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Essex theses, uk & north american theses, open access digitised dissertations.

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Theses (or dissertations as they are sometimes called) are the product of extended independent research by students. They may be produced at undergraduate level (e.g. 3rd year Capstone projects), and are nearly always a feature of postgraduate research from Master's through to Ph.D. level.

Books offering guidance on how to write a thesis can be found at LB 2369 on floor 5 of the Albert Sloman Library.

Students often need to consult theses for various reasons, including:

• checking the style and presentation of good past dissertations from their department
• making sure that they are not repeating research already undertaken
• using theses on a similar topic to gain useful information and/or references

Essex Sociology theses  can be found in the following locations:

• Sociology Study Centre - print copies of dissertations submitted up to 2018 are available in the Sociology Study Centre (5A.307). These are all undergraduate (2.1 and 1st) and Master's dissertations. Submissions from 2018 onwards are available to access digitally, with a request to the Department's Study Support Manager. Please go to the Study Centre Moodle page, where there is further information on the Dissertation Library . For help and advice on finding suitable examples, please email: [email protected]
• Al bert Sloman Library - the University Library at Colchester holds print copies of all Essex Criminology M.Phil. and Ph.D. dissertations up to 30 September 2016. They are listed in the catalogue, and must be consulted in the Library. To search by department type the keywords: essex thesis sociology

University of Essex Research Repository  - contains digitised versions of theses submitted after 30 September 2016. These are also listed in the library catalogue

To search for dissertations from  other universities in the UK and beyond , there are a couple of very useful databases:  

EThOS  offers details of UK doctoral theses, some of which are digitised

ProQuest Dissertations & Theses  lists North American & UK theses (with some coverage of other countries):

• EThOS EThOS aims to provide a 'single point of access' where researchers the world over can access all theses produced by UK Higher Education. The database can be searched by anyone, but individual users need to register to get access to the full text of theses. Many theses are free to download instantly, whilst others will only be available once digitisation has been requested. The hub automatically harvests e-theses from Institutional Repositories and digitises paper theses from participating institutions to offer the single point of access. Many UK institutions support Open Access to their theses, so download of their digital and digitised theses is free to the researcher. A small number of participating institutions may not be able to offer Open Access and in this case the researcher may have to pay for the digitisation. Where a thesis must be digitised before supply, you can expect a short delay. However, you will be informed when the thesis is ready for collection and you can then log on to the system and download it.
• ProQuest dissertations and theses ProQuest Dissertations and Theses: Global (PQDTGlobal) is the world's most comprehensive collection of full-text dissertations and theses. As the official digital dissertations archive for the Library of Congress and as the database of record for graduate research, PQDTGlobal includes millions of searchable citations to dissertations and theses from 1861 to the present day together with over a million full-text dissertations that are available for download in PDF format. Over 2.1 million titles are available for purchase as printed copies. The database offers full text for most of the dissertations added since 1997 and strong retrospective full-text coverage for older graduate works. It also includes PQDT UK & Ireland content. More than 70,000 new full-text dissertations and theses are added to the database each year through dissertations publishing partnerships with 700 leading academic institutions worldwide, and collaborative retrospective digitization of dissertations. Full-text dissertations are archived as submitted by the degree-granting institution. Some will be native PDF, some PDF image. Each dissertation published since July, 1980 includes a 350-word abstract written by the author. Master's theses published since 1988 include 150-word abstracts. Simple bibliographic citations are available for dissertations dating from 1637. Where available, PQDTGlobal provides 24-page previews of dissertations and theses. Note: Full text for certain publications is subject to market availability more... less... Shibboleth login

There are also many portals to  open access dissertations . NDLTD maintains a pretty comprehensive & up to date list of national portals around the world:

• NDLTD Digital Theses Portals Useful listing of national e-theses portals

Global search engines for digital theses include the following:

• CRL Dissertations details of over 800 000 non-US dissertations held by the CRL from mid-19th century onwards
• Ebsco Open Dissertations over 800 000 open access dissertations worldwide
• Networked Digital Library of Theses & Dissertations NDLTD is a portal to millions of digitised theses

