Institute for Computational and Mathematical Engineering (ICME)
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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.

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 realtime beamforming algorithms. His current research is developing accurate and spatially resolved speedofsound imaging in tissue based on phase aberration correction, spatial coherence, and computed tomography

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 highfidelity 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 reentry vehicles. He is the author of over 200 technical publications on the topics of computational aircraft and spacecraft design, multidisciplinary optimization, fundamental numerical methods, and highperformance 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 coursedevelopment 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.

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 datascience and its applications to large scale projects such as construction, infrastructure and city management.

Jing An
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2016
BioI am a 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 biology, physics.

David Barmherzig
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2013
BioI am a fourthyear 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.

Poorvi Bhargava
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2016
BioI am currently a student at Stanford University, studying Computational and Mathematical Engineering. Prior to joining Stanford, I studied Biomedical Engineering at the University of Texas at Austin. I hope to combine my interests in data science and design to solve impactful, humancentered, and social problems. My hobbies include art & design and traveling.

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

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
Professor of Geophysics
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 activesource experiments (reflection data), or by faraway earthquakes (teleseismic data). The highresolution and fidelity of 3D reflectionseismic 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 oneday 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); codirector, Stanford Exploration Project (1998present); founding member, Editorial Board of SIAM Journal on Imaging Sciences (2007present); member, SEG Research Committee (1996present); 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 whotofollow 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 PhDlevel 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, CUHKShenzhen, 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 parsersolvers 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 BealeOrchardHays 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.

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.

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.

Leopold Cambier
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2015
Current Research and Scholarly InterestsFast Linear Solver for BEM equations

Emmanuel Candes
BarnumSimons Chair in Math and Statistics, and Professor of Statistics and, by courtesy, of Electrical Engineering
BioEmmanuel Candès is the BarnumSimons 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 earlycareer 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 solidstate 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

Ines Chami
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2016
BioI am a secondyear 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 crossmodal information retrieval (image annotation and automated textillustration). I am currently working on information extraction from semistructured data (pdf tables) within the Hazy Research group led by Prof. Ré at Stanford.

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.

Casey Chu
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2016
Current Research and Scholarly InterestsTheoretical foundations of inference.

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 UH60A/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.

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.

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.

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. 
Eric Dunham
Associate Professor of Geophysics
Current Research and Scholarly InterestsPhysics of natural hazards, specifically earthquakes, tsunamis, and volcanoes. Computational geophysics.

Cooper Elsworth
Ph.D. Student in Geophysics
Masters Student in Computational and Mathematical Engineering, admitted Winter 2018BioCooper Elsworth is a PhD candidate in the Department of Geophysics and MS student in Computational Mathematics & Engineering at Stanford University. As a member of the SIGMA group, his research focuses on the coupled processes governing streaming ice flow in Western Antarctica. Previously, he attended Penn State University, where he completed BS and MS degrees in Engineering Mechanics, focusing on computational methods for fluidstructure interaction. His research interests include coupled systems, fluid dynamics, glaciology and computational mechanics.

Ron Estrin
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2014
BioI am a PhD candidate working on problems in numerical linear algebra and optimization (in particular, nonconvex problems with nonlinear constraints) with my doctoral advisor Michael Saunders, as well as with Michael Friedlander and Dominique Orban. Prior to beginning my PhD, I completed my BSc with a Combined Honours in Mathematics and Computer Science from the University of British Columbia. During my time at UBC I also completed a senior thesis with Chen Greif, studying saddlepoint matrices exhibiting certain special structure.

Philip Etter
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2017
Current Research and Scholarly InterestsI am currently developing a novel approach to reduced basis methods based on numerical linear algebra techniques. Reduced basis methods are model order reduction techniques which can solve large collections of similar PDEs by exploiting sparsity in the underlying solution space. Applications range from the computation of radar crosssections to uncertainty quantification.

Charbel Farhat
Vivian Church Hoff Professor of Aircraft Structures, Professor of Mechanical Engineering and Director of the Army High Performance Computing Research Center
Current Research and Scholarly InterestsCharbel Farhat and his Research Group (FRG) develop mathematical models, advanced computational algorithms, and highperformance software for the design and analysis of complex systems in aerospace, marine, mechanical, and naval engineering. They contribute major advances to SimulationBased Engineering Science. Current engineering foci in research are on the nonlinear aeroelasticity and flight dynamics of Micro Aerial Vehicles (MAVs) with flexible flapping wings and N+3 aircraft with High Aspect Ratio (HAR) wings, layout optimization and additive manufacturing of wing structures, supersonic inflatable aerodynamic decelerators for Mars landing, and underwater acoustics. Current theoretical and computational emphases in research are on highperformance, multiscale modeling for the highfidelity analysis of multiphysics problems, highorder embedded boundary methods, uncertainty quantification, and efficient modelorder reduction for timecritical applications such as design and active control.

