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Dissertation

Once the coursework and field papers are completed, students proceed to the dissertation stage. The first step is to delineate an original research project in a dissertation prospectus. Presented to a faculty examining committee, the prospectus provides the principal basis for discussion during the qualifying oral examination which advances the student to PhD. candidacy. Sometimes the dissertation emerges directly from earlier field papers; but students often extend themselves in unexpected directions as they open new avenues of discovery. Either way, we take it as our obligation to try to provide constructive guidance without usurping the student’s intellectual autonomy. In the usual course of things, we expect students to complete their graduate training in five to seven years.

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  • UCLA Dissertations and Theses in print (archives) UCLA masters theses and doctoral dissertations, written from 1934-1972. These are non-circulating and must be requested in Library Special Collections.
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  • UCLA Previously Published Works

Cover page of Optimization-based Planning and Control for Robust and Dexterous Locomotion and Manipulation through Contact

Optimization-based Planning and Control for Robust and Dexterous Locomotion and Manipulation through Contact

  • Shirai, Yuki
  • Advisor(s): Hong, Dennis W.

Although robotic locomotion and manipulation have shown some remarkable progress in the real world, the current locomotion and manipulation algorithms are inefficient in performance. They often only work for relatively simple tasks such as walking and running for locomotion and pick-and-place in structured environments (e.g., factory) for manipulation. In contrast, humans can perform quite dexterous tasks through contact as contacts provide additional dexterity to interact with environments. Hence, understanding the underlying contact mechanics plays a key role in designing contact-aware planners, controllers, and estimators for locomotion and manipulation.

However, design for planners, controllers, and estimators is extremely challenging. First, the number of contact states such as making and breaking contact with environments increases dramatically as the number of contacts increases. Thus, the underlying contact dynamics become large-scale non-smooth dynamics. As a result, optimization solvers have difficulties converging due to the non-convexity of the optimization problem.

Second, it is desirable that a robot should be able to interact in unknown environments during operation, leading to generalizable locomotion and manipulation. However, robust planning with frictional interaction with uncertain physical properties is very tough as the robot might cause undesired unexpected contact events. As a result, a robot might not be able to complete its desired task.

Third, once uncertainty is quite large, it is indispensable for closed-loop controllers to stabilize locomotion and manipulation. However, the design of manipulation is quite challenging as most manipulation systems are underactuated and unobservable with potential changes in contact states and modes.

In this dissertation, we present a methodology for contact-rich locomotion and planning using trajectory optimization. We first show that the planner using graph-search planners with trajectory optimization can be beneficial for decreasing the computation complexity. Second, we describe our contact-implicit trajectory optimization for planning of multi-limbed systems for running and climbing. We use decomposition-based optimization techniques to efficiently design a trajectory for a robot subject to various complicated contact constraints such as mixed-integer constraints. Then, we present our robust and stochastic trajectory optimization algorithms for multi-contact systems. We show that our chance-constrained optimization is applicable for planning multi-limbed robots. We also propose covariance steering algorithm for contact-rich systems using a particle filter to approximate a distribution of underlying contact dynamics. Our covariance steering is able to regulate robots' states and contact states simultaneously with probabilistic guarantees. Furthermore, utilizing the underlying structure of contact-rich manipulation, we present robust bilevel trajectory optimization for pivoting manipulation under uncertain physical parameters such as friction coefficients. Our proposed framework is able to design optimal control sequences while improving the worst-case stability margin along the manipulation. Finally, we present our closed-loop controller framework for tool manipulation using visuo-tactile feedback. Our approach enables the robot to achieve tool manipulation under unexpected contact events in closed-loop control fashion with no visual feedback for partially unknown objects.

The perspectives gained from this dissertation provide better insight into developing a contact-rich planning, estimation, and control framework for dexterous locomotion and manipulation in highly unstructured environments.

Cover page of Energetic Electron Losses Driven by Whistler-Mode Waves in the Inner Magnetosphere: ELFIN observations and theoretical models

Energetic Electron Losses Driven by Whistler-Mode Waves in the Inner Magnetosphere: ELFIN observations and theoretical models

  • Tsai, Ethan
  • Advisor(s): Angelopoulos, Vassilis

Resonant interactions between energetic radiation belt electrons and equatorially-generated whistler-mode waves are widely studied because they yield either electron acceleration or precipitation -- where electrons are scattered and lost into the Earth's atmosphere -- both of which are fundamental to space weather forecasting, which is an increasingly relevant challenge as society scales up its reliance on space technologies. This dissertation investigates the mechanisms that govern the effectiveness of electron losses from Earth's radiation belts driven by whistler-mode waves using novel electron precipitation measurements from the ELFIN CubeSats. A culmination of innovative engineering efforts and a refactored satellite operations program has allowed ELFIN to obtain over 12,500 high-quality, low-altitude electron measurements of the radiation belts. These measurements are uniquely capable of resolving the bounce loss cone, allowing us to probe the physics that drive electron precipitation in great detail. We first present a test particle simulation that directly compares ELFIN-measured electron precipitation with equatorial electron and wave measurements by the THEMIS and MMS spacecraft during magnetic conjunctions, confirming the importance of mid-high latitude wave-power. Next, we demonstrate that test particle simulations combined with an empirical wave amplitude model adequately approximate statistical ELFIN observations at the dawn, day, and dusk MLT sectors, but they significantly underestimate relativistic (>500$keV) electron losses on the nightside. To resolve this discrepancy, we additionally use quasi-linear diffusion simulation methods to find that considering wave obliquity, wave frequency, and plasma density together are required to recover the energetic portion (>100 keV) of precipitating electron spectra without overestimating the loss contributions from the quasi-linear regime (~100 keV). We conclude by presenting the ranges of wave and plasma characteristics necessary for the incorporation of accurately modeled electron loss rates into modern radiation belt models. This unlocks the potential to remotely sense equatorial wave properties using electron precipitation measurements, but also calls for future \textit{in situ} satellite experiments to more deeply understand the interconnected role of energetic electron losses in atmospheric, ionospheric, and magnetospheric dynamics.

