Data Science
Data Science
Data Science
Wed 01.20.16
Data Science
Wed 01.20.16
Data Science
Data Science
Data Science
Wed 01.20.16
Data Science
Wed 01.20.16
Keywords
machine learning, statistics, data mining, parallel & distributed data analysis, database systems, information retrieval, knowledge representation, information visualization, natural language processing, computational biology and bioinformatics, computational social science, digital humanities, health informatics, business and predictive analytics
Keywords
machine learning, statistics, data mining, parallel & distributed data analysis, database systems, information retrieval, knowledge representation, information visualization, natural language processing, computational biology and bioinformatics, computational social science, digital humanities, health informatics, business and predictive analytics
Keywords
machine learning, statistics, data mining, parallel & distributed data analysis, database systems, information retrieval, knowledge representation, information visualization, natural language processing, computational biology and bioinformatics, computational social science, digital humanities, health informatics, business and predictive analytics
Keywords
machine learning, statistics, data mining, parallel & distributed data analysis, database systems, information retrieval, knowledge representation, information visualization, natural language processing, computational biology and bioinformatics, computational social science, digital humanities, health informatics, business and predictive analytics
Interdisciplinary research for a data-driven world
How can we address the unique challenges of our increasingly data-driven society? At Khoury College of Computer Sciences, we develop new methods and tools for effective data storage, retrieval, visualization, and interpretation. Data science research impacts a broad range of disciplines striving to drive society forward—from basic science and engineering to political and social science to human health.
Areas of investigation
- Business and predictive analytics
- Computational epidemiology
- Computational molecular biology and bioinformatics
- Computational social science
- Computer vision
- Data mining
- Database systems
- Digital humanities
- Game analytics
- Health informatics
- Information retrieval
- Information visualization
- Knowledge representation
- Machine learning
- Natural language processing
- Parallel and distributed data analysis
- Statistics
Interdisciplinary research for a data-driven world
How can we address the unique challenges of our increasingly data-driven society? At Khoury College of Computer Sciences, we develop new methods and tools for effective data storage, retrieval, visualization, and interpretation. Data science research impacts a broad range of disciplines striving to drive society forward—from basic science and engineering to political and social science to human health.
Areas of investigation
- Business and predictive analytics
- Computational epidemiology
- Computational molecular biology and bioinformatics
- Computational social science
- Computer vision
- Data mining
- Database systems
- Digital humanities
- Game analytics
- Health informatics
- Information retrieval
- Information visualization
- Knowledge representation
- Machine learning
- Natural language processing
- Parallel and distributed data analysis
- Statistics
Interdisciplinary research for a data-driven world
How can we address the unique challenges of our increasingly data-driven society? At Khoury College of Computer Sciences, we develop new methods and tools for effective data storage, retrieval, visualization, and interpretation. Data science research impacts a broad range of disciplines striving to drive society forward—from basic science and engineering to political and social science to human health.
Areas of investigation
- Business and predictive analytics
- Computational epidemiology
- Computational molecular biology and bioinformatics
- Computational social science
- Computer vision
- Data mining
- Database systems
- Digital humanities
- Game analytics
- Health informatics
- Information retrieval
- Information visualization
- Knowledge representation
- Machine learning
- Natural language processing
- Parallel and distributed data analysis
- Statistics
Interdisciplinary research for a data-driven world
How can we address the unique challenges of our increasingly data-driven society? At Khoury College of Computer Sciences, we develop new methods and tools for effective data storage, retrieval, visualization, and interpretation. Data science research impacts a broad range of disciplines striving to drive society forward—from basic science and engineering to political and social science to human health.
Areas of investigation
- Business and predictive analytics
- Computational epidemiology
- Computational molecular biology and bioinformatics
- Computational social science
- Computer vision
- Data mining
- Database systems
- Digital humanities
- Game analytics
- Health informatics
- Information retrieval
- Information visualization
- Knowledge representation
- Machine learning
- Natural language processing
- Parallel and distributed data analysis
- Statistics
Labs and groups
Labs and groups
Labs and groups
Labs and groups
Notable research achievements
- Developed a new class of efficient algorithms with provable guarantees, which have state-of-the-art applications for several important problems in computer vision, including motion segmentation in videos, human activity modeling, and data summarization.
- Received a $1.8M National Institutes of Health (NIH) grant to develop techniques for automated reconstruction of structure and dynamics in neural circuits—a major step toward understanding the brain.
- Developed statistical methods and software for modern biotechnologies, which study complex biomolecular systems on a large scale. One such tool, Cardinal, developed for statistical analysis of mass spectrometry-based imaging experiments, received the 2015 John M. Chambers Statistical Software Award of the American Statistical Association.