Ron Fedkiw
Professor of Computer Science
BioFedkiw's research is focused on the design of new computational algorithms for a variety of applications including computational fluid dynamics, computer graphics, and biomechanics.

Jordi Feliu Faba
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2016
BioI am a PhD student in the Institute for Computational and Mathematical Engineering (ICME). I was born and I received my education in Spain. I received my two Bachelor's degrees in Industrial Technology Engineering and in Civil Engineering at Universitat Politècnica de Catalunya (UPC) in Barcelona. In 2014 I moved for 6 months to France to finish my Bachelor's degree in Civil Engineering at Ecole Centrale de Nantes. Next, I returned to Barcelona to course a MSc in Civil Engineering at UPC and gain work experience in civil engineering. My research interests lie in the area of computational engineering.

Casey Fleeter
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2015
Masters Student in Computational and Mathematical Engineering, admitted Winter 2018BioI am a PhD student at Stanford University's Institute of Computational and Mathematical Engineering (ICME). I graduated from Harvard University in 2015 with a Bachelor of Arts in Physics. My research interests lie in the applications of mathematical methods to the cardiovascular system. My project in the Marsden Lab specifically utilizes techniques in uncertainty quantification.

Oliver Fringer
Associate Professor of Civil and Environmental Engineering
BioFringer's research focuses on the development and application of numerical models and highperformance computational techniques to the study of fundamental processes that influence the dynamics of the coastal ocean, rivers, lakes, and estuaries.

Pengfei Gao
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2014
BioI am a thirdyear PhD candidate in the ICME (Institute for Computational and Mathematical Engineering) at Stanford University. My PhD advisor is Professor Tze Leung Lai. I received my Bachelor’s degree in Mathematics and Physics (2014) from Tsinghua University.
My current research interests is AI applied in quantitative trading. To apply theory in practice, I cofounded a trading firm, Insanity Trading, based in Beijing with alumni from Stanford University, Peking University and Tsinghua University. With the deep understanding of China market characteristics, we integrate modern statistical theories, cuttingedge AI algorithms and sophisticated optimization methods into our trading strategies, hence consistently achieve exceptional returns with minimum influence from market conditions.
If you want to implement your strategies in Chinese markets, or need supports in developing trading ideas, please feel free to contact us. 
Guillaume Genthial
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2016
BioI am currently enrolled in my second year as a master's student in Computational and Mathematical Engineering in the Data Science track, where I develop strong computational and programming skills.
I also have a masters' degree in Applied Mathematics from the Ecole polytechnique, the France's top university for science and engineering, where I also studied computer science, quantum and statistical physics.
I have solid research experience in Natural Language Processing and Deep Learning as well as teaching experience in Natural Language Processing and Reinforcement Learning.
I am passionate about new computational techniques, especially AI and DL, that make new discoveries and applications possible.
You can check my personal blog at https://guillaumegenthial.github.io 
Margot Gerritsen
Senior Associate Dean for Educational Initiatives, Professor of Energy Resources Engineering, Senior Fellow at the Precourt Institute for Energy and Professor, by courtesy, of Civil and Environmental Engineering
Current Research and Scholarly InterestsResearch
My work is about understanding and simulating complicated fluid flow problems. My research focuses on the design of highly accurate and efficient parallel computational methods to predict the performance of enhanced oil recovery methods. I'm particularly interested in gas injection and insitu combustion processes. These recovery methods are extremely challenging to simulate because of the very strong nonlinearities in the governing equations. Outside petroleum engineering, I'm active in coastal ocean simulation with colleagues from the Department of Civil and Environmental Engineering, yacht research and pterosaur flight mechanics with colleagues from the Department of Mechanical and Aeronautical Engineering, and the design of search algorithms in collaboration with the Library of Congress and colleagues from the Institute of Computational and Mathematical Engineering.
Teaching
I teach courses in both energy related topics (reservoir simulation, energy, and the environment) in my department, and mathematics for engineers through the Institute of Computational and Mathematical Engineering (ICME). I also initiated two courses in professional development in our department (presentation skills and teaching assistant training), and a consulting course for graduate students in ICME, which offers expertise in computational methods to the Stanford community and selected industries.
Professional Activities
Senior Associate Dean, School of Earth, Energy and Environmental Sciences, Stanford (from 2015); Director, Institute for Computational and Mathematical Engineering, Stanford (from 2010); Stanford Fellow (20102012); Magne Espedal Professor II, Bergen University (20112014); Aldo Leopold Fellow (2009); Chair, SIAM Activity group in Geosciences (2007, present, reelected in 2009); Faculty Research Fellow, Clayman Institute (2008); Elected to Council of Society of Industrial and Applied Mathematics (SIAM) (2007); organizing committee, 2008 Gordon Conference on Flow in Porous Media; producer, Smart Energy podcast channel; Director, Stanford Yacht Research; Codirector and founder, Stanford Center of Excellence for Computational Algorithms in Digital Stewardship; Editor, Journal of Small Craft Technology; Associate editor, Transport in Porous Media; Reviewer for various journals and organizations including SPE, DoE, NSF, Journal of Computational Physics, Journal of Scientific Computing, Transport in Porous Media, Computational Geosciences; member, SIAM, SPE, KIVI, AGU, and APS 
Kay Giesecke
Associate Professor of Management Science and Engineering
Current Research and Scholarly InterestsKay is a financial engineer. He develops stochastic financial models, designs statistical methods for analyzing financial data, examines simulation and other numerical algorithms for solving the associated computational problems, and performs empirical analyses. Much of Kay's work is driven by important applications in areas such as credit risk management, investment management, and, most recently, housing finance.