Cover page of Data-Driven Modeling and Control of Extreme Aerodynamic Flows: Super Resolution, Manifold Identification, and Phase-Amplitude Reduction

Data-Driven Modeling and Control of Extreme Aerodynamic Flows: Super Resolution, Manifold Identification, and Phase-Amplitude Reduction

  • Fukami, Kai
  • Advisor(s): Taira, Kunihiko

In this thesis, we develop data-driven techniques to analyze unsteady aerodynamic flows under extremely gusty conditions for global field reconstruction, low-order modeling, and control. We first consider global field reconstruction from sparse sensors through the lens of generalized super-resolution analysis. This thesis offers a survey with comprehensive case studies of machine-learning-based super resolution for turbulent flows. Supervised machine-learning-based sparse reconstruction is then performed with vortical flows in a pump sump, an example of industrial turbulence. In addition, we establish a robust sparse reconstruction technique for situations in which the numbers and positions of sensors are changing over time, referred to as a Voronoi- tessellation-assisted convolutional neural network. We demonstrate its performance and robustness against noisy sensor measurements with a range of fluid flow examples. Defining interpolation and extrapolation conditions of machine-learning-based studies in unsteady flows is challenging due to their high-dimensionality and scale-invariant nature. For this reason, we consider nonlinear data-driven scaling of turbulent flows to reveal scale-invariant vortical structures across Reynolds numbers. This nonlinear scaling provides insights for supporting machine-learning-based studies of turbulent flows.To perform flow control leveraging the reconstructed fields from sparse sensors, we then consider constructing a control strategy of flows in a low-order subspace identified by nonlinear machine-learning-based data compression. We develop a nonlinear observable-augmented autoencoder that can incorporate physical observables in identifying a low-dimensional latent manifold. This thesis considers extreme vortex-gust airfoil interactions occurring when modern small aircraft fly in severe atmospheric conditions. Under such extreme aerodynamic situations, wings experience massive separation while exhibiting sharp and highly unsteady aerodynamic force responses. Although it is challenging to analyze the nonlinear, transient nature of extreme aerodynamics with conventional linear techniques, we reveal that the underlying physics of a collection of time-varying vortical flows in a high-dimensional space can be expressed on a low-rank manifold leveraging the present data-driven compression. It is also demonstrated that efficient control strategies can be derived at a minimal cost with the assistance of phase-amplitude reduction on the discovered manifold. These developed data-driven strategies offer a new perspective on reconstructing, modeling, and controlling a range of extremely unsteady flows.

Cover page of Concrete’s Strength Prediction using Machine Learning Method

Concrete’s Strength Prediction using Machine Learning Method

  • Ouyang, Boya
  • Advisor(s): Sant, Gaurav

In this study, I present a comprehensive study that addresses the complex challenge of predicting concrete strength, leveraging the power of advanced machine learning techniques. Recognizing the limitations of traditional prediction models, I have introduced innovative methodologies to enhance accuracy and interpretability in this crucial aspect of construction.

Central to my approach is the development of the Ensemble-Based Outlier Detection (EBOD) algorithm. Recognizing the detrimental impact of noisy data on model performance, I designed EBOD to integrate multiple detection algorithms, thereby significantly reducing the bias associated with single-algorithm methods. This innovation ensures that the datasets used for model training and analysis are of the highest quality, laying a solid foundation for more accurate predictive modeling.

Moving forward, I explored the capabilities of Gaussian Process Regression (GPR) in predicting concrete strength. My work with GPR is not just about prediction; it's about understanding the intricacies of the data. I optimized the GPR model to not only forecast concrete strength with remarkable accuracy but also to quantify the uncertainties associated with these predictions. This dual capability of the GPR model enriches the interpretability of the results, providing deeper insights that are invaluable for material engineering and construction management.

In my pursuit of transparency and interpretability in predictive modeling, I introduced symbolic regression into the study. I recognized the need for models that not only predict but also explain. Symbolic regression offered a solution, enabling me to construct interpretable models that shed light on the underlying physical phenomena governing concrete strength. To enhance the predictive power of these models, I incorporated advanced data augmentation techniques, such as the Synthetic Minority Over-sampling Technique (SMOTE), pushing the boundaries of prediction and understanding in unexplored domains.

A pivotal aspect of my study involved a meticulous analysis of the balance between data volume and the precision of machine learning models. I undertook a comprehensive evaluation of a vast dataset, assessing the performance of various algorithms in predicting concrete strength. This rigorous analysis highlights my commitment to not only advancing the accuracy of predictive models but also to understanding the practical challenges and limitations of employing machine learning in the field of concrete strength prediction.

Through the development of innovative algorithms, the application of advanced machine learning techniques, and a thorough analysis of extensive datasets, I aim to revolutionize the way we predict, understand, and apply concrete strength models in industrial applications, setting new benchmarks for accuracy and interpretability.

Cover page of Novel Implicit Discretization and Solutions for Elastic Solids and Fluids

Novel Implicit Discretization and Solutions for Elastic Solids and Fluids

  • Chen, Jingyu
  • Advisor(s): Teran, Joseph M ;
  • Kavehpour, Pirouz

Physics-based simulations are a powerful tool in both computer graphics and engineering applications. Implicit discretization is essential for accurate, stable, and efficient simulations of solids and fluids.

In this thesis, we first present a novel implicit Material Point Method (MPM) discretization of spatially varying surface energies. Our discretization is based on surface energy, enabling implicit time stepping and capturing surface gradients without explicitly resolving them as in traction-condition-based approaches. We include an implicit discretization of thermomechanical material coupling with novel particle-based enforcement of Robin boundary conditions. Lastly, we design a particle resampling approach for perfect conservations of linear and angular momentum with Affine-Particle-In-Cell (APIC) [Jiang et al. 2015].