Many  regions and countries  also have portals to electronic theses. Examples include:

Africa  -  Database of African Theses and Dissertations (DATAD)

Australia  -  Trove

Brazil  -  Biblioteca Digital Brasileira de Teses e Dissertacoes (BDTD)

Canada  -  Theses Canada Portal

Europe  -  DART-Europe

TEL Theses-en-ligne (PhD)

DUMAS (Masters)  

Germany  -  Dissonline

Greece  -  National Archive of PhD Theses

Hong Kong  -  Hong Kong University Theses Online

India  -  Shodhganga

Japan  -  National Diet Library doctoral dissertations

Netherlands  -  NARCIS  

Russia & CIS  -  Dissertation CIS

Scandinavia  -  DiVA  (the Academic Archive Online)

South Africa  -  National ETD Portal

Spain  -  TDX (Tesis Doctorales en Xarva)

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Resitting or resubmission - student visa

Resits, resubmission, viva.

Although the Board of Examiners may have given you options under the Rules of Assessment, some options are not always an option for sponsored student who would need to apply for further Student immigration permission due to academic failure.

There are a maximum number of years you can spend in the UK studying at undergraduate degree level so, any changes to your studies that will result in you spending longer than planned obtaining your qualification must be considered very carefully.

If you have a Tier 4 or Student visa, the University is required to report changes in your studies to the Home Office. The University is only able to sponsor you for the periods that you are required to be in attendance in the UK. You should leave the UK when you are not required to attend and will usually have to apply for a new visa before you return.

Resitting exams (out of residence)

Students who are offered resits out of residence will not be required to attend until the first exam in the summer term of the next academic year. You should leave the UK during this period. If you have a valid student visa it will be curtailed (cut short) by the Home Office and won't be valid for travel back to the UK.

Most students will need to apply for entry clearance overseas to return to the UK to take their resit exam(s). If your studies will have finished once you have taken your exam(s) you could apply to return to the UK as a Standard Visitor provided you can meet all the Home Office requirements. Standard Visitors cannot work or apply to extend their visa from within the UK. Non-visa nationals can apply for entry as a Standard Visitor at the UK border. Further information is available in our ' applying for a visa ' section.

The University does not sponsor students under Student route when they are only required to resit exams. If your resits are to be held inside the UK and there are reasons why you would like to apply for a Student visa to return to the UK to take your resit exams, you should contact the International Services Team to ask if it would be possible for us to sponsor you to apply for a Student visa.

Repeating the year or repeating modules part-time

It's not always possible for you to take these options if they're offered to you by the Board of Examiners. This is because of the Student Immigration Rules regarding the maximum length of time you can spend studying in the UK either below degree level or at undergraduate degree level.

If you're not required to attend in all three terms, we can't sponsor you for the periods you're not required to attend. If you only need to attend for up to six months you may have to return as a short-term student .

If you have been offered repeat the year or modules part-time in all three terms and your current Student visa is not long enough to cover the extended course duration, please contact the International Services Team immediately to request a CAS.

If you're eligible for a CAS you should make your Student application before you return for the next academic year. If you're repeating during that year you should be able to make the application in the UK. However, you may choose to make the application overseas.

If you are unsure what you should do and want advice about your choices, seek advice from the International Services Team by completing our online enquiry form .

Resubmission of dissertation – Postgraduate taught students

Postgraduate taught students who are offered the opportunity to resubmit their dissertation are not required to be present at the University and can submit online. Therefore, if your Student visa expires before you are due to submit your dissertation, the University will not able to sponsor you to extend your visa.

If you need to be in the UK to work on and submit your dissertation and you would like to apply for further Student immigration permission, you should contact the International Services Team to ask if it would be possible for us to sponsor you to apply for a Student visa.

Attending your Viva Voce – PhD students

If your student visa expires before you have attended your Viva and finished your PhD and you would like to apply for further Student immigration permission, please contact the International Services Team to request a CAS.

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Submissions

This page is designed to help you ensure your submission fits the scope of the journal.

Before submitting you should read over the guidelines both on this page, and within the relevant submission  template.  

