autonomous phd thesis

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•     Bib Dam, T. (2023). Sample Efficient Monte Carlo Tree Search for Robotics , Ph.D. Thesis .
•       Bib Flynn, H. (2023). PAC-Bayesian Bandit Algorithms With Guarantees , Ph.D. Thesis .
•       Bib Klink, P. (2023). Reinforcement Learning Curricula as Interpolations between Task Distributions , Ph.D. Thesis .
•       Bib Look, A. (2023). Deterministic Approximations for Deep State-Space Models , Ph.D. Thesis .
•   Bib Prasad, V.; (2023). Learning Human-Robot Interaction: A Case Study on Human-Robot Handshaking , Ph.D. Thesis .
•     Bib Urain, J. (2023). Deep Generative Models for Motion Planning and Control , Ph.D. Thesis .
•       Bib Abdulsamad, H. (2022). Statistical Machine Learning for Modeling and Control of Stochastic Structured Systems , Ph.D. Thesis .
•     Bib Becker-Ehmck, P. (2022). Latent State-Space Models for Control , Ph.D. Thesis .
•       Bib Belousov, B. (2022). On Optimal Behavior Under Uncertainty in Humans and Robots , Ph.D. Thesis .
•     Bib Cowen-Rivers, A. (2022). Pushing The Limits of Sample-Efficient Optimisation , Ph.D. Thesis .
•       Bib Arenz, O. (2021). Sample-Efficient I-Projections for Robot Learning , Ph.D. Thesis .
•     Bib Loeckel, S. (2021). Machine Learning for Modeling and Analyzing of Race Car Drivers , Ph.D. Thesis .
•     Bib Lutter, M. (2021). Inductive Biases for Machine Learning in Robotics and Control , Ph.D. Thesis .
•     Bib Muratore, F. (2021). Randomizing Physics Simulations for Robot Learning , Ph.D. Thesis .
•     Bib Tosatto, S. (2021). Off-Policy Reinforcement Learning for Robotics , PhD Thesis .
•     Bib Koert, D. (2020). Interactive Machine Learning for Assistive Robots , Ph.D. Thesis .
•     Bib Lampariello, R. (2020). Optimal Motion Planning for Object Interception and Grasping , Ph.D. Thesis .
•     Bib Tanneberg, D. (2020). Understand-Compute-Adapt: Neural Networks for Intelligent Agents , Ph.D. Thesis .
•     Bib Buechler, D. (2019). Robot Learning for Muscular Systems , Ph.D. Thesis .
•     Bib Ewerton, M. (2019). Bidirectional Human-Robot Learning: Imitation and Skill Improvement , PhD Thesis .
•     Bib Gebhardt, G.H.W. (2019). Using Mean Embeddings for State Estimation and Reinforcement Learning , PhD Thesis .
•     Bib Gomez-Gonzalez, S. (2019). Real Time Probabilistic Models for Robot Trajectories , Ph.D. Thesis .
•     Bib Parisi, S. (2019). Reinforcement Learning with Sparse and Multiple Rewards , PhD Thesis .
•     Bib Koc, O. (2018). Optimal Trajectory Generation and Learning Control for Robot Table Tennis , PhD Thesis .
•     Bib Lioutikov, R. (2018). Parsing Motion and Composing Behavior for Semi-Autonomous Manipulation , PhD Thesis .
•     Bib Veiga, F. (2018). Toward Dextrous In-Hand Manipulation through Tactile Sensing , PhD Thesis .
•       Bib Manschitz, S. (2017). Learning Sequential Skills for Robot Manipulation Tasks , PhD Thesis .
•       Bib Paraschos, A. (2017). Robot Skill Representation, Learning and Control with Probabilistic Movement Primitives , PhD Thesis .
•     Bib Vinogradska, J. (2017). Gaussian Processes in Reinforcement Learning: Stability Analysis and Efficient Value Propagation , PhD Thesis .
•     Bib Calandra, R. (2016). Bayesian Modeling for Optimization and Control in Robotics , PhD Thesis .
•     Bib Daniel, C. (2016). Learning Hierarchical Policies from Human Feedback , PhD Thesis .
•     Bib Hoof, H.v. (2016). Machine Learning through Exploration for Perception-Driven Robotics , PhD Thesis .
•     Bib Kroemer, O. (2015). Machine Learning for Robot Grasping and Manipulation , PhD Thesis .
•       Bib Muelling, K. (2013). Modeling and Learning of Complex Motor Tasks: A Case Study with Robot Table Tennis , PhD Thesis .
•       Bib Wang, Z. (2013). Intention Inference and Decision Making with Hierarchical Gaussian Process Dynamics Model , PhD Thesis .
•       Bib Kober, J. (2012). Learning Motor Skills: From Algorithms to Robot Experiments , PhD Thesis .
•       Bib Nguyen-Tuong, D (2011). Model Learning in Robot Control , PhD Thesis (Completed at IAS/Tuebingen before move to TU Darmstadt) .

