Search Results for "-P웹문서-찌라시전문첫페이지‑(-@hhu9999 )최저가상위노출도배문의ޜ구글-웹문서전문1페이지㈪구글-웹문서1페이지전문홍보팀㏽구글-찌라시광고프로그램 -.pij"

Mohammad Raihanul Islam

Mohammad Raihanul Islam was a Ph.D. student in the Department of Computer Science, advised by Naren Ramakrishnan.  His research interests include data mining, text mining, and computational social science.

Yaser Keneshloo

Yaser Keneshloo is a DAC Ph.D. student in the Department of Computer Science and his advisor is Naren Ramakrishnan. Keneshloo’s research interest lies in forecasting domestic political crises in countries of interest, a useful tool for social scientists and policy makers. A wealth of event data is now available for historical as well as prospective analysis. […]

Sathappan Muthiah

Sathappan Muthiah was a Ph.D. student in the Department of Computer Science.  He was advised by Naren Ramakrishnan. Muthiah’s areas of interest and specialties include forecasting, machine learning, information retrieval, topic detection and tracking (TDT).

Rongrong Tao

Rongrong Tao was a Ph.D. student in the Department of Computer Science.  Her advisor was Naren Ramakrishnan. Tao’s research interest lies in forecasting population-level events.

Huijuan Shao

Huijuan Shao was a Ph.D. student working on data mining models for smart buildings. Specifically, she uses temporal models to mine time series for energy disaggregation and occupancy prediction. Energy disaggregation is used to analyze the electricity usage of each device inside buildings by monitoring only the whole-house meter at entry service. Occupancy prediction aims […]

Wei Wang

Wei Wang was a Ph.D. student in the Department of Computer Science. His advisor was Naren Ramakrishnan. His research interest spans a number of areas in data mining and machine learning, including event encoding, anomaly detection, and predictive modeling.

Patterns amongst Competing Task Frequencies: Super-Linearities, and the Almond-DG Model

Competing Memes Propagation on Networks: A Network Science Perspective

Hidden Hazards: Finding Missing Nodes in Large Graph Epidemics

Controlling Propagation at Group Scale on Networks