• Template for academic writing (essays, research papers, case studies, academic blog posts, etc.).
• Template for creative writing (currently accepting short fiction and poetry - register your interest to be the first to know if/when we open to new creative writing formats).

Use the relevant template to format your paper, then register for an account before submitting (or login if you have an existing account).

The Essex Student Journal is an online multi-disciplinary academic journal, run by and for University of Essex students, with the administration funded and supported by the University of Essex. The journal is dedicated to the publication of high-quality undergraduate and postgraduate writing, and is committed to creating accessible and engaging content for a non-specialist readership. The Essex Student Journal encourages and celebrates student research by offering valuable early experience of academic publishing and the peer review process. More information about the Essex Student Journal is available on University of Essex Library website . 

Focus and Scope

The Essex Student Journal publishes the work of undergraduate and Masters students currently studying at the University of Essex. Submissions will also be accepted from individuals who have graduated from the University of Essex within the last 12 months.

The Essex Student Journal is a multidisciplinary journal, meaning we accept submissions from all subject areas. Please see below for further information.

Peer Review

This journal operates a double blind peer review policy, meaning that neither the author nor the reviewer will be aware of each other's identities. The final decision on accepting/publishing a paper is made by the editor but informed by peer reviewer comments.

If you are a PhD student and are interested in becoming a peer reviewer, you can sign up here . Please ensure you add your subject interests when creating your account, as this ensures you are assigned papers relevant to your expertise and interests.

You can find more information and advice on completing peer review in our peer reviewer guidance . No experience of peer reviewing is required to be a reviewer for the Essex Student Journal, and we are always happy to help.

Submission Checklist

The Essex Student Journal is open for submission with no deadline; articles are published online when ready. Publications must be submitted by current students, or based on coursework written whilst studying at the University of Essex. The submission must be in English, and of high quality (for example coursework that has received a mark of 70% or higher).

We currently accept these types of papers from all subject areas:

• Research papers
• Case studies
• Other (can include academic blog posts, conference papers, reviews etc.)
• We are currently running a  creative writing pilot , where we are accepting works of short fiction and poetry. More information about the format of creative writing is available in our creative writing template . If you would like to publish a different form of creative writing to short fiction or poetry, please  register your interest to find out more.

Below is some information about how we classify our standard publication types: essays, research papers, and case studies.

Submission checklist

• Submissions must be submitted in a Word document, using either our academic writing template , or our creative writing template .
• Abstracts should be 200 words maximum.
• The word limit for general submissions is 2,800-3,000 words for the main body. For Masters students who wish to submit their dissertations, the word limit is 8000 words. Please be aware that longer submissions of this nature will take more time to peer review.
• Submissions must be edited according to the style guide (below) to suit the journal audience.
• Do not include your name anywhere in the Word document, as the peer review process will be double blind (both author and peer reviewer are anonymous). Your name will be linked to the document in the submission system, which only the Editor will see. 

Style guide

• All formatting should follow the guidelines available in either our  academic writing template , or our  creative writing template
• We require all submissions to follow Harvard style referencing  where sources are cited . However, in some cases, such as legal texts, other referencing styles can be used (e.g. OSCOLA ).
• Academic writing should be  concise , with clear subjects and actions in every sentence. This style will vary when submitting creative writing.
• Use consistent verb tenses throughout your manuscript. This style will vary when submitting creative writing.

Please note that all submissions will be subject to peer review to decide whether they are suitable for the journal. We also expect that submissions will not be under consideration, or previously published, with another publication.

If you have any questions about submissions, please email us at [email protected] .

Expectations for authors

• Follow the journal’s deadlines (for corrections and re-submission in case of conditional acceptance). 
• Provide an email address that will stay active for at least 6 months. You can provide either your Essex email address or your personal one. 
• In cases where we cannot communicate with you for more than 4 months, your paper will be deleted from our system, and it will not be published. 
• Don’t forget to remove your name or personal details from any part of your paper.
• Follow the style guide on the submission checklist.

