Institute for Computational and Mathematical Engineering (ICME)
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Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2013
BioI am a fourth-year Ph.D. candidate in the Institute for Computational and Mathematical Engineering advised by Professor Emmanuel J. Candès. My research interests include mathematical signal processing, optimization, and computational imaging and geometry.
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2016
Current Research and Scholarly InterestsData Science, Information Retrieval, Machine Learning and Data Mining
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2017
BioI am a master's student at ICME, interested in applications of machine learning to problems from social and behavioral science, healthcare and economics.
I graduated from IIT Madras with a bachelor's degree in electrical engineering in 2014. Prior to joining ICME, I worked as a quant in the asset management industry for three years.
Barney and Estelle Morris Professor
Current Research and Scholarly InterestsResearch
My students and I devise new algorithms to improve the imaging of reflection seismic data. Images obtained from seismic data are the main source of information on the structural and stratigraphic complexities in Earth's subsurface. These images are constructed by processing seismic wavefields recorded at the surface of Earth and generated by either active-source experiments (reflection data), or by far-away earthquakes (teleseismic data). The high-resolution and fidelity of 3-D reflection-seismic images enables oil companies to drill with high accuracy for hydrocarbon reservoirs that are buried under two kilometers of water and up to 15 kilometers of sediments and hard rock. To achieve this technological feat, the recorded data must be processed employing advanced mathematical algorithms that harness the power of huge computational resources. To demonstrate the advantages of our new methods, we process 3D field data on our parallel cluster running several hundreds of processors.
I teach a course on seismic imaging for graduate students in geophysics and in the other departments of the School of Earth Sciences. I run a research graduate seminar every quarter of the year. This year I will be teaching a one-day short course in 30 cities around the world as the SEG/EAGE Distinguished Instructor Short Course, the most important educational outreach program of these two societies.
2007 SEG/EAGE Distinguished Instructor Short Course (2007); co-director, Stanford Exploration Project (1998-present); founding member, Editorial Board of SIAM Journal on Imaging Sciences (2007-present); member, SEG Research Committee (1996-present); chairman, SEG/EAGE Summer Research Workshop (2006)
Reza Bosagh Zadeh
Adjunct Professor, Institute for Computational and Mathematical Engineering (ICME)
BioReza Bosagh Zadeh is an Adjunct Professor at Stanford University and Founder CEO at Matroid. His work focuses on Machine Learning, Distributed Computing, and Discrete Applied Mathematics. Reza received his PhD in Computational Mathematics from Stanford University under the supervision of Gunnar Carlsson. His awards include a KDD Best Paper Award and the Gene Golub Outstanding Thesis Award. He has served on the Technical Advisory Board of Microsoft and Databricks.
As part of his research, Reza built the Machine Learning Algorithms behind Twitter's who-to-follow system, the first product to use Machine Learning at Twitter. Reza is the initial creator of the Linear Algebra Package in Apache Spark. Through Apache Spark, Reza's work has been incorporated into industrial and academic cluster computing environments. In addition to research, Reza designed and teaches two PhD-level classes at Stanford: Distributed Algorithms and Optimization (CME 323), and Discrete Mathematics and Algorithms (CME 305).