- Pioneered the field of game analytics and published the first book on the topic: Game Analytics: Maximizing the Value of Player Data.
- Conducted a study on biases in peer review that measured “intellectual distance” between the knowledge embodied in research proposals and an evaluator’s own expertise. The work informs peer-review policies of large science funding organizations like the National Science Foundation (NSF) and the National Institutes of Health (NIH).
Notable research achievements
- Developed a new class of efficient algorithms with provable guarantees, which have state-of-the-art applications for several important problems in computer vision, including motion segmentation in videos, human activity modeling, and data summarization.
- Received a $1.8M National Institutes of Health (NIH) grant to develop techniques for automated reconstruction of structure and dynamics in neural circuits—a major step toward understanding the brain.
- Developed statistical methods and software for modern biotechnologies, which study complex biomolecular systems on a large scale. One such tool, Cardinal, developed for statistical analysis of mass spectrometry-based imaging experiments, received the 2015 John M. Chambers Statistical Software Award of the American Statistical Association.
- Pioneered the field of game analytics and published the first book on the topic: Game Analytics: Maximizing the Value of Player Data.
- Conducted a study on biases in peer review that measured “intellectual distance” between the knowledge embodied in research proposals and an evaluator’s own expertise. The work informs peer-review policies of large science funding organizations like the National Science Foundation (NSF) and the National Institutes of Health (NIH).
Notable research achievements
- Developed a new class of efficient algorithms with provable guarantees, which have state-of-the-art applications for several important problems in computer vision, including motion segmentation in videos, human activity modeling, and data summarization.
- Received a $1.8M National Institutes of Health (NIH) grant to develop techniques for automated reconstruction of structure and dynamics in neural circuits—a major step toward understanding the brain.
- Developed statistical methods and software for modern biotechnologies, which study complex biomolecular systems on a large scale. One such tool, Cardinal, developed for statistical analysis of mass spectrometry-based imaging experiments, received the 2015 John M. Chambers Statistical Software Award of the American Statistical Association.
- Pioneered the field of game analytics and published the first book on the topic: Game Analytics: Maximizing the Value of Player Data.
- Conducted a study on biases in peer review that measured “intellectual distance” between the knowledge embodied in research proposals and an evaluator’s own expertise. The work informs peer-review policies of large science funding organizations like the National Science Foundation (NSF) and the National Institutes of Health (NIH).
Notable research achievements
- Developed a new class of efficient algorithms with provable guarantees, which have state-of-the-art applications for several important problems in computer vision, including motion segmentation in videos, human activity modeling, and data summarization.
- Received a $1.8M National Institutes of Health (NIH) grant to develop techniques for automated reconstruction of structure and dynamics in neural circuits—a major step toward understanding the brain.
- Developed statistical methods and software for modern biotechnologies, which study complex biomolecular systems on a large scale. One such tool, Cardinal, developed for statistical analysis of mass spectrometry-based imaging experiments, received the 2015 John M. Chambers Statistical Software Award of the American Statistical Association.
- Pioneered the field of game analytics and published the first book on the topic: Game Analytics: Maximizing the Value of Player Data.
- Conducted a study on biases in peer review that measured “intellectual distance” between the knowledge embodied in research proposals and an evaluator’s own expertise. The work informs peer-review policies of large science funding organizations like the National Science Foundation (NSF) and the National Institutes of Health (NIH).
FEATURED RESEARCH
FEATURED RESEARCH
Faculty
Faculty
PUBLISHED RESEARCH
PUBLISHED RESEARCH
© 2024 Northeastern University
Khoury Social
Contact Khoury
440 Huntington Avenue, 202 West Village H
Boston, MA 02115
617.373.2462
TTY: 617.373.3768
Khoury Social
Contact Khoury
440 Huntington Avenue, 202 West Village H
Boston, MA 02115
617.373.2462
TTY: 617.373.3768
x
x
About
Programs
Experiential Learning
Research
Life at Khoury
Information for...
x
About
Programs
Experiential Learning
Research
Life at Khoury
Information for...
© 2024 Northeastern University
Khoury Social
Contact Khoury
440 Huntington Avenue, 202 West Village H
Boston, MA 02115
617.373.2462
TTY: 617.373.3768
Khoury Social
Contact Khoury
440 Huntington Avenue, 202 West Village H
Boston, MA 02115
617.373.2462
TTY: 617.373.3768
x
x
About
Programs
Experiential Learning
Research
Life at Khoury
Information for...
x
About
Programs
Experiential Learning
Research
Life at Khoury
Information for...