Automatic laser calibration, mapping, and localization for autonomous vehicles

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System modeling for connected and autonomous vehicles

Connected and autonomous vehicle (CAV) technologies provide disruptive and transformational opportunities for innovations toward intelligent transportation systems. Compared with human driven vehicles (HDVs), the CAVs can reduce reaction time and human errors, increase traffic mobility and will be more knowledgeable due to vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. CAVs’ potential to reduce traffic accidents, improve vehicular mobility and promote eco-driving is immense. However, the new characteristics and capabilities of CAVs will significantly transform the future of transportation, including the dissemination of traffic information, traffic flow dynamics and network equilibrium flow. This dissertation seeks to realize and enhance the application of CAVs by specifically advancing the research in three connected topics: (1) modeling and controlling information flow propagation within a V2V communication environment, (2) designing a real-time deployable cooperative control mechanism for CAV platoons, and (3) modeling network equilibrium flow with a mix of CAVs and HDVs.

Vehicular traffic congestion in a V2V communication environment can lead to congestion effects for information flow propagation due to full occupation of the communication channel. Such congestion effects can impact not only whether a specific information packet of interest is able to reach a desired location, but also the timeliness needed to influence traffic system performance. This dissertation begins with exploring spatiotemporal information flow propagation under information congestion effects, by introducing a two-layer macroscopic model and an information packet relay control strategy. The upper layer models the information dissemination in the information flow regime, and the lower layer model captures the impacts of traffic flow dynamics on information propagation. Analytical and numerical solutions of the information flow propagation wave (IFPW) speed are provided, and the density of informed vehicles is derived under different traffic conditions. Hence, the proposed model can be leveraged to develop a new generation of information dissemination strategies focused on enabling specific V2V information to reach specific locations at specific points in time.

In a V2V-based system, multiclass information (e.g., safety information, routing information, work zone information) needs to be disseminated simultaneously. The application needs of different classes of information related to vehicular reception ratio, the time delay and spatial coverage (i.e., distance it can be propagated) are different. To meet the application needs of multiclass information under different traffic and communication environments, a queuing strategy is proposed for each equipped vehicle to disseminate the received information. It enables control of multiclass information flow propagation through two parameters: 1) the number of communication servers and 2) the communication service rate. A two-layer model is derived to characterize the IFPW under the designed queuing strategy. Analytical and numerical solutions are derived to investigate the effects of the two control parameters on information propagation performance in different information classes.

Third, this dissertation also develops a real-time implementable cooperative control mechanism for CAV platoons. Recently, model predictive control (MPC)-based platooning strategies have been developed for CAVs to enhance traffic performance by enabling cooperation among vehicles in the platoon. However, they are not deployable in practice as they require anembedded optimal control problem to be solved instantaneously, with platoon size and prediction horizon duration compounding the intractability. Ignoring the computational requirements leads to control delays that can deteriorate platoon performance and cause collisions between vehicles. To address this critical gap, this dissertation first proposes an idealized MPC-based cooperative control strategy for CAV platooning based on the strong assumption that the problem can be solved instantaneously. It then develops a deployable model predictive control with first-order approximation (DMPC-FOA) that can accurately estimate the optimal control decisions of the idealized MPC strategy without entailing control delay. Application of the DMPC-FOA approach for a CAV platoon using real-world leading vehicle trajectory data shows that it can dampen the traffic oscillation effectively, and can lead to smooth deceleration and acceleration behavior of all following vehicles.

Finally, this dissertation also develops a multiclass traffic assignment model for mixed traffic flow of CAVs and HDVs. Due to the advantages of CAVs over HDVs, such as reduced value of time, enhanced quality of travel experience, and seamless situational awareness and connectivity, CAV users can differ in their route choice behavior compared to HDV users, leading to mixed traffic flows that can significantly deviate from the single-class HDV traffic pattern. However, due to a lack of quantitative models, there is limited knowledge on the evolution of mixed traffic flows in a traffic network. To partly bridge this gap, this dissertation proposes a multiclass traffic assignment model. The multiclass model captures the effect of knowledge level of traffic conditions on route choice of both CAVs and HDVs. In addition, it captures the characteristics of mixed traffic flow such as the difference in value of time between HDVs and CAVs and the asymmetry in their driving interactions, thereby enhancing behavioral realism in the modeling. New solution algorithms will be developed to solve the multiclass traffic assignment model. The study results can assist transportation decision-makers to design effective planning and operational strategies to leverage the advantages of CAVs and manage traffic congestion under mixed traffic flows.