Expectations for reviewers

• Follow the journal’s deadlines for reviewing the papers. In cases where you need more time, you can contact the journal to ask for an extension to the original deadline. 
• Provide an email address that will stay active for as long as you are volunteering to be a reviewer. You can provide either your Essex email address or your personal one. 
• Remember to anonymize your review, because the journal operates a double-blind peer review process. 
• Provide fair and constructive feedback to authors, and offer additional clarification if requested by the editor.

Expectations for the editor

• Respond to any enquiries within a week.
• Pass on the submitted papers to peer reviewers in a timely fashion. 
• Inform authors about completed reviews, including comments and feedback from the reviewers.
• Notify the author when the paper is published.
• Provide clear messaging if the editorial team will be on a break.
• Be objective and professional when reading the submitted papers.
• Make the final decision on whether a paper should be accepted and published.

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CS&E Announces 2024-25 Doctoral Dissertation Fellowship (DDF) Award Winners

Seven Ph.D. students working with CS&E professors have been named Doctoral Dissertation Fellows for the 2024-25 school year. The Doctoral Dissertation Fellowship is a highly competitive fellowship that gives the University’s most accomplished Ph.D. candidates an opportunity to devote full-time effort to an outstanding research project by providing time to finalize and write a dissertation during the fellowship year. The award includes a stipend of $25,000, tuition for up to 14 thesis credits each semester, and subsidized health insurance through the Graduate Assistant Health Plan.

CS&E congratulates the following students on this outstanding accomplishment:

• Athanasios Bacharis (Advisor: Nikolaos Papanikolopoulos )
• Karin de Langis (Advisor:  Dongyeop Kang )
• Arshia Zernab Hassan (Advisors: Chad Myers )
• Xinyue Hu (Advisors: Zhi-Li Zhang )
• Lucas Kramer (Advisors: Eric Van Wyk )
• Yijun Lin (Advisors: Yao-Yi Chiang )
• Mingzhou Yang (Advisors: Shashi Shekhar )

Athanasios Bacharis

Bacharis’ work centers around the robot-vision area, focusing on making autonomous robots act on visual information. His research includes active vision approaches, namely, view planning and next-best-view, to tackle the problem of 3D reconstruction via different optimization frameworks. The acquisition of 3D information is crucial for automating tasks, and active vision methods obtain it via optimal inference. Areas of impact include agriculture and healthcare, where 3D models can lead to reduced use of fertilizers via phenotype analysis of crops and effective management of cancer treatments. Bacharis has a strong publication record, with two peer-reviewed conference papers and one journal paper already published. He also has one conference paper under review and two journal papers in the submission process. His publications are featured in prestigious robotic and automation venues, further demonstrating his expertise and the relevance of his research in the field.

Karin de Langis

Karin's thesis works at the intersection of Natural Language Processing (NLP) and cognitive science. Her work uses eye-tracking and other cognitive signals to improve NLP systems in their performance and cognitive interpretability, and to create NLP systems that process language more similarly to humans. Her human-centric approach to NLP is motivated by the possibility of addressing the shortcomings of current statistics-based NLP systems, which often become stuck on explainability and interpretability, resulting in potential biases. This work has most recently been accepted and presented at SIGNLL Conference on Computational Natural Language Learning (CoNLL) conference which has a special focus on theoretically, cognitively and scientifically motivated approaches to computational linguistics.

Arshia Zernab Hassan

Hassan's thesis work delves into developing computational methods for interpreting data from genome wide CRISPR/Cas9 screens. CRISPR/Cas9 is a new approach for genome editing that enables precise, large-scale editing of genomes and construction of mutants in human cells. These are powerful data for inferring functional relationships among genes essential for cancer growth. Moreover, chemical-genetic CRISPR screens, where population of mutant cells are grown in the presence of chemical compounds, help us understand the effect the chemicals have on cancer cells and formulate precise drug solutions. Given the novelty of these experimental technologies, computational methods to process and interpret the resulting data and accurately quantify the various genetic interactions are still quite limited, and this is where Hassan’s dissertation is focused on. Her research extends to developing deep-learning based methods that leverage CRISPR chemical-genetic and other genomic datasets to predict cancer sensitivity to candidate drugs. Her methods on improving information content in CRISPR screens was published in the Molecular Systems Biology journal, a highly visible journal in the computational biology field. 

