Institute for Computational and Mathematical Engineering (ICME)
Showing 1-50 of 196 Results
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Guillermo (Willie) Aboumrad Sidaoui
Masters Student in Computational and Mathematical Engineering, admitted Winter 2016
SUMO Tutor, Leadership Education & Athletic Advising ResourcesBioWillie was born and raised in Mexico City. Aged 16, he moved to the UK to continue his high school studies. In the fall of 2014, Willie arrived at Stanford to begin his undergraduate career in Mathematics. Interested in applications of mathematical theory, he later gained admission to the Master's program at ICME. Having completed his undergraduate studies and having passed the ICME qualifying exams last summer, Willie is currently seeking an advisor to guide him through doctoral research.
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Rehman Ali
Ph.D. Student in Electrical Engineering, admitted Autumn 2017
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2017BioRehman Ali received the B.S. degree in biomedical engineering from Georgia Institute of Technology in 2016. He is currently an NDSEG fellow, completing a M.S. in Computational & Mathematical Engineering and pursuing a Ph.D. in Electrical Engineering at Stanford. His research interests include signal processing, inverse problems, computational modeling of acoustics, and real-time beamforming algorithms. His current research is developing accurate and spatially resolved speed-of-sound imaging in tissue based on phase aberration correction, spatial coherence, and computed tomography
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Juan J. Alonso
Professor of Aeronautics and Astronautics
BioProf. Alonso is the founder and director of the Aerospace Design Laboratory (ADL) where he specializes in the development of high-fidelity computational design methodologies to enable the creation of realizable and efficient aerospace systems. Prof. Alonso’s research involves a large number of different manned and unmanned applications including transonic, supersonic, and hypersonic aircraft, helicopters, turbomachinery, and launch and re-entry vehicles. He is the author of over 200 technical publications on the topics of computational aircraft and spacecraft design, multi-disciplinary optimization, fundamental numerical methods, and high-performance parallel computing. Prof. Alonso is keenly interested in the development of an advanced curriculum for the training of future engineers and scientists and has participated actively in course-development activities in both the Aeronautics & Astronautics Department (particularly in the development of coursework for aircraft design, sustainable aviation, and UAS design and operation) and for the Institute for Computational and Mathematical Engineering (ICME) at Stanford University. He was a member of the team that currently holds the world speed record for human powered vehicles over water. A student team led by Prof. Alonso also holds the altitude record for an unmanned electric vehicle under 5 lbs of mass.
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Remmelt Ammerlaan
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2017
BioI am originally from the Netherlands and currently studying Computational and Mathematical engineering at Stanford. My interest is in data-science and its applications to large scale projects such as construction, infrastructure and city management.
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Jing An
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2016
BioI am a second-year PhD student in the Institute for Computational and Mathematical Engineering. I obtained my B.S. degree in Mathematics of Computation from the University of California, Los Angeles. My research interests include partial differential equations, numerical analysis and their applications in fluids, biology.
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David Barmherzig
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.
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Shruti Bhargava
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2016
Current Research and Scholarly InterestsData Science, Information Retrieval, Machine Learning and Data Mining
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Jayadev Bhaskaran
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. -
Biondo Biondi
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.
Teaching
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.
Professional Activities
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). -
Stephen Boyd
Samsung Professor in the School of Engineering and Professor, by courtesy, of Computer Science and of Management Science and Engineering
BioStephen P. Boyd is the Samsung Professor of Engineering, and Professor of Electrical Engineering in the Information Systems Laboratory at Stanford University. He has courtesy appointments in the Department of Management Science and Engineering and the Department of Computer Science, and is member of the Institute for Computational and Mathematical Engineering. His current research focus is on convex optimization applications in control, signal processing, machine learning, and finance.
Professor Boyd received an AB degree in Mathematics, summa cum laude, from Harvard University in 1980, and a PhD in EECS from U. C. Berkeley in 1985. In 1985 he joined the faculty of Stanford's Electrical Engineering Department. He has held visiting Professor positions at Katholieke University (Leuven), McGill University (Montreal), Ecole Polytechnique Federale (Lausanne), Tsinghua University (Beijing), Universite Paul Sabatier (Toulouse), Royal Institute of Technology (Stockholm), Kyoto University, Harbin Institute of Technology, NYU, MIT, UC Berkeley, CUHK-Shenzhen, and IMT Lucca. He holds honorary doctorates from Royal Institute of Technology (KTH), Stockholm, and Catholic University of Louvain (UCL).