The second part presents a novel deep-learning approach to approximate the solution of large, sparse, symmetric, positive-definite linear systems of equations. Our method is motivated by the conjugate gradients algorithm that iteratively selects search directions for minimizing the matrix norm of the approximation error. We use a deep neural network to accelerate convergence via data-driven improvement of the search direction at each iteration. We demonstrate the efficacy of our approach on discretized Poisson equations with millions of degrees of freedom. Our algorithm can reduce the linear system residual to the target tolerance in a small number of iterations, independent of the problem size, and generalize effectively to various systems beyond those encountered during training.

Finally, we present improvements to Position Based Dynamics (PBD) [Müller et al. 2007] and Extended Position Based Dynamics (XPBD) [Macklin et al. 2016] methods, which are variants of implicit time integrator. PBD/XPBD are powerful methods for the real-time simulation of elastic objects, but they do not always converge. We isolate the root cause in the approximate linearization of the nonlinear backward Euler systems utilized by XPBD. We provide two extensions to XPBD to address the non-convergence and support general hyperelastic models. The following chapter presents a novel position-based nonlinear Gauss-Seidel approach for quasistatic simulations of elastic objects. This approach retains the essential PBD feature of stable behavior with limited computational budgets and allows for convergent behavior when the budgets expand.

Cover page of Seismic Risk Assessment of Spatially Distributed Levee System in the Sacramento-San Joaquin Delta

Seismic Risk Assessment of Spatially Distributed Levee System in the Sacramento-San Joaquin Delta

  • Advisor(s): Brandenberg, Scott

The approximately 1,100 miles of levees in the Sacramento-San Joaquin Delta is critical to aquatic and terrestrial habitat, agriculture, California’s water supply and distribution system, and other infrastructure investments, and the levee system protects them from flooding and salt water intrusion. However, the levee system is threatened by a variety of hazards. Land due to oxidation of the rich Delta peat soils, and due to sea level risk act together to effectively increase the levee hydraulic loading. Consolidation of peat soils beneath levees can lead to their continued settlement over time. Delta levees are also threatened by potential sudden shocks from floods events and earthquakes. Numerous advances with greater proliferation and more sophisticated methods of risk assessments have been made since the most recent risk study of the Delta was completed. Therefore, assessing multi-hazard risks of the Delta levee system by leveraging newly available data and knowledge is of great importance for decision makers to implement improvements in response to those long-term and short-term stressors.This study primarily focuses on seismic risk assessment of Bacon Island in the central Delta. The seismic capacity, demand, spatial correlations of levee systems, and system reliability analysis are four essential components throughout the seismic risk assessment. Newly available LiDAR, bathymetry data, geotechnical site investigation results, and measurements from advanced geophysical tests significantly facilitate determining geometry, soil stratigraphy/layering, and soil property of levees. Consequently, the levee fragility functions which reflect the system seismic capacity are developed from a large number of time-series nonlinear finite element simulations using OpenSees. An overview of updated probabilistic seismic hazard analysis results for the Delta region is discussed. Moreover, an algorithm for selecting a subset of events for hazard-consistent analysis of spatially distributed infrastructures is introduced, and performed to analyze the regional probabilistic seismic hazard analysis of the Bacon Island levee system, which quantifies seismic demand of the levees. The correlation functions of capacity are derived based on field geophysical measurements and geo-statistics analysis. Furthermore, the system reliability analysis using level crossing statistics method is implemented to assess seismic risk for Bacon Island levees based on the developed levee fragility, correlation lengths, and selected event subset.

Cover page of Uncertainty, portability and ancestry in polygenic scoring

Uncertainty, portability and ancestry in polygenic scoring

  • Advisor(s): Pasaniuc, Bogdan

Polygenic score (PGS) is a tool for understanding an individual's predisposition to certain diseases or complex traits based on its genetic profile. In the burgeoning era of genomic medicine, PGS has emerged as a promising tool in advancing precision healthcare, demonstrating versatile utility such as patient risk stratification, disease risk prediction, and disease subtyping. However, its real application in clinical settings is limited by its uncertainty, bias, and low portability across diverse populations. For example, an individual may receive different genetic risk reports from different providers, and the score for a non-European individual may be less accurate than for a European individual. To fully understand and partially address these limitations, I first developed a Bayesian method to quantify the uncertainty in PGS at the individual level. I find trait-specific genetic architecture such as larger polygenicity and lower heritability combined with a small training sample size will lead to large uncertainty in PGS estimate, which in turn results in unreliable patient stratification in downstream analysis. Next, I expanded this approach to encompass individuals from varied genetic ancestry backgrounds. I find that the PGS performance varied from individual to individual with genetic distance playing a key role in impacting the performance of PGS; larger genetic distance from training data correlates with higher uncertainty and lower accuracy in testing individuals. These findings highlight the necessity of integrating individual-level PGS metrics in personalized medicine and the need for increasing genetic research diversity to ensure equitable and responsible use of PGS in clinical settings.

Enhancing Tumor-Infiltrating T cells with an Exclusive Fuel Source

  • Miller, Matthew Lawrence
  • Advisor(s): Butte, Manish J

Solid tumors harbor immunosuppressive microenvironments that inhibit tumor-infiltrating lymphocytes (TILs) through the voracious consumption of glucose. We sought to restore TIL function by providing them with an exclusive fuel source. The glucose disaccharide cellobiose, which is a building block of cellulose, contains a β-1,4-glycosidic bond that cannot be hydrolyzed by animals (or their tumors), but fungal and bacterial organisms have evolved enzymes to catabolize cellobiose and use the resulting glucose. By equipping T cells with two proteins that enable import and hydrolysis of cellobiose, we demonstrate that supplementation of cellobiose during glucose withdrawal restores T cell cytokine production and cellular proliferation. Murine tumor growth is suppressed, and survival is prolonged. Offering exclusive access to a natural disaccharide is a new tool that augments cancer immunotherapies. Beyond cancer, this approach could be used to answer questions about the regulation of glucose metabolism across many cell types, biological processes, and diseases.

