Systems Optimization Laboratory
Stanford, CA 943054121 USA

SOL PhD Dissertations
Thesis thoughts:
LaTeX resources:
The following systems allow asynchronous writing of LaTeX documents
from multiple machines. Often this is for coauthors to collaborate (without
sending zip files back and forth). For your thesis, they allow you
to write at your university desk or your laptop at home.
Pretty soon you'll find that they are ideal for writing the papers
associated with your thesis research.
Stanford thesis format:
 Jul 2016: Start your thesis with these lines:
\documentclass[10pt]{report}
\usepackage{suthesis2e}
\usepackage[total={5.5in,8.5in}, top=1.25in, left=1.5in]{geometry}
\setstretch{1.0}
Line 1 recognizes that 10pt is big enough and saves paper.
Line 2 uses years of evolving macros.
Line 3 gives 1.5in margins left and right (good for binding and PDF viewing).
Line 4 gives single spacing.
Further details here:
suthesis2e.sty home page and here:
https://registrar.stanford.edu/students/dissertationandthesissubmission/preparingdissertationselectronicsubmission/format#spacing
but note that the above green lines override some of the specifications there.

Mar 2015: Success at last! Santiago Akle's thesis was
submitted in 10pt with single spacing (\setstretch{1.0}). Thesis formatting
at Stanford is now checked only by the Primary Adviser (who takes
tacit responsibility when pressing the "Accept" button following
online submission). We can now bypass some of the archaic specifications
of ProQuest Dissertation Publishing (Ann Arbor), who have been catering to
the needs of microfiche storage(!).

Aug 2014 (revised Aug 2016): Stanford Thesis style file from Emma Pease, CSLI:
suthesis2e.sty home page.
The example begins with \documentclass[12pt]{report}, and suthesis2e.sty
specifies \setstretch{1.3}.
We strongly recommend [10pt] and \setstretch{1.0} on the grounds that
nobody needs to maximize the length of their thesis.
We hope that the Registrar will officially allow \setstretch{1.0} (single spacing) before too much longer, like most books and journals and technical papers that we read every day.

Aug 2014: Unofficial help from Stanford students:
Thesis and Dissertation Help Center.

Nov 2007: Example LaTeX driver from Felix Kwok:
felixthesisexample.tex.
To save trees, it uses 10pt, twoside, and \setstretch{1.213},
as permitted by the Registrar.
Update (June 2011): Emma Pease now has \setstretch{1.3} in suthesis2e.sty,
but \setstretch{1.213} still seems enough.

Dec 2004: Earlier example LaTeX driver from Michael Friedlander:
mpfthesisexample.tex.
Here's what it looks like (19 short pages):
mpfthesisexample.pdf.
This is where \setstretch{1.213} began.
pdflatex seems the best way to go nowadays.
Figures can include pdf, png, or jpg files.
Some earlier help for making readable ps and pdf files is here:
readme.txt.
Portable PDF files:

