonsense knowledge reasoning.

  • Sheshera Mysore PhD, started 2018

    Current interests include neural network models to learn representations of common sense knowledge defined as event frames and event chains.

  • Neha Nayak PhD, started 2018

  • Andrew Drozdov PhD, started 2018

    My current research interests are in automatically generating knowledge bases from raw text and vice versa.

Affiliated PhD Students

  • Mohit Yadav PhD, started 2017

    I am broadly interested in machine learning and unsupervised deep learning methods for NLP.

  • Dongxu Zhang PhD, started 2017

    My main research interests lie in information extraction, knowledge representation and reasoning, question answering and machine learning.

  • Nishant Yadav PhD, started 2017

    I am broadly interested in machine learning  and natural language processing. A bit more specifically, I am interested in methods for learning representation of entities, structured prediction models and clustering.

  • Justin Payan PhD, started 2018

    I'm generally interested in natural language processing and network science, as well as the intersection of the two.

Masters Students

Undergraduates

Staff

Alumni