Cover page of Cooperative Channel Sensing, Relaying and Computing in UAV and Vehicular Networks

Cooperative Channel Sensing, Relaying and Computing in UAV and Vehicular Networks

  • Krijestorac, Enes
  • Advisor(s): Cabric, Danijela

Mobile devices generate an enormous amount of data traffic to satisfy their computing and communications needs. To meet these demands, mobile network operators frequently need to expand their capacity, which entails significant capital costs and increased energy consumption. Motivated by this, we seek to develop cooperative systems that will bring higher communications speeds and larger computing power to mobile devices without relying on mobile network infrastructure.

In recent years, unmanned aerial vehicle (UAV) technology has garnered interest for its potential use as a communications enabler. Swarms of UAVs can be deployed as temporary relays to meet short term but high intensity communication demands from mobile users. UAV swarms can coordinate their placement to improve the capacity on the fronthaul link between users and UAVs. Algorithms for optimal placement often rely on the knowledge of channel gain across space. Hence, we developed deep learning methods for channel gain prediction across space based on measurements collected by the UAVs and 3D maps of the environment. In line with this, we also developed methods to design UAV flying paths for optimal measurement collection such that the accuracy of channel gain prediction is maximized under constraints on the distance traveled by the UAVs. Additionally, we develop a reinforcement-learning based approach that controls a UAV to directly improve the fronthaul link without relying on channel gain knowledge across space.

With the proliferation of intelligent vehicles, there is an increasing number of computationally demanding computer applications appearing in vehicular environments. Providing the computational resources to meet the demands of such applications is a critical problem. In this work, we consider a cooperative computing paradigm between intelligent vehicles of similar computing power to enable emerging vehicular applications. Vehicles cooperate with each other over vehicle-to-vehicle networks to form vehicular micro clouds that can complete computationally intensive tasks without relying on cloud or edge computing. We developed optimized resource assignment and scheduling algorithms that efficiently use vehicular computing resources for computation in emerging vehicular applications. Our proposed approaches adapt to link quality changes between vehicles and prevent congestion in vehicular networks, even in the presence of incumbent interference.

Cover page of Earth’s radiation belts: From machine learning to physical understanding

Earth’s radiation belts: From machine learning to physical understanding

  • Ma, Donglai
  • Advisor(s): Bortnik, Jacob

This dissertation explores how machine learning can be used to study the Earth's radiation belts and the physical conclusions we derive from machine learning. To be concrete, the Earth's radiation belts contain many high-energy electrons, with their energies ranging from kilo-electron volts (keV) to several Mega-electron volts (MeV). This radiation environment, exhibiting rich dynamical variations, is known to be particularly hazardous to spacecraft and is difficult to predict, particularly because of the delicate balance between acceleration, transport, and loss, combined with the many different physical processes that produce these effects. With high-quality data from the Van Allen Probes mission, we present a set of machine-learning-based models of electron fluxes ranging from 50 keV to several MeV using a neural network approach in the Earth's outer radiation belt. The Outer RadIation belt Electron Neural neT model (ORIENT) uses only a few days of the history of solar wind conditions and geomagnetic indices as input. The models show great performance ($R^2 \sim 0.7-0.9$) on the out-of-sample dataset and are able to capture electron dynamics such as intensifications, decays, dropouts, and the Magnetic Local Time dependence of the lower energy ($\sim < 100$ keV) electron fluxes during storms. Motivated by the great performance of the machine learning model, we realize that the trained model contain the information of the repeated magnetospheric dynamics driven by solar activity. Thus, we utilize a state-of-the-art feature attribution method called DeepSHAP, which was based on Shapley values in game theory, to explain the behavior of the ORIENT model at a representative electron energy of $\sim 1$ MeV during a storm time event and a non-storm time event. The results show that the feature importance calculated from the purely data-driven ORIENT model identifies physically meaningful behaviors such as magnetopause shadowing, substorm-driven acceleration, and Dst effect. We then combine this method with superposed epoch analysis to identify the long-debated question: What causes the radiation belt electrons to have two different responses, namely `enhancement' and `depletion' to storms? Our feature attribution results indicate that the depletion events can be thought of essentially as “non-acceleration” events that occur when substorm activity following the pressure maximum is not sufficient to accelerate the fluxes above its pre-storm level. The results show that average AL over storm-time period and recovery phase has a significant correlation with the resulting flux levels suggesting that it is important to incorporate the AL index history more directly into the radiation belt modeling. We then turn back to physics and build the statistical model of waves and density related to the AL index to create a Fokker-Planck simulation driven by time-varying geomagnetic activity. The result reproduces the enhancement of electrons at the ultra-relativistic range very well. The observations and simulations of 186 events illustrate a clear threshold on integral AL increasing with energy and demonstrate this is due to the influence of substorm activity on wave intensity and the density of background electrons. We demonstrate that the continuously elevated substorm activity is the determining feature needed for ultra-relativistic electron acceleration.

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GWC: Thesis and Dissertation Writing in STEM Fields (Final Stages)

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Presenter: Marilyn Gray, Director, Graduate Writing Center

Description: This workshop will give an overview of the final components and writing stages of a STEM thesis or dissertation.

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Summer Dissertation Programs 2019

2020 Summer Programs will be conducted via Zoom. We hope to have the new schedule posted by June 1st.

The Graduate Writing Center holds several programs during the summer to support graduate students who are at the dissertation and dissertation proposal stages. Programs are free of charge to those who participate. Plan to participate and have a productive summer!

How to Apply : Submit an application by the deadline indicated for the specific program. Space is limited, but we try to accept as many people as we can.

Eligibility: Only UCLA graduate and professional students who have been registered during the academic year are eligible to apply. Participants must also be at the appropriate stage for the program to which they apply.

1) Dissertation Boot Camp (Qualitative Social Sciences)

This program targets graduate students using qualitative social science research methods or mixed methods with a qualitative emphasis. Graduate students who apply to this program should have defended their proposals, completed the majority of their data collection and analysis, and be ready to write (or already writing) the results and discussion chapters (or sections). The program will address writing issues specific to qualitative research as well as general writing and organizational strategies. You are also welcome to apply if you use mixed or quantitative methods but intend to work on a descriptive or qualitative section. This program will meet Tuesdays, 5:30–8:00 PM, for the 6 weeks of Session A, June 25th–July 30th.

