Computer Science Ph.D. students Yanif Ahmad and Anna Ritz recently received fellowships from IBM’s Ph.D. Fellowship Awards Program and the National Science Foundation’s Graduate Research Fellowship Program, respectively, two prestigious and highly competitive fellowship programs.
Yanif’s research spans data stream query processing and optimization, and investigates how to augment processing with data models capturing the time-varying nature of attributes, to efficiently process queries. This continuously changing, time-dependent data naturally occurs in many stream applications, especially geospatial and financial applications. The models are an approximation of the raw data, requiring techniques to manage errors and their propagation during query processing.
Anna’s proposed plan of research is to design new algorithms to analyze high-throughput, temporal measurements of cellular signaling networks. She hopes her computational tools will be useful to biologists studying how cells transmit information and respond to external stimuli. Anna’s recent work, “Quantitative Time-Resolved Phosphoproteomic Analysis of Mast Cell Signaling,” was published in the November 2007 issue of The Journal of Immunology.
The IBM Ph.D. Fellowships provide support for one academic year and may be renewed for two more years. Nominations are submitted by departments worldwide and award recipients are selected based on their overall potential for research excellence, their academic progress to-date, as evidenced by publications, and the degree to which their technical interests align with those of IBM.
The NSF Graduate Research Fellowships provide three years of support leading to research-based master’s or doctoral degrees and are intended for individuals in the early stages of their graduate study in the fields of science, technology, engineering, and mathematics. Awards are granted based on previous research experience, the proposed plan of research, and the student’s ability to make a “broader impact” in their program of study in terms of educational, industrial, and societal relevance.