Professor Boyd is the author of many research articles and three books: Convex Optimization (with Lieven Vandenberghe, 2004), Linear Matrix Inequalities in System and Control Theory (with L. El Ghaoui, E. Feron, and V. Balakrishnan, 1994), and Linear Controller Design: Limits of Performance (with Craig Barratt, 1991). His group has produced many open source tools, including CVX (with Michael Grant), CVXPY (with Steven Diamond) and Convex.jl (with Madeleine Udell and others), widely used parser-solvers for convex optimization.
Professor Boyd has received many awards and honors for his research in control systems engineering and optimization, including an ONR Young Investigator Award, a Presidential Young Investigator Award, and the AACC Donald P. Eckman Award. In 2013, he received the IEEE Control Systems Award, given for outstanding contributions to control systems engineering, science, or technology. In 2012, Michael Grant and he were given the Mathematical Optimization Society's Beale-Orchard-Hays Award, given every three years for excellence in computational mathematical programming. He is a Fellow of the IEEE, SIAM, and INFORMS, a Distinguished Lecturer of the IEEE Control Systems Society, and a member of the US National Academy of Engineering and a foreign member of the Chinese Academy of Engineering. He has been invited to deliver more than 90 plenary and keynote lectures at major conferences in control, optimization, signal processing, and machine learning.
He has developed and taught many undergraduate and graduate courses, including Signals & Systems, Linear Dynamical Systems, Convex Optimization, and a recent undergraduate course on Matrix Methods. His graduate convex optimization course attracts around 300 students from more than 20 departments. In 1991 he received an ASSU Graduate Teaching Award, and in 1994 he received the Perrin Award for Outstanding Undergraduate Teaching in the School of Engineering. In 2003, he received the AACC Ragazzini Education award, for contributions to control education, with citation: “For excellence in classroom teaching, textbook and monograph preparation, and undergraduate and graduate mentoring of students in the area of systems, control, and optimization.” In 2016 he received the Walter J. Gores award, the highest award for teaching at Stanford University. In 2017 he received the IEEE James H. Mulligan, Jr. Education Medal, for a career of outstanding contributions to education in the fields of interest of IEEE, with citation "For inspirational education of students and researchers in the theory and application of optimization." -
Steven Brill
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2016
BioI am a second year PhD student in the Institute for Computational and Mathematical Engineering (ICME). I am interested in computational fluid dynamics, higher order methods for numerical PDEs, and high performance computing. I earned my bachelor's degree in mechanical engineering at the University of Notre Dame. I am originally from Cincinnati, Ohio. In my free time I enjoy juggling, hiking, and college football.
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Carlos Bustamante
Professor of Biomedical Data Science, of Genetics and, by courtesy, of Biology
Current Research and Scholarly InterestsMy research focuses on analyzing genome wide patterns of variation within and between species to address fundamental questions in biology, anthropology, and medicine. My group works on a variety of organisms and model systems ranging from humans and other primates to domesticated plant and animals. Much of our research is at the interface of computational biology, mathematical genetics, and evolutionary genomics.
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Daniel Byrnes
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2016
BioDaniel is an ICME student interested in 3D modeling, motion planning, optimal control, and machine learning. Over the course of summer 2017 he worked on problems related to point cloud alignment as a software engineer intern at DeepMap. Daniel received his BA in mathematics from Bowdoin College in 2015.
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Leopold Cambier
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2015
Current Research and Scholarly InterestsFast Linear Solver for BEM equations
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Emmanuel Candes
Barnum-Simons Chair in Math and Statistics, and Professor of Statistics and, by courtesy, of Electrical Engineering
BioEmmanuel Candès is the Barnum-Simons Chair in Mathematics and Statistics, a professor of electrical engineering (by courtesy) and a member of the Institute of Computational and Mathematical Engineering at Stanford University. Earlier, Candès was the Ronald and Maxine Linde Professor of Applied and Computational Mathematics at the California Institute of Technology. His research interests are in computational harmonic analysis, statistics, information theory, signal processing and mathematical optimization with applications to the imaging sciences, scientific computing and inverse problems. He received his Ph.D. in statistics from Stanford University in 1998.