This dissertation deepens our understanding of the characteristics and phenomena in domains of traffic information dissemination, traffic flow dynamics and network equilibrium flow in the age of connected and autonomous transportation. The findings of this dissertation can assist transportation managers in designing effective traffic operation and planning strategies to fully exploit the potential of CAVs to improve system performance related to traffic safety, mobility and energy consumption.

Collaborative Research: Coordinated Real-Time Traffic Management Based on Dynamic Information Propagation and Aggregation under Connected Vehicle Systems

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• Civil Engineering

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Game-Theoretic and Set-Based Methods for Safe Autonomous Vehicles on Shared Roads

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Autonomous Systems Lab

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Motion Planning for Autonomous Vehicles in Urban Scenarios: A Sequential Optimization Approach

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• Control Systems, Robotics and Automation

Autonomous Vehicles & Artificial Intelligence Laboratory (AVAILab)

Multidisciplinary laboratory focused on developments and applications within the fields of mathematical modelling, optimisation, soft & natural computing, self-organisation & swarm robotics, autonomous navigation, computer vision, and positioning systems..

Dr Daizy Rajput (2023). Optimal Transmission System for Energy-Efficient Hybrid Electrified Powertrains . Coventry University. Supervised by Dr Arash M. Dizqah  (PI, University of Sussex), Dr Mauro S. Innocente  (DoS), Dr José M. Herreros  (University of Birmingham)

Paolo Grasso (2022). Towards an autonomous wildfire suppression system based on swarms of self-organising drones . Coventry University. Supervised by Dr Mauro S. Innocente

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Beyond the Limits: The Making of MARTYKhana

Making cars safer by programming them to  drift.

To ensure safety in the widest possible range of scenarios, automated vehicles must be able to react rapidly if needed. When trying to maneuver quickly, it is critical to consider that if you rotate the car too aggressively, it can become unstable and start to spin out.

The conventional approach to dealing with this phenomemon, that underpins Electronic Stability Control (ESC) and other similar systems, is to restrict the vehicle to stay within conservative limits wherein it is always stable. This is a  trade-off : we sacrifice agility, in exchange for making it easy for an average driver - or naive automated system - to control.

One can access a much wider range of maneuvers - and therefore, avoid accidents in a larger number of scenarios - by understanding how to control a vehicle  beyond the stability limits.  Expert drivers in drifting competitions, for example, can precisely position the car while purposefully operating in unstable conditions. Automated vehicles have the opportunity - and the responsibility - to be much better than the average driver, and thereby remove the need for this trade-off.

The Stanford News article,  ‘Automated Vehicle Control Beyond the Stability Limits’ , describes the lab’s recent contributions to controlling automated vehicles in these unstable situations. The highlight is a video that shows MARTY - the lab’s electric DeLorean - autonomously drifting through a challenging kilometer-long course.

To accompany the article, this page highlights information about the lab’s automated drifting research, the MARTY test vehicle, and additional media resources.Additional Uncut Video Footage

To accompany the videos from the article, uncut video footage from a complete run of this course is presented from three different perspectives: aerial, interior, and a camera mounted on the roof of the car.

Additional Uncut Video Footage

Aerial View

Interior View

Roof Mounted Camera View

If you're going to build an autonomous drifting car, why not do it with some style?

MARTY is a 1981 DMC DeLorean that has been extensively modified to serve as a flexible testbed for automated control at and beyond the limits of handling.

More detailed information on the build is available here.

The PhD thesis  Automated Vehicle Control Beyond the Stability Limits  by Jonathan Goh describes this research in detail, including the experiments on MARTY. The full manuscript is publicly available through the  Stanford Library .

The locations of the cones that demarcate the course are shown here, in relative East-North coordinates. This map is also available as a vector  PDF .

The cones are divided into three categories: inside of the turn, outside of the turn, and transition cones. The transition cones are closer to the centerline of the vehicle path, and represent a narrower corridor that the vehicle should pass through at low sideslip; these are represented by haybales in the video. The relative East-North coordinates of the  outside ,  inside , and  transition cones  are also available in .CSV format.