CLICK to see application instructions and program details.

How to Apply for the Qualitative Social Sciences Dissertation Chapter Boot Camp : Interested graduate students must fill out the Google application form linked here (your application will be kept confidential) by no later than Monday, June 17th .

Not sure whether you should apply to the Humanities or Qualitative Social Sciences Dissertation Boot Camp?

Your dissertation would fit better with humanities if one or more of the following applies:

  • you study texts, aesthetic objects, or theories;
  • you don't have separate chapters on literature review and methods;
  • you don't work with human subjects (in a manner requiring IRB approval);
  • and/or your chapters are organized in a purely topical way.

Your dissertation would fit better with qualitative social sciences if one or more of the following applies:

  • you have separate methods and literature review chapters;
  • you work with human subjects and went through the IRB process;
  • you do descriptive or ethnographic research based on interviews and observations;
  • your data analysis involves coding;
  • and/or you write your findings in results and discussion chapters.

Some research--such as oral histories, ethnographic studies, and studies of language and performance--falls in between humanities and qualitative social sciences, but we usually group projects involving human subjects with qualitative social sciences. Oral historians who don't code their interviews may fit better with the humanities. If you are not sure which section to choose, please consult with the GWC Director (Marilyn Gray: [email protected] ).

Preparation for the Qualitative Dissertation Boot Camp (for those accepted)

First Session Preparation and Homework :

Before the first session, participants should 1) read/skim a dissertation recently completed in your department, preferably one chaired by your dissertation committee chair, to get a sense of overall structure (search ProQuest Dissertations/Theses database by advisor); 2) review and do a brief outline/sketch (1-page maximum) of the structure of one of the analytical chapters in the sample dissertation, paying attention to a) type of content (data analysis, relevant empirical literature, theory, historical background, cultural context, etc.); and b) form (narrative arc, argument, and language that signposts what the writer is doing); 3) organize your notes, sources, and data for the analytical dissertation chapter you will work on during the program. Bring all relevant materials into a single physical and/or electronic location to simplify your workflow.

Participants should bring to the first session 1) your brief sketch of the sample dissertation chapter you reviewed; and 2) a 1-2 page outline of the analytical dissertation chapter you will work on during the program. If you are in the very early stages, a bulleted list of the topics and ideas you plan to address in the chapter would be fine.

Homework for Subsequent Sessions: Each session after the first will require 5 to 10 pages of new writing (of the dissertation draft). There may be additional reading and homework assignments to reinforce writing strategies.

Strongly Recommended Reading: Joan Bolker. Writing Your Dissertation in Fifteen Minutes a Day . 1998. (Available at the UCLA bookstore.) We recommend a more careful reading of chapters 3, 4 and 8, but the entire book is worth skimming.

Deadline to Apply: This program is closed .

2) Dissertation Boot Camp (Humanities & Arts)

This program targets humanities and arts graduate students who have advanced to candidacy and are at the dissertation-writing stage. The program will teach writing strategies and provide structure to help people produce a draft of a dissertation chapter. Graduate students from social science fields who use humanities approaches, such as historians or political science students who focus on theory, should also apply to this program. This program will meet Wednesdays, 5:30–8:00 PM, for the 6 weeks of Session A, June 26th–July 31st.

How to Apply for the Humanities & Arts Dissertation Chapter Boot Camp : Interested graduate students must fill out the application Google form linked here (your application will be kept confidential) by no later than Monday, June 17th . Space is limited.

Preparation for the Humanities & Arts Dissertation Boot Camp (for those accepted)

Before the first session, participants should 1) read/skim a dissertation recently completed in your department, preferably one chaired by your dissertation committee chair, to get a sense of overall structure (search ProQuest Dissertations/Theses database by advisor); 2) review and do a brief outline/sketch (1-page maximum) of the structure of one of the analytical chapters in the sample dissertation, paying attention to a) type of content (primary source analysis, secondary criticism, theory, historical or biographical background, etc.); and b) form (narrative arc, argument, and language that signposts what the writer is doing); 3) organize your notes, sources, and data for the analytical dissertation chapter you will work on during the program. Bring all relevant materials into a single physical and/or electronic location to simplify your workflow.

Participants should bring to the first session

1) your brief sketch of the sample dissertation chapter you reviewed; and 2) a 1-2 page outline of the analytical dissertation chapter you will work on during the program. If you are in the very early stages, a bulleted list of the topics and ideas you plan to address in the chapter would be fine.

3) Dissertation Proposal Boot Camp (Social Sciences)

The Social Sciences Dissertation Proposal Boot Camp is designed to help graduate students make substantial progress on a draft of their dissertation proposals. Sessions will cover strategies for writing the components of the proposal as well as managing the process. For guidance concerning research design, methodology, and other field-specific issues, please consult with faculty mentors. This program will meet Thursdays, 5:30–8:00 PM, for the 6 weeks of July 11th–August 15th.

How to Apply : Interested graduate students must fill out the Google application form linked here (your application will be kept confidential) by no later than Sunday, June 30th . Space is limited.

Homework for those accepted to the Social Sciences Dissertation Proposal Boot Camp:

For the first session , participants must bring the following:

  • Annotated Bibliography : bring a bibliography of your secondary and theoretical sources. Select four or five of the most important theoretical and secondary sources and write a paragraph or two about each. Also make sure that you have organized notes for your other sources. For the other sources that will be discussed in your literature review, we recommend writing at least a short annotation (2-3 sentences) for each one.
  • Project description (from application): bring a 200-300 word description of your dissertation project. Please be prepared to articulate your research topic succinctly.
  • Research questions: bring in a printout of your specific research questions, or if appropriate, your hypotheses and aims.
  • Recommended Reading : Joan Bolker. Writing Your Dissertation in Fifteen Minutes A Day . 1998. Chapters 1, 3 and 4. (Available at the UCLA bookstore.)