The following Unix or Linux command makes a PDF file truly portable
by embedding all necessary fonts within the file:
ps2pdf dPDFSETTINGS=/prepress thesis.pdf thesis_font_embed.pdf
A sidebenefit is that the file size shrinks!
(Thanks to David Fong for finding this command.)
Completed dissertations:
 Ding Ma (MS&E).
Essays in Marketing, Economics, and Optimization.
PhD thesis, Stanford University, December 2018.
 Xiaotong Suo (ICME).
Topics in HighDimensional Statistical Learning.
PhD thesis, Stanford University, June 2018.
 Umnouy (Tee) Ponsukcharoen (ICME).
Impact of Distributed PV Generation on Grid Operation.
PhD thesis, Stanford University, January 2017.
 Jiyan Yang (ICME).
Randomized Linear Algebra for LargeScale Data Applications.
PhD thesis, Stanford University, August 2016.
 Yuekai Sun (ICME).
Regularization in HighDimensional Statistics.
PhD thesis, Stanford University, June 2015.
 Santiago Akle Serrano (ICME).
Algorithms for Unsymmetric Cone Optimization
and an Implementation for Problems with the Exponential Cone.
PhD thesis, Stanford University, March 2015.
 Tomas Tinoco De Rubira (EE).
Numerical Optimization and Modeling Techniques for
Power System Operations and Planning.
PhD thesis, Stanford University, March 2015.
 Xiangrui Meng (ICME).
Randomized Algorithms for Largescale Strongly
Overdetermined Linear Regression Problems.
PhD thesis, Stanford University, June 2014.
 Arwen Meister (ICME).
Learning and Prediction with Dynamical System Models of Gene Regulation.
PhD thesis, Stanford University, November 2013.
 Youngsoo Choi (ICME).
Simultaneous Analysis and Design in
PDEConstrained Optimization.
PhD thesis, Stanford University, December 2012.
 Nicholas Henderson (ICME).
Arc Search Methods
for Linearly Constrained Optimization.
PhD thesis, Stanford University, June 2012.
 Nicole Taheri (ICME).
Linear Optimization Methods
for Vehicle Energy and Communication Networks.
PhD thesis, Stanford University, June 2012.
 David Fong (ICME).
MinimumResidual Methods for Sparse LeastSquares Using GolubKahan Bidiagonalization.
PhD thesis, Stanford University, December 2011.
 Howard Shek (ICME).
Statistical and Algorithm Aspects of Optimal Portfolios.
PhD thesis, Stanford University, March 2011.
 Christopher Maes (ICME).
A Regularized Activeset Method
for Sparse Convex Quadratic Programming.
PhD thesis, Stanford University, November 2010.
 Michael Haythorpe (School of Mathematics and Statistics, University of South Australia).
Markov Chain Based Algorithms
for the Hamiltonian Cycle Problem.
PhD thesis, University of South Australia, July 2010.
 Linzhong Deng (ICME).
MultipleRank Updates
to Matrix Factorizations for Nonlinear Analysis and Circuit Design.
PhD thesis, Stanford University, May 2010.
 Andrew Bradley (ICME).
Algorithms for the Equilibration of Matrices and Their Application to LimitedMemory QuasiNewton Methods.
PhD thesis, Stanford University, May 2010.
 David Gleich (ICME).
Models and Algorithms for PageRank Sensitivity.
PhD thesis, Stanford University, September 2009.
 Rene Schaub.
Stochastic Programming Solutions to Supply Chain Management.
PhD thesis, Stanford University, March 2009.
 Kaustuv (SCCM).
IPSOL: An Interior Point Solver for Nonconvex Optimization Problems.
PhD thesis, Stanford University, December 2008.
 Hanh Huynh (SCCM).
A Largescale Quadratic Programming Solver Based on BlockLU Updates of the KKT System.
PhD thesis, Stanford University, September 2008.
 Leo Tenenblat (IMPA).
Iterative Refinements and Zoom: Acceleration and Warmstarting of Interior Point Methods
PhD thesis, IMPA, Rio de Janeiro, Brazil, draft of June 2008.
The Zoom strategy for accelerating and warmstarting interior methods
PhD defense slides, IMPA, Rio de Janeiro, Brazil, July 2008.
 SouCheng Choi (ICME).
Iterative Methods for Singular
Linear Equations and LeastSquares Problems.
PhD thesis, Stanford University, December 2006.
 Samantha Infeld (Aero/Astro).
Optimization of Mission Design for
Constrained Libration Point Space Missions.
PhD thesis, Stanford University, March 2006. (version Dec.16, 2005)
 Holly Jin.
Scalable Sensor Localization Algorithms
for Wireless Sensor Networks.
PhD thesis, University of Toronto
(joint research with Stanford University), November 2005.
M. W. Carter, H. H. Jin, M. A. Saunders, and Y. Ye.
SpaseLoc: An adaptive subproblem algorithm for
scalable wireless sensor network localization,
SIAM J. on Optimization 17(4), 11021128, December 2006.
 Vinayak (Uday) Shanbhag.
Decomposition and Sampling Methods
for Stochastic Equilibrium Problems.
PhD thesis, Stanford University, December 2005.
Winner of 2006 A. W. Tucker Prize awarded by the
Mathematical Programming Society.
 CheLin Su.
Equilibrium Problems with Equilibrium Constraints:
Stationarities, Algorithms, and Applications.
PhD thesis, Stanford University, September 2005.
 Zheng Su (SCCM).
Computational Methods for Least Squares Problems
and Clinical Trials.
PhD thesis, Stanford University, June 2005.
 Alexis Collomb.
Dynamic Asset Allocation by Stochastic Programming Methods.
PhD thesis, Stanford University, December 2004.
 Maureen Doyle.
A Barrier Algorithm for Large Nonlinear Optimization Problems.
PhD thesis, Stanford University, December 2003.
 CarlMagnus Fransson (Visiting Researcher, 20012003).
Optimization Methods for Robust Control,
with Application to Resistive Wall Modes in Tokamaks.
PhD thesis, Dept of Signals and Systems,
Chalmers University of Technology, Goteborg, Sweden, September 2003.
 Byunggyoo Kim.
Numerical Optimization Methods for Image Restoration.
PhD thesis, Stanford University, December 2002.
 Michael P. Friedlander.
A Globally Convergent Linearly Constrained Lagrangian Method
for Nonlinear Optimization.
PhD thesis, Stanford University, August 2002.
 KienMing Ng.
A Continuation Approach for Solving
Nonlinear Optimization Problems with Discrete Variables.
PhD thesis, Stanford University, June 2002.
(ps)
 ChihHung Lin.
A NullSpace PrimalDual Algorithm
for Nonlinear Network Optimization.
PhD thesis, Stanford University, March 2002.
(ps)
 Michael J. O'Sullivan.
New Methods for Dynamic Programming
Over an Infinite Time Horizon.
PhD thesis, Stanford University, Sepetember 2002.
(ps)
 Heiko Pieper.
Algorithms for Mathematical Programs with Equilibrium
Constraints with Applications to Deregulated Electricity Markets.
PhD thesis, Stanford University, June 2001.
(ps)
 Titus F. Dorstenstein.
Constructive and Exchange Algorithms
for the Frequency Assignment Problem.
PhD thesis, Stanford University, June 2001.
 AngelVictor de Miguel.
Two Decomposition Algorithms for
Nonconvex Optimization Problems with Global Variables.
PhD thesis, Stanford University, April 2001.
(ps)
 Marty O'Brien.
Techniques for Incorporating Expected Value Constraints
into Stochastic Programs.
PhD thesis, Stanford University, June 2000.
 Antonino Del Gatto.
A Subspace Method Based on a Differential Equation Approach
to Solve Unconstrained Optimization Problems.
PhD thesis, Stanford University, June 2000.
(ps)
 Aparna Gupta (SCCM).
Optimum Asset Allocation with Behavioral Utilities:
A Plan for Acquiring and Consuming Retirement Funds.
PhD thesis, SCCM, Stanford University, May 2000.
 Meredith J. Goldsmith.
Sequential Quadratic Programming Methods
Based on Indefinite Hessian Approximations.
PhD thesis, Stanford University, March 1999.
(ps)
 Erik Boman (SCCM).
Infeasibility and Negative Curvature in Optimization.
PhD thesis, Stanford University, February 1999.
 William Behrman (SCCM).
An Efficient Gradient Flow Method
for Unconstrained Optimization.
PhD thesis, Stanford University, June 1998.
