School of Engineering
Showing 1-50 of 307 Results
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Guillermo (Willie) Aboumrad Sidaoui
Ph.D. Student in Computational and Mathematical Engineering, admitted Summer 2018
Other Tech - Graduate, DAPER Departmentwide Operations
SU Student - Summer, School of Engineering - Student AffairsBioWillie was born and raised in Mexico City. He later moved to the UK to complete 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. He is currently pursuing a doctoral degree under the advisory of Prof. Daniel Bump.
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Alex Aiken
Alcatel-Lucent Professor in Communications and Networking and Professor of Particle Physics and Astrophysics and of Photon Science
BioAiken's research focuses on developing techniques for the construction of reliable software systems. His interests include both static and dynamic methods of analyzing programs, and span both detecting errors and verifying the absence of errors in software. Most of his research combines a theoretical component (for example, proving the soundness of an analysis technique) and a practical component, which often involves the implementation and measurement of advanced program analysis algorithms. Finally, his research also extends to the design of new programming languages and programming techniques in which it is easier to write software that can be checked for a wide variety of errors.
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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 third-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. Currently I am interested in stochastic analysis in machine learning algorithms, and PDE analysis in mathematical biology and fluid mechanics.
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Amin Arbabian
Assistant Professor of Electrical Engineering
Current Research and Scholarly InterestsMy group's research covers RF circuits and system design for (1) biomedical, (2) sensing, and (3) Internet of Things (IoT) applications.
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Amel Awadelkarim
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2017
BioMy academic background is in Computational Fluid Dynamics, Finite Element Analysis, and Continuum Mechanics with an M.S. in Engineering Science and Mechanics from Penn State University. I am becoming more and more intrigued by data analytics & applying machine learning techniques to social sciences and networks.
Outside of academia, my interests include consuming music at all times (digitally and at live shows), competing on various Ultimate Frisbee teams (Club and National levels), cooking, and generally exploring the surrounding area. -
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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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) -
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 four books: Introduction to Applied Linear Algeba: Vectors, Matrices, and Least-Squares (with Lieven Vandenberghe, 2018), 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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Leticia Britos Cavagnaro
Adjunct Professor, Hasso Plattner Institute of Design
BioLeticia Britos Cavagnaro, Ph.D., is co-Director of the University Innovation Fellows, a program of the Hasso Plattner Institute of Design (d.school), which empowers students to be co-designers of their education, in collaboration with faculty and leaders at their schools. Leticia was Deputy Director of the National Center for Engineering Pathways to Innovation (Epicenter), an NSF-funded initiative that operated from 2011 to 2016 to foster innovation and entrepreneurship in engineering education nationwide. She is an adjunct professor at the d.school, where she teaches Stanford students of all disciplines how to build their creative confidence to become engines of innovation in teams and organizations. Leticia has a Ph.D. in Developmental Biology from Stanford's School of Medicine, and is a former member of the Research in Education & Design Lab (REDlab) at Stanford’s School of Education. Having witnessed the journey of students who are transformed by their experience at the d.school, bringing design thinking to more people beyond Stanford has become a priority for Leticia, and she has worked with hundreds of educators and students of all ages, as well as corporate and non-profit leaders in the US and abroad. In the Summer of 2013, Leticia engaged thousands of people from over 130 countries in learning design thinking and applying the methodology to innovate in their contexts, via an experiential MOOC (http://novoed.com/designthinking).
Find out more about Leticia's work at:
http://universityinnovationfellows.org
http://epicenter.stanford.edu
http://teachingcommons.stanford.edu/teaching-talk/design-thinking-action-lab-1
Connect with Leticia:
LinkedIn: linkedin.com/pub/leticia-britos-cavagnaro/9/b4a/752/
Twitter: @LeticiaBritosC (twitter.com/leticiabritosc) -
Carlos Bustamante
Professor of Biomedical Data Science, of Genetics and, by courtesy, of Biology
Current Research and Scholarly InterestsMy genetics research focuses on analyzing genome wide patterns of variation within and between species to address fundamental questions in biology, anthropology, and medicine. We focus on novel methods development for complex disease genetics and risk prediction in multi-ethnic settings. I am also interested in clinical data science and development of new diagnostics.I am also interested in disruptive innovation for healthcare including modeling long-term risk shifts and novel payment models.
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Leopold Cambier
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2015
Current Research and Scholarly InterestsFast Sparse Linear Solvers
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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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Carissa Carter
Adjunct Professor, Hasso Plattner Institute of Design
BioCarissa Carter is the Director of Teaching + Learning at the Stanford d.school. In this role she guides the development of the d.school’s pedagogy, leads its instructors, and shapes its class offering. She teaches courses on the intersection of data and design, design for climate change, and maps and the visual sorting of information.