Peter Glynn
Thomas W. Ford Professor in the School of Engineering and Professor, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsStochastic modeling; statistics; simulation; finance

Abeynaya Gnanasekaran
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2016
BioI am a first year PhD student in the Institute for Computational and Mathematical engineering at Stanford University. My research interests broadly lie in the applications of mathematics and simulations to study problems in engineering and biology. I have a bachelors degree (with Honours) in Chemical engineering from Indian Institute of Technology Madras, India. My undergraduate research was in the area of Computational Microfluidics. Also I did a summer research internship in Process Control at EPFL, Switzerland.
I was born and brought up in Neyveli, an industrial town in south India. I enjoy listening to Indian music and reading novels. 
Ashish Goel
Professor of Management Science and Engineering and, by courtesy, of Computer Science
BioAshish Goel is a Professor of Management Science and Engineering and (by courtesy) Computer Science at Stanford University. He received his PhD in Computer Science from Stanford in 1999, and was an Assistant Professor of Computer Science at the University of Southern California from 1999 to 2002. His research interests lie in the design, analysis, and applications of algorithms.

Leonidas Guibas
Paul Pigott Professor in the School of Engineering and Professor, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsShape and motion representations and algorithms for biological structures

Noam Habot
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2016
Stanford Student Employee, Law Instructional SupportBioI am a second year Master's student in the Data Science Track of ICME. I am currently seeking a data science / machine learning fulltime position upon my graduation from the Data Science Track of ICME program in end of March, 2018. For my 2017 summer internship, I worked as an Applied Machine Learning intern at Apple, focusing on optimizing search on the apple.com website. I previously worked as a Software Engineering Intern for Qualcomm in San Diego, summers (’14 and ’15), building internal tools to automate processes and improve efficiency. Before attending Stanford, I completed my undergraduate studies at UCLA, majoring in Applied Mathematics and in Statistics.

Alexander Haigh
Masters Student in Computational and Mathematical Engineering, admitted Spring 2017
BioAlex was born in Boston and attended Belmont Hill School before arriving at Stanford in September, 2014. As an undergraduate, he majored in Computer Science concentrating in AI, and, outside of his own coursework, was a Teaching Assistant for CS106A, the Vice President of his fraternity, and the captain of the men's lacrosse team. As he progressed through his CS major, Alex found that he was increasingly attracted to the mathematical side of his coursework and decided to pursue a Master's Degree in Computational and Mathematical Engineering. After graduation, Alex is interested in building consumer products that leverage AI to provide a better user experience.

Pat Hanrahan
Canon USA Professor in the School of Engineering and Professor of Electrical Engineering
BioProfessor Hanrahan's current research involves rendering algorithms, high performance graphics architectures, and systems support for graphical interaction. He also has worked on raster graphics systems, computer animation and modeling and scientific visualization, in particular, volume rendering.