For subsequent sessions : Each session will have a required writing assignment related to your proposal. There may also be required readings that we will make available electronically.

Deadline to Apply: Sunday, June 30.

4) Dissertation Prospectus Boot Camp (Humanities & Arts)

The Humanities Dissertation Prospectus Boot Camp is designed to help graduate students make substantial progress on a draft of their dissertation prospectuses. Sessions will cover strategies for writing the components of the prospectus as well as managing the process. For guidance concerning research design, methodology, and other field-specific issues, please consult with faculty advisors/mentors. This program will meet Thursdays, 5:30–8:00 PM, for the 6 weeks of July 11th–August 15th.

How to Apply : Interested graduate students must fill out the Google application form linked here (your application will be kept confidential) by no later than Sunday, June 30th .

Homework for those accepted to the Humanities & Arts Prospectus Boot Camp:

For the first session , participants must bring in the following:

  • Annotated Bibliography: bring a bibliography of your secondary and theoretical sources. Select four or five of the most important theoretical and secondary sources and write a paragraph or two about each. Also make sure that you have organized notes for your other sources. For the other sources that will be discussed in your literature review, we recommend writing at least a short annotation (2-3 sentences) for each one.
  • Reading Assignment : In preparation for the first session, please read: Joan Bolker. Writing Your Dissertation in Fifteen Minutes A Day . 1998. Chapters 1, 3 and 4. (Available at the UCLA bookstore.)

For subsequent sessions : Each session will have a required writing assignment related to your prospectus. There may be additional required readings that we will make available electronically.

Deadline to Apply: Extended until July 7th .

5) STEM Thesis Writing Retreat

This program targets graduate students who are already writing toward their doctoral dissertation or master's thesis, such as manuscripts for publication, proposals, or dissertation/thesis chapters. The program will provide a quiet space to get away and focus on your writing. It will also offer workshops that address thesis and dissertation structure, writing strategies, and scientific writing issues. This program will meet 9:00–4:30, July 15th - 18th.

SCHEDULE, July 15th – 18th (Monday – Thursday):

Schedule (all days): * 9:00-9:15: Check in 9:15-10:00: Goal setting and productivity sessions 10:00-12:00: Individual work 12:00-12:45: Lunch break 12:45-4:30: Workshops and individual work 4:30-5:00: Check out

*Full attendance is required, but you may miss a few hours to attend lab meetings or other required appointments.

Morning Goal Setting and Productivity Sessions (Required) Every morning we will address goal setting and productivity strategies for managing writing projects efficiently. Participants will have the opportunity to discuss how their work is going and share tips. We will provide coffee and bagels.

Workshops (Recommended): Attending workshops is not required, but we recommend attending the ones that are relevant to you at your current stage of writing.

Monday, July 15th, 1:00–2:00 PM Getting Started on the Dissertation This workshop will focus on identifying and improving dissertation structure. We will examine common dissertation structures and discuss strategies for improving organization and flow both within and across articles/chapters of the dissertation. We will also discuss writing process in the sciences, project management, and time management strategies. Please bring an outline of your dissertation or dissertation proposal if you have one. Recommended for people working on their dissertation proposal and people at the early stages of writing their dissertation articles/chapters, but all are welcome.

Tuesday, July 16th, 1:00 – 2:00 PM Strategies for Writing Scientific Papers This workshop will focus on strategies for self-editing structure and style in scientific writing. We will review in depth tactics for improving flow, clarity, and conciseness, as well as general tips for healthy writing. Recommended for people at all writing stages.

Wednesday, July 17th , 1:00–2:00 PM Writing the Sciences Dissertation This workshop will focus on writing the final dissertation components, including global introduction and background sections, global conclusions, and abstracts. We will also discuss strategies for editing and integrating articles/chapters. We will be focusing on dissertations structured as a compilation of articles, but writing strategies are applicable to other thesis types. If you have started writing global introduction or conclusion chapters, we encourage you to bring them with you. Recommended for people approaching the final stages of their dissertation writing, but all are welcome.

How to Apply for the Writing Retreat : Interested graduate students should fill out the web application (linked here). Applications due Monday, July 8th .

We will let you know whether you are accepted and send further details shortly after the deadline. The program will take place in reserved rooms within the Engineering Library.

Preparation for the Writing Retreat (for those accepted)

In preparation for the program, read/skim a master's thesis or dissertation recently completed in your department, preferably one chaired by your advisor that uses similar methods. (You can do this through the ProQuest Dissertations database available through the UCLA Library.) This exercise will help you get a sense of structure and organization as well as demystify what the end product looks like. Please also bring an outline of your thesis or dissertation--the more detail, the better--to aid you in discussing your project during the program.

Optional Reading: Paul Silvia. How to Write a Lot . 2007.

Please Note : For guidance on field-specific issues, please consult faculty advisors/mentors.

If you have any questions, please contact [email protected] .

Deadline to Apply: Monday, July 8th .

Previous Workshops and Programs

Click here to see an archive of past programs and workshops .

📈 Arizona, Baylor rise in MBB Power 36

🏀 Iowa big winners in WBB Power 10

🔥 Oklahoma stays on top of softball Power 10

🏆 DIII wrestling championship selections

SELECTION SUNDAY

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Autumn Johnson | March 4, 2024

Iowa makes huge gains in new women's basketball power 10 rankings.

ucla dissertation committee

Iowa secured its most impressive win of the season in front of the women's basketball world Sunday, exacting revenge on No. 2 Ohio State 93-83 to close the regular season and rise five places in NCAA.com correspondent Autumn Johnson's Power 10 rankings. 