Candès has received several awards including the Alan T. Waterman Award from NSF, which is the highest honor bestowed by the National Science Foundation, and which recognizes the achievements of early-career scientists. He has given over 60 plenary lectures at major international conferences, not only in mathematics and statistics but in many other areas as well including biomedical imaging and solid-state physics. He was elected to the National Academy of Sciences and to the American Academy of Arts and Sciences in 2014. -
Gunnar Carlsson
Ann and Bill Swindells Professor, Emeritus
BioDr. Carlsson has been a professor of mathematics at Stanford University since 1991. In the last ten years, he has been involved in adapting topological techniques to data analysis, under NSF funding and as the lead PI on the DARPA “Topological Data Analysis” project from 2005 to 2010. He is the lead organizer of the ATMCS conferences, and serves as an editor of several Mathematics journals
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Ines Chami
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2016
BioI am a second-year Masters student in the ICME data science program. Prior to joining Stanford, I studied mathematics and computer science at Ecole Centrale Paris. My research interests include computer vision, natural language processing and, more specifically, multimodal analysis. My previous research was focused on cross-modal information retrieval (image annotation and automated text-illustration). I am currently working on information extraction from semi-structured data (pdf tables) within the Hazy Research group led by Prof. Ré at Stanford.
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Enze Chen
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2016
BioEnze is concurrently pursuing a Master's degree in ICME and a Bachelor's degree in Materials Science and Engineering at Stanford University. He wishes to apply machine learning, data science, and other computational tools to problems in the materials domain to accelerate R&D. His research in Prof. Evan Reed's group involves statistical learning of kinetic Monte Carlo models for complex chemical reactions.
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Casey Chu
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2016
Current Research and Scholarly InterestsTheoretical foundations of inference.
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Sean Clement
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2016
BioI am a masters student in Stanford's Computational Mathematics and Engineering department starting in 2016. I am currently a Captain in the US Army where I work in the FA49 branch which handles all of the Army's Operations Research and Systems Analysis needs. I chose to study here at Stanford after completing my company command in Germany. Previously, I was a UH-60A/L Blackhawk pilot and majored in Operations Research at the United States Military Academy at West Point. I'm very excited to not only study here at Stanford but also be much closer to my family in the Pacific Northwest. I enjoy traveling, camping, hockey, and archery.
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Eric Darve
Associate Professor of Mechanical Engineering
BioProfessor Darve's research is focused on the development of numerical methods for large scale scientific computing with applications in biomolecular simulations, acoustics, electromagnetics, and microfluidics. In these applications, the computational expense of simulating large and complex systems is very significant and in many instances beyond current computer capabilities. He is developing innovative numerical techniques to reduce this computational expense and enable the simulation of complex systems over realistic time scales. Professor Darve also uses processors with novel architectures, such as GPUs and the Cell processor, for scientific computing. Applications range from particle simulation to fluid dynamics and solving partial differential equations.
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Andrew Deveau
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2017
BioI am a masters student in the data science track within the Institute for Computational and Mathematical Engineering. Before coming to Stanford, I received a B.S. in mathematics from Yale and spent two years working for a proprietary trading firm. I am broadly interested in reinforcement learning and socially beneficial applications of machine learning.
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David Donoho
Anne T. and Robert M. Bass Professor in the School of Humanities and Sciences
BioDavid Donoho is a mathematician who has made fundamental contributions to theoretical and computational statistics, as well as to signal processing and harmonic analysis. His algorithms have contributed significantly to our understanding of the maximum entropy principle, of the structure of robust procedures, and of sparse data description.
Research Statement:
My theoretical research interests have focused on the mathematics of statistical inference and on theoretical questions arising in applying harmonic analysis to various applied problems. My applied research interests have ranged from data visualization to various problems in scientific signal processing, image processing, and inverse problems.