Jerry Harris
The Cecil H. and Ida M. Green Professor in Geophysics
Current Research and Scholarly InterestsBiographical Information
Jerry M. Harris is the Cecil and Ida Green Professor of Geophysics and Associate Dean for the Office of Multicultural Affairs. He joined Stanford in 1988 following 11 years in private industry. He served five years as Geophysics department chair, was the Founding Director of the Stanford Center for Computational Earth and Environmental Science (CEES), and colaunched Stanford's Global Climate and Energy Project (GCEP). Graduates from Jerry's research group, the Stanford Wave Physics Lab, work in private industry, government labs, and universities.
Research
My research interests address the physics and dynamics of seismic and electromagnetic waves in complex media. My approach to these problems includes theory, numerical simulation, laboratory methods, and the analysis of field data. My group, collectively known as the Stanford Wave Physics Laboratory, specializes on high frequency borehole methods and low frequency labratory methods. We apply this research to the characterization and monitoring of petroleum and CO2 storage reservoirs.
Teaching
I teach courses on waves phenomena for borehole geophysics and tomography. I recently introduced and cotaught a new course on computational geosciences.
Professional Activities
I was the First Vice President of the Society of Exploration Geophysicists in 200304, and have served as the Distinguished Lecturer for the SPE, SEG, and AAPG. 
Trevor Hastie
John A. Overdeck Professor, Professor of Statistics and of Biomedical Data Sciences
Current Research and Scholarly InterestsFlexible statistical modelling, datamining, bioinformatics, and statistical computing.

Suraj Heereguppe Radhakrishna
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2016
BioI am a master's student at ICME, with a passion for all the various ways data science may be applied in areas that have the potential to impact society in insightful ways.
Music is a big part of my life, having played the violin for around 15 years. I am also a part of Raagapella, a South Asian A Capella group at Stanford. If you run into me randomly and happen to hear me humming and lost in the tune, don't worry that's what I'm usually doing when not interacting with anyone. 
Gianluca Iaccarino
Professor of Mechanical Engineering
BioIaccarino's research themes include numerical methods for fluid mechanics, physical models for laminar/turbulent flows, and uncertainty quantification in computational science.

Alex Infanger
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 graduated with a BS in physics with highest honors from UC Santa Cruz, where I developed search algorithms and used statistical methods to show the existence of ultra bright Terrestrial Gammaray Flashes using data from the Reuven Ramaty High Energy Solar Spectroscopic Imager.

Arun Jambulapati
Ph.D. Student in Computational and Mathematical Engineering, admitted Spring 2016
Current Research and Scholarly InterestsI am interested in discrete mathematics and graph theory, especially in applications of combinatorics to Big Data.

Doug James
Professor of Computer Science and, by courtesy, of Music
Current Research and Scholarly InterestsComputer graphics & animation, physicsbased sound synthesis, computational physics, haptics, reducedorder modeling

Antony Jameson
Professor (Research) of Aeronautics and Astronautics, Emeritus
BioProfessor Jameson's research focuses on the numerical solution of partial differential equations with applications to subsonic, transonic, and supersonic flow past complex configurations, as well as aerodynamic shape optimization.

Ramesh Johari
Associate Professor of Management Science and Engineering and, by courtesy, of Computer Science and of Electrical Engineering
BioJohari is interested in the design and management of largescale complex networks, such as the Internet. Using tools from operations research, engineering, and economics, he has developed models to analyze efficient market mechanisms for resource allocation in networks.

Indraneel Gireendra Kasmalkar
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2015
Masters Student in Computational and Mathematical Engineering, admitted Spring 2017Current Research and Scholarly InterestsWe are currently limited in our understanding of what drives fast ice flow in Antarctica. I study water systems at the interface of the ice and the underlying bed and their coupled dynamics with ice and sediment. My goal is to understand how subglacial meltwater facilitates fast flow.

Ramtin Keramati
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2015
Current Research and Scholarly InterestsReinforcement Learning, Deep Learning, Human in the Loop Reinforcement Learning

Peter K. Kitanidis
Professor of Civil and Environmental Engineering
BioKitanidis develops methods for the solution of interpolation and inverse problems utilizing observations and mathematical models of flow and transport. He studies dilution and mixing of soluble substances in heterogeneous geologic formations, issues of scale in mass transport in heterogeneous porous media, and techniques to speed up the decay of pollutants in situ. He also develops methods for hydrologic forecasting and the optimization of sampling and control strategies.

Allison Koenecke
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2016
BioI am a PhD student in the Institute for Computational and Mathematical Engineering (ICME). Prior to joining the Stanford community, I worked at NERA Economic Consulting in New York, where I specialized in data work with applications to antitrust litigation and mergers. I am originally from the DC area and received my Bachelor's in Mathematics with Computer Science from MIT. Previous internships include data science roles at Facebook and Google.