Towards Automated Vehicle Control Beyond the Stability Limits: Drifting Along a General Path

• Vehicle Dynamics and Control At The Limits of Handling

A Controller for Automated Drifting Along Complex Trajectories

• Conference Proceeding

Simultaneous Stabilization and Tracking of Basic Automobile Drifting Trajectories

MARTY Drifts Figure 8s

The Dynamic Design Lab's autonomous electric DeLorean, MARTY, repeatedly executes a highly dynamic figure 8 drifting maneuver. During the rapid transitions between +/- 40 degrees of drift angle, the vehicle steers lock-to-lock in about a second, reaching yaw rates as high as 120 deg/s. By studying how to control a vehicle in these extreme situations, the researchers are helping to make autonomous vehicles safer.

MARTY 'Cassette-Tape' Autonomous Drifting Test

This video of MARTY doing a 'cassette-tape' maneuver was first presented at the AVEC conference in Beijing, on July 17, 2018.

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MARTY with Doors Up at Thunderhill

MARTY Drifts on the Thunderhill Skidpad

MARTY Large Figure 8 Photocomposite

Sunset View of MARTY at Thunderhill

MARTY Systems

MARTY drifts on the Thunderhill skidpad

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Nonlinear Model Predictive Control for Autonomous Vehicles

Author: Paolo Falcone ; Chalmers Tekniska Högskola. ; Chalmers University Of Technology. ; [2007]

Keywords: TEKNIKVETENSKAP ; TECHNOLOGY ;

Abstract: In this thesis we consider the problem of designing and implementing Model Predictive Controllers (MPC) for stabilizing the dynamics of an autonomous ground vehicle. For such a class of systems, the non-linear dynamics and the fast sampling time limit the real-time implementation of MPC algorithms to local and linear operating regions. This phenomenon becomes more relevant when using the limited computational resources of a standard rapid prototyping system for automotive applications. In this thesis we first study the design and the implementation of a nonlinear MPC controller for an Active Font Steering (AFS) problem. At each time step a trajectory is assumed to be known over a finite horizon, and the nonlinear MPC controller computes the front steering angle in order to follow the trajectory on slippery roads at the highest possible entry speed. We demonstrate that experimental tests can be performed only at low vehicle speed on a dSPACE rapid prototyping system with a frequency of 20 Hz. Then, we propose a low complexity MPC algorithm which is real-time capable for wider operating range of the state and input space (i.e., high vehicle speed and large slip angles). The MPC control algorithm is based on successive on-line linearizations of the nonlinear vehicle model (LTV MPC). We study performance and stability of the proposed MPC scheme. Performance is improved through an ad hoc stabilizing state and input constraints arising from a careful study of the vehicle nonlinearities. The stability of the LTV MPC is enforced by means of an additional convex constraint to the finite time optimization problem. We used the proposed LTV MPC algorithm in order to design AFS controllers and combined steering and braking controllers. We validated the proposed AFS and combined steering and braking MPC algorithms in real-time, on a passenger vehicle equipped with a dSPACE rapid prototyping system. Experiments have been performed in a testing center equipped with snowy and icy tracks. For both controllers we showed that vehicle stabilization can be achieved at high speed (up to 75 Kph) on icy covered roads. This research activity has been supported by Ford Research Laboratories, in Dearborn, MI, USA.

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Motion planning for autonomous flights : algorithms, systems, and applications

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Autonomous formation flying in low earth orbit

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Formation flying is commonly identified as the collective usage of two or more cooperative spacecraft to exercise the function of a single monolithic virtual instrument. The distribution of tasks and payloads among fleets of coordinated smaller satellites offers the possibility to overcome the classical limitations of traditional single-satellite systems. The science return is enhanced through observations made with larger, configurable baselines and an improved degree of redundancy can be achieved in the event of failures. Different classes of formation flying missions are currently under discussion within the engineering and science community: technology demonstration missions, synthetic aperture interferometers and gravimeters for Earth observation, multi-spacecraft interferometers in the infrared and visible wavelength regions as a key to new astrophysics discoveries and to the direct search for terrestrial exoplanets. These missions are characterized by different levels of complexity, mainly dictated by the payload metrology and actuation needs, and require a high level of on-board autonomy to satisfy the continuously increasing demand of relative navigation and control accuracy. This dissertation presents the first realistic demonstration of a complete guidance, navigation and control (GNC) system for formation flying spacecraft in low Earth orbit. Numerous technical contributions have been made during the course of this research in the areas of formation flying guidance, GPS-based relative navigation, and impulsive relative orbit control, but the primary contribution of this thesis does not lie in one or more of these disciplines. The innovation and originality of this work stems from the design and implementation of a comprehensive formation flying system through the successful integration of various techniques. This research has led to the full development, testing and validation of the GNC flight code to be embedded in the on-board computer of the active spacecraft of the PRISMA technology demonstration. Furthermore key guidance and control algorithms presented here are going to be demonstrated for the first time in the TanDEM-X formation flying mission. Overall this thesis focuses on realistic application cases closely related to upcoming missions. The intention is to realize a practical and reliable way to formation flying: a technology that is discussed and studied since decades but is still confined in research laboratories. Hardware-in-the-loop real-time simulations including a representative flight computer and the GPS hardware architecture show that simple techniques, which exploit the natural orbit motion to full extent, can meet the demanding requirements of long-term close formation-flying.

