The Data Mining and Machine Learning lab (DMML) is led by Professor Huan Liu with a research focus on developing computational methods for data mining, machine learning, and social computing, and designing efficient algorithms to enable effective problem solving ranging from text/web mining, feature selection with a focus on real-world applications. The research includes (i) dealing with high dimensional data via feature selection and feature discretization; (ii) social computing, social media mining, group understanding, and interaction; (iii) integrating multiple data sources to overcome ambiguity and uncertainty, (iv) employing domain knowledge for effective mining and information integration, and (v) assisting human experts by developing effective methods of ensemble learning, semi-supervised learning, and active learning with hierarchical classification, subspace clustering, and metadata. Recent investigations have been to develop methods to apply these research findings to the area of social cyber attacks, such as misinformation campaigns, bot detection, and better handling PII. The research done by members of this group has received international acclaim. The group has produced over 200 conference papers, 100 journal articles, and 19 books including 1 textbook and 8 monographs. Their research works have generated worldwide impact and received more than 30,000 citations (https://scholar.google.com/citations?user=Dzf46C8AAAAJ&hl=en)
Motivated by our research on understanding the way users behave and interact on social media platforms and the lack of existing solutions which enable first responders to capture and use the information in social media for disaster response, we have built innovative social media tracking systems, such as TweetTracker, TweetXplorer, and ASU Coordination Tracker (ACT). These systems have helped first responders make informed decisions by incorporating the social signal produced during times of disaster. By bridging the gap between first responders and the information generated on social media we are working towards ASU's challenge of focusing information and technology to produce meaningful change. Our systems have been used by over 200 organizations, including Universities, government agencies, and NGOs. The work done on these tools has earned the lab the ASU President's Award for Innovation, the highest award for research at ASU. The systems developed as part of this project are exemplary of the innovation aspirations of ASU. Our tools are the first of their kind to aid first responders in making sense of the noisy and voluminous data generated on social media. In developing these tools, we have helped first responders to create an informed picture of the events of Hurricane Sandy, Typhoon Haiyan, and several others.
The DMML lab has produced first-class students, many of whom have been recognized for their achievements. Among the members are a Dean's Fellowship award winner, two ASU Faculty Emeriti Fellows, and two SMART scholars. Students have won awards ranging from the 2014 Outstanding Computer Science TA award, two US President's Volunteer Service Awards, and the ASU Graduate Education Dissertation Fellowship. Undergraduate students in the lab have been successful in winning awards pertaining to research, including prestigious awards such as the FURI award, and honorable mention for the CRA Outstanding Undergraduate Research Award. In the last five years, the DMML lab graduated 13 Ph.D. students, 4 of them became professors have gone on to be tenure-track faculty at research universities and other alumni of the lab are working at leading companies and start-ups in the area of data mining and predictive analytics (e.g., LinkedIn, Yahoo, Google, Microsoft, Amazon).