Hu's Ph.D. dissertation is concentrated on how to effectively leverage the power of artificial intelligence and machine learning (AI/ML) – especially deep learning – to tackle challenging and important problems in the design and development of reliable, effective and secure (independent) physical infrastructure networks. More specifically, her research focuses on two critical infrastructures: power grids and communication networks, in particular, emerging 5G networks, both of which not only play a critical role in our daily life but are also vital to the nation’s economic well-being and security. Due to the enormous complexity, diversity, and scale of these two infrastructures, traditional approaches based on (simplified) theoretical models and heuristics-based optimization are no longer sufficient in overcoming many technical challenges in the design and operations of these infrastructures: data-driven machine learning approaches have become increasingly essential. The key question now is: how does one leverage the power of AI/ML without abandoning the rich theory and practical expertise that have accumulated over the years? Hu’s research has pioneered a new paradigm – (domain) knowledge-guided machine learning (KGML) – in tackling challenging and important problems in power grid and communications (e.g., 5G) network infrastructures.

Lucas Kramer

Kramer is now the driving force in designing tools and techniques for building extensible programming languages, with the Minnesota Extensible Language Tools (MELT) group. These are languages that start with a host language such as C or Java, but can then be extended with new syntax (notations) and new semantics (e.g. error-checking analyses or optimizations) over that new syntax and the original host language syntax. One extension that Kramer created was to embed the domain-specific language Halide in MELT's extensible specification of C, called ableC. This extension allows programmers to specify how code working on multi-dimensional matrices is transformed and optimized to make efficient use of hardware. Another embeds the logic-programming language Prolog into ableC; yet another provides a form of nondeterministic parallelism useful in some algorithms that search for a solution in a structured, but very large, search space. The goal of his research is to make building language extensions such as these more practical for non-expert developers.  To this end he has made many significant contributions to the MELT group's Silver meta-language, making it easier for extension developers to correctly specify complex language features with minimal boilerplate. Kramer is the lead author of one journal and four conference papers on his work at the University of Minnesota, winning the distinguished paper award for his 2020 paper at the Software Language Engineering conference, "Strategic Tree Rewriting in Attribute Grammars".

Lin’s doctoral dissertation focuses on a timely, important topic of spatiotemporal prediction and forecasting using multimodal and multiscale data. Spatiotemporal prediction and forecasting are important scientific problems applicable to diverse phenomena, such as air quality, ambient noise, traffic conditions, and meteorology. Her work also couples the resulting prediction and forecasting with multimodal (e.g., satellite imagery, street-view photos, census records, and human mobility data) and multiscale geographic information (e.g., census records focusing on small tracts vs. neighborhood surveys) to characterize the natural and built environment, facilitating our understanding of the interactions between and within human social systems and the ecosystem. Her work has a wide-reaching impact across multiple domains such as smart cities, urban planning, policymaking, and public health.

Mingzhou Yang

Yang is developing a thesis in the broad area of spatial data mining for problems in transportation. His thesis has both societal and theoretical significance. Societally, climate change is a grand challenge due to the increasing severity and frequency of climate-related disasters such as wildfires, floods, droughts, etc. Thus, many nations are aiming at carbon neutrality (also called net zero) by mid-century to avert the worst impacts of global warming. Improving energy efficiency and reducing toxic emissions in transportation is important because transportation accounts for the vast majority of U.S. petroleum consumption as well as over a third of GHG emissions and over a hundred thousand U.S. deaths annually via air pollution. To accurately quantify the expected environmental cost of vehicles during real-world driving, Yang's thesis explores ways to incorporate physics in the neural network architecture complementing other methods of integration: feature incorporation, and regularization. This approach imposes stringent physical constraints on the neural network model, guaranteeing that its outputs are consistently in accordance with established physical laws for vehicles. Extensive experiments including ablation studies demonstrated the efficacy of incorporating physics into the model. 

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