Chief of Artificial Intelligence, Professor
Boston
Chief of Artificial Intelligence, Professor
Boston
Chief of Artificial Intelligence, Professor
Boston
Chief of Artificial Intelligence, Professor
Boston
Javed Aslam is chief of artificial intelligence and a professor at the Khoury College of Computer Sciences at Northeastern University. While most of his research entails machine learning and information retrieval, he has experience in the fields of human computation, transportation, computer security, wireless networking, and medical informatics.
Before joining Northeastern University, he was an assistant professor in the Department of Computer Science at Dartmouth College. He also held a postdoctoral position in the School of Engineering and Applied Sciences at Harvard University.
In machine learning, Aslam has developed models and algorithms for multi-label classification and learning in the presence of noisy or erroneous training data. In information retrieval, he has applied techniques from machine learning, statistics, information theory, and social choice theory to develop algorithms for automatic information organization, metasearch, and efficient search engine training and evaluation.
Aslam served as the general co-chair for the 2009 ACM SIGIR Conference on Research and Development in Information Retrieval, and he also served as the program co-chair for SIGIR 2016.
Javed Aslam is chief of artificial intelligence and a professor at the Khoury College of Computer Sciences at Northeastern University. While most of his research entails machine learning and information retrieval, he has experience in the fields of human computation, transportation, computer security, wireless networking, and medical informatics.
Before joining Northeastern University, he was an assistant professor in the Department of Computer Science at Dartmouth College. He also held a postdoctoral position in the School of Engineering and Applied Sciences at Harvard University.
In machine learning, Aslam has developed models and algorithms for multi-label classification and learning in the presence of noisy or erroneous training data. In information retrieval, he has applied techniques from machine learning, statistics, information theory, and social choice theory to develop algorithms for automatic information organization, metasearch, and efficient search engine training and evaluation.
Aslam served as the general co-chair for the 2009 ACM SIGIR Conference on Research and Development in Information Retrieval, and he also served as the program co-chair for SIGIR 2016.