With conference tournament season now officially underway, here's a look at Johnson's complete rankings as we enter the madness:

Power 10 for the week of March 4

  • South Carolina (1) —  The Gamecocks finish the regular season flawless for the second year in a row! Dawn Staley has this new wave of talent looking like national championship contenders!
  • Stanford (5) —  The Cardinal scored a hugely impressive mid-week victory, storming into Corvallis and outlasting No. 11 Oregon State before blasting Oregon, 76-56.
  • Iowa (8) —  The Hawkeyes split the series with Ohio State in a massive statement game over the Big Ten regular season champs. In that matchup, Caitlin Clark became the all-time leading scorer in men's and women's Division I basketball history! 
  • Ohio State (2) —  Despite falling to the Hawkeyes on Sunday, Ohio State can still claim an improbable 2023-24 Big Ten regular season championship.
  • Texas (3) —  The Longhorns' eight-game winning streak fell victim to a buzzer-beater in Norman, gifting the Sooners the Big 12 regular season crown.
  • LSU (6)   —  The defending champs took care of Georgia and Kentucky in blowout fashion to remain rooted at six.
  • UCLA (9)  — The Bruins are peaking at the right time, cruising through their Arizona road trip by a combined 50 points. 
  • Indiana (7)  — No trouble this week for the Hoosiers, finishing up Big Ten play with comfortable wins over Northwestern and Maryland.
  • Southern Cal (10)  — The Trojans escaped a pesky Arizona squad in overtime before defeating Arizona State. 
  • UConn (NR) - Riding a six-game winning streak, UConn once again breaks into the top 10.

👉🏼 Clark breaks scoring record, South Carolina remains perfect on busy Sunday

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  • Clark breaks scoring record, South Carolina remains perfect headlining the the first Sunday in March

ucla dissertation committee

Caitlin Clark's impact on girls basketball in the Hoosier State

ucla dissertation committee

South Carolina, Ohio State, Stanford, UCLA earn top seeds in DI Women's Basketball Committee top-16 reveal

March madness.

  • 📆 2024 March Madness schedule
  • ❓ How the field of 68 is picked
  • 👀 Best performances in tournament history

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Women's Final Four Most Outstanding Players from 1982 to present

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The 13 highest-scoring individual performances in March Madness history

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Women's basketball championship history

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Schools with the most DI women's basketball national championships

ucla dissertation committee

Best performances in NCAA women's basketball tournament history

Di women's basketball news.

  • Fairfield is NCAA.com's women's basketball team of the week
  • Iowa soars back into top 3 of Power 10 women's basketball rankings
  • Iowa makes huge gains in women's basketball Power 10 rankings
  • Caitlin Clark tracker: Follow the Iowa star's biggest games and highlights in the 2023-24 season
  • Undefeated teams in DI college basketball
  • Women's college basketball all-time DI scoring leaders
  • How to play the official March Madness Men's Conference Tournament Pick'Em and Women's Conference Tournament Pick'Em games
  • A reason to believe in each of the selection committee's top-16 seeds
  • NCAA women's basketball tournament bracket predictions on the first day of March

Follow NCAA Women's Basketball

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UCLA Graduate Programs

Students meeting in an on-campus coffee shop

Reconstitution of Master’s Thesis Committee

Form and requirements for changing the members of your Master’s Committee. Any changes in committee membership are requested after consultation with the chair of the committee, all committee members (incoming, outgoing, and continuing members), and the student.

IMAGES

  1. Han Bao Successfully Defends Dissertation

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  2. Summer Dissertation Fellowship

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  3. Thesis/Dissertation Template for University of California, Los Angeles

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  4. UCI/UCLA Joint Ed.D. Program Dissertation Titles

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  5. Department Honors Program

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  6. Committees

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VIDEO

  1. The 4th Undergraduate Research Forum

  2. President's Undergraduate Research Symposium: Session 1

  3. Courtney Radsch on Google's profiting from news publishers

  4. Local universities break down plans to maintain a diverse campus

  5. Activists are suing Harvard University over legacy admissions

  6. Get involved at the Institute of Politics

COMMENTS

  1. Master's Thesis Committee Regulations

    Master's Thesis committees are appointed by the Dean of the Graduate Division, acting for the Graduate Council, upon nomination by the Chair of the Department (or Interdepartmental Program), after consultation with the student. Master's Thesis committees consist of a minimum of three faculty members from UCLA. Acting Professor (any rank).

  2. Nomination of Doctoral Committee

    Nomination of Doctoral Committee. Launch interactive PDF. Form and requirements governing nomination of doctoral committee. PhD students can nominate their doctoral committee and read UCLA's regulations.

  3. Minimum Standards for Doctoral Committee Constitution

    All committee members read, approve, and certify the dissertation. Each program or department may set additional requirements above the UCLA minimum standards in their Program Requirements regarding: UCLA members (e.g., all three must hail from the home department, two out of three from the same discipline as the student, etc.)

  4. Summer Dissertation Programs 2023

    Summer Dissertation Programs 2023. The Graduate Writing Center holds several programs during the summer to support graduate students who are at the dissertation, dissertation proposal, or master's thesis writing stages. Programs are free of charge to UCLA graduate students who participate. Note: All summer programs will be held via Zoom.

  5. Thesis Committee and Oral Qualifying Exam

    Once this examination is passed and students have chosen a research area for the dissertation, within a reasonable time frame agreed on with the dissertation advisor, they form a doctoral committee and schedule the University Oral Qualifying Examination. This examination is based on a proposed dissertation topic.

  6. PDF PhD Program Dissertation

    Formation of the Dissertation Committee. Select a member of the faculty to serve as chair of the student's dissertation committee. The student works with the chair of their committee to form the full committee, consisting of a minimum of 4 faculty members. Discuss dissertation plans with each prospective committee member before the committee ...

  7. Dissertation

    Dissertation. Once the coursework and field papers are completed, students proceed to the dissertation stage. The first step is to delineate an original research project in a dissertation prospectus. Presented to a faculty examining committee, the prospectus provides the principal basis for discussion during the qualifying oral examination ...

  8. File Your Thesis or Dissertation

    The last date that all of the items listed above is complete will be your filing date for your thesis or dissertation. For example, if you submit your final dissertation PDF and complete the online process on May 31, three committee members sign on June 1, and the final committee member signs on June 2, your filing date will be June 2 assuming ...

