Four UW faculty members have been awarded Sloan Research Fellowships, given to the very best young faculty in the country in designated scientific fields.
This year’s UW recipients are Daniel Chiu, assistant professor of chemistry; Venkatesan Guruswami and Mark Oskin, both assistant professors of computer science & engineering and Adrienne Fairhall, assistant professor of physiology and biophysics.
A total of 116 fellowships were awarded in seven fields: chemistry, computational and evolutionary molecular biology, computer science, economics, mathematics, neuroscience, and physics. Fellowships of $40,000 are awarded for a two-year period. Funds may be used by the Fellow for such purposes as equipment, technical assistance, professional travel, trainee support, or any other activity directly related to the Fellow’s research.
In 2004, the UW also was awarded three Sloan Research Fellowships; two of those also went to faculty in the Computer Science & Engineering Department.
Chiu studies how biological systems, based on a complex series of coupled biochemical reactions, encode and process information. To approach this question experimentally, his research focuses on the development of new tools that combine ultrasensitive laser-based detection and manipulation methodologies with micro- and nano-fabrication techniques for interfacing with biological systems at the nanometer scale.
Guruswami’s research interests lie in theoretical computer science, and specifically focus on topics such as error-correcting codes, graph-theoretic optimization and approximation problems, probabilistically checkable proofs, hardness of approximations and complexity theory.
Oskin heads the WaveScalar project, which brings together two ideas: distributing computation across a set of homogenous “tiles” that merge an instruction cache and a microprocessor into a single concept; and using dataflow as the basis for programming these tiles.
Fairhall studies how neurons transform time-varying inputs into a string of output pulses, using both experimental data and simple neural model dynamical systems.