Artificial Intelligence and Robotics

Encompassed under AI and Robotics are:

Data Analytics and Mining  

Professor Zhang's lab investigates data analytics and mining solutions that efficiently extract valuable knowledge - e.g.,
statistical/aggregate information, hidden features, patterns, trends - from large amounts of structured and unstructured data. In particular, we develop principled sublinear-time algorithms using techniques such as sampling and sketching, and address the various challenges posed by access limitations to the underlying data, e.g., those enforced by the data access channels, caused by privacy concerns.

 

Machine Learning  

Professor Monteleoni's Machine Learning Group is concerned with developing principled methods (known as algorithms) to automatically detect patterns in data. In this era of "Big Data," the various forms of complexity inherent in real data sources increasingly pose challenges for machine learning algorithm design. The GW Machine Learning Group works on the design, analysis, and application of machine learning algorithms, motivated by problems in real data sources, including learning from data streams, learning from raw (unlabeled) data, learning from private data, and climate informatics: accelerating discovery in climate science with machine learning.

 

Claire Monteleoni

Associate Professor

Department: Computer Science
Phone:  202-994-6569
Email: cmontel@gwu.edu
Full Profile 

Research Interest:  Professor Claire Monteleoni's Machine Learning Group is concerned with developing principled methods (known as algorithms) to automatically detect patterns in data. In this era of "Big Data," the various forms of complexity inherent in real data sources increasingly pose challenges for machine learning algorithm design. The GW Machine Learning Group works on the design, analysis, and application of machine learning algorithms, motivated by problems in real data sources, including learning from data streams, learning from raw (unlabeled) data, learning from private data, and climate informatics: accelerating discovery in climate science with machine learning.
 


 

Natural Language Processing 

Statistical Natural Language Processing (NLP) is a rapidly growing exciting field of research in artificial intelligence and computer science. Interdisciplinarity is inherent to NLP drawing on the fields of computer algorithms, software engineering, statistics, machine learning, linguistics, pragmatics, information technology, etc. In NLP, we model language and its use. We build both analytical models and predictive ones. In Professor Diab's NLP lab, we address problems in social media processing building robust enabling technologies such as syntactic and semantic processing tools for written texts in different languages, information extraction tools for large data, multilingual processing, machine translation, and computational sociolinguistic processing. Prof. Diab has a special interest in Arabic NLP where the focus has been on investigating Arabic dialects with very few available automated resources.

 

Mona Diab

Professor

Department: Computer Science
Phone: (202) 994-8109
Email: mtdiab@gwu.edu
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Research Interest: Professor Diab conducts research in Statistical Natural Language Processing (NLP) is a rapidly growing, exciting field of research in artificial intelligence and computer science. Interdisciplinarity is inherent to NLP, drawing on the fields of computer algorithms, software engineering, statistics, machine learning, linguistics, pragmatics, information technology, etc. In NLP, we model language and its use. We build both analytical models and predictive ones. In Professor Mona Diab's NLP lab, we address problems in social media processing, building robust enabling technologies such as syntactic and semantic processing tools for written texts in different languages, information extraction tools for large data, multilingual processing, machine translation, and computational sociolinguistic processing. Professor Diab has a special interest in Arabic NLP, where the emphasis has been on investigating Arabic dialect processing where there are very few available automated resources.