  9. Summer Dissertation Programs 2021

    1) read/skim a dissertation recently completed in your department, preferably one chaired by your dissertation committee chair, to get a sense of overall structure (search ProQuest Dissertations/Theses database by advisor);

  10. Summer Dissertation Programs 2020

    Eligibility: Only UCLA graduate and professional students who have been registered during the academic year are eligible to apply. Participants must also be at the appropriate stage for the program to which they apply. ... preferably one chaired by your dissertation committee chair, to get a sense of overall structure (search ProQuest ...

  11. Dissertations and Theses

    UCLA has access to all full text dissertations in the database. Non-UCLA users may use Dissertations Express to purchase digital or print copies of individual dissertations. Over 5 million dissertations and theses available in OCLC member libraries. Many theses are available electronically, at no charge, directly from the publishing institution.

  12. Dissertations

    Dissertations at UCLA and Beyond. Index to doctoral dissertations from 1637 to the present, with abstracts since 1980. A number of master's theses are also indexed, with abstracts since 1988. Many are available for download in pdf format. UCLA has access to all full text dissertations in the database.

  13. Dissertations

    Historically, most doctoral dissertations and selected master's theses were deposited in the Library's main collections. Those theses and dissertations can be found in the Catalog under the subject headings Dissertations, Academic--UCLA--[Department].As of 2012, UCLA's Graduate Division switched to all digital submissions, so the Library no longer receives print copies of UCLA theses and ...

  14. UCLA Electronic Theses and Dissertations

    Advisor (s): Bortnik, Jacob. ( 2024) This dissertation explores how machine learning can be used to study the Earth's radiation belts and the physical conclusions we derive from machine learning. To be concrete, the Earth's radiation belts contain many high-energy electrons, with their energies ranging from kilo-electron volts (keV) to several ...

  15. Professional (Non-Ph.D.) Doctoral Committee Policy, Effective Fall 2022

    Effective Fall 2022, Adjuncts are permitted to serve as regular members, but not as sole chair or Academic Senate members, on professional (non-Ph.D.) doctoral committees, without need of an exception from the Graduate Council's Committee on Degree Programs (CDP). If an Adjunct serves as co-chair, at least one of the co-chairs must be from ...

  16. GWC: Thesis and Dissertation Writing in STEM Fields (Final Stages

    Share This: Share GWC: Thesis and Dissertation Writing in STEM Fields (Final Stages) on Facebook Share GWC: Thesis and Dissertation Writing in STEM Fields (Final Stages) ... [email protected]. Address. Strathmore Building 2nd & 3rd Floors 501 Westwood Plaza Los Angeles, CA 90095-1573. Career Service Hours. M Monday 9:00 am- 5:00 pm

  17. South Carolina, Ohio State, Stanford, UCLA earn top seeds in DI Women's

    With only 18 days remaining before Selection Sunday, the NCAA Division I Women's Basketball Committee tabbed South Carolina, Ohio State, Stanford and UCLA as the No. 1 seeds in the latest top-16 ...

  18. PDF Ali Fattahi CV

    • Dissertation Year Fellowship, UCLA Graduate Education, Sept. 2018 - June 2019. • Harold and Pauline Price Center for Entrepreneurship and Innovation, 2016 - 2017. ... • Committee Member, OMBA Tenure-Track Faculty Hiring, Carey BS, 2023 - 2024.

  19. Thesis & Dissertation Filing Requirements

    View Thesis & Dissertation Filing Requirements PDF. This is the official UCLA manuscript preparation guide that contains established criteria for uniformity in the format of theses and dissertations. The regulations included in it supersede any style manual instructions regarding format. Also includes information on filing dates and procedures ...

  20. Ohio State tops final Power 5 of women's hockey season

    With only 18 days remaining before Selection Sunday, the NCAA Division I Women's Basketball Committee tabbed South Carolina, Ohio State, Stanford and UCLA as the No. 1 seeds in the latest top-16 ...

  21. Nomination of Master's Thesis Committee

    Nomination of Master's Thesis Committee. Launch interactive PDF. Form and requirements governing nomination of a master's thesis committee. Master's students can nominate their thesis committee and read UCLA's regulations.

  22. Summer Dissertation Programs 2019

    Eligibility: Only UCLA graduate and professional students who have been registered during the academic year are eligible to apply. Participants must also be at the appropriate stage for the program to which they apply. ... preferably one chaired by your dissertation committee chair, to get a sense of overall structure (search ProQuest ...

  23. Iowa makes huge gains in new women's basketball Power 10 rankings

    With only 18 days remaining before Selection Sunday, the NCAA Division I Women's Basketball Committee tabbed South Carolina, Ohio State, Stanford and UCLA as the No. 1 seeds in the latest top-16 ...

  24. Reconstitution of the Doctoral Committee and/or Change in Final Oral

    Recommendation for reconstitution of a doctoral committee is made jointly by the chair of the department and the chair of the doctoral committee after consultation with the members of the committee who are in residence and the student. Student Instructions for Completing Doctoral Reconstitution (PDF)

  25. PDF UCLA Thesis and Dissertation Filing Requirements & Public Dissemination

    Students are encouraged to file their thesis or dissertation as early as possible. All filing must be completed online. Submissions on the day of the deadline will be accepted until 5 PM PT. A completed submission entails the following: • All committee members must have reported approval via go.grad.ucla.edu) )

  26. Dissertation Year Award

    Dissertation Year Award. This program is intended to support doctoral students who are advanced to candidacy at the time of nomination by their department to the Division of Graduate Education. Applicants should be within one year of completing and filing the dissertation and planning to start teaching or research appointments soon after the ...

  27. Reconstitution of Master's Thesis Committee

    Reconstitution of Master's Thesis Committee. Launch interactive PDF. Form and requirements for changing the members of your Master's Committee. Any changes in committee membership are requested after consultation with the chair of the committee, all committee members (incoming, outgoing, and continuing members), and the student.