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The Zhang Lab explores and studies biological diversity to understand nature and discover systems and processes that may be harnessed through bioengineering for the improvement of human well-being.

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Developing Programmable Therapeutics Can we accelerate the development of new therapeutics? We aim to create modular systems that interchangeably combine a therapeutic molecule, such as a gene editing construct, and a delivery vehicle. By focusing on creating compatible and extensible platforms for both intervention and delivery, we can rapidly generate a large number of therapeutics tailored for a wide range of contexts.

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Dr. Zhang is a molecular biologist focused on improving human health. He played an integral role in the development of two revolutionary technologies, optogenetics and CRISPR-Cas systems, including pioneering the use of Cas9 for genome editing and discovering CRISPR-Cas12 and Cas13 systems and developing them for therapeutic and diagnostic applications. Current research in the Zhang laboratory is centered on the discovery of novel biological systems and processes, uncovering their mechanisms, and developing them into molecular tools and therapies to study and treat human disease. Zhang is a core member of the Broad Institute, an Investigator at the McGovern Institute for Brain Research, the James and Patricia Poitras Professor of Neuroscience at MIT, and a Howard Hughes Medical Investigator. He is also a member of the National Academy of Sciences, the National Academy of Medicine, and the American Academy of Arts and Sciences as well as a fellow in the National Academy of Inventors.

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A thesis submitted for examination at the University of Birmingham must be solely the postgraduate researcher’s own work (except where University Regulations permit the inclusion of appropriately referenced collaborative research or work – see Regulation 7.4.1 . A postgraduate researcher must not employ a ‘ghost writer’ to write parts or all of the thesis, whether in draft or as a final version, on his/her behalf.

Editors, whether they are formal supervisors, informal mentors, family or friends or professional, need to be clear about the extent and nature of help they offer in the editing of University of Birmingham PGRs theses and dissertations. Supervisors of PGRs also need to be clear about the role of the third party editors as well as their own editorial role.

PGRs may use third party editorial assistance (paid or voluntary) from an outside source.  This must be with the knowledge and support of supervisors and the use of third party editorial assistance must be stated in the thesis acknowledgement page.

A ‘third party’ editor cannot be used :

• To change the text of the thesis so as to clarify and/or develop the ideas and arguments;
• To reduce the length of the thesis so it falls within the specified word limit;
• To correct information within the thesis;
• To change ideas and arguments put forward within the thesis; and/or
• To translate the thesis into English.

A ‘third party’ editor can be used to offer advice on:

• Spelling and punctuation;
• Formatting and sorting of footnotes and endnotes for consistency and order;
• Ensuring the thesis follows the conventions of grammar and syntax in written English;
• Shortening long sentences and editing long paragraphs;
• Changing passives and impersonal usages into actives, vice versa as may be appropriate;
• Improving the positioning of tables and illustrations and the clarity, grammar, spelling and punctuation of any text in or under tables and illustrations; and
• Ensuring consistency of page numbers, headers and footers.

Where a third party editor is used it is the PGR’s responsibility to provide the third party editor with a copy of this statement (Word - 20KB)  and ensure they complete the Third Party Editor Declaration Form (Word - 32KB)  confirming their compliance with this statement.

When submitting the thesis the PGR must record in the Acknowledgements page the form of contribution the ‘third party’ editor has made, by stating for example, “this thesis was copy edited for conventions of language, spelling and grammar by ABC Editing Ltd”.

Please also see the Code of Practice on Academic Integrity .

 Intellectual property rights

These rights generally belong to the student, but if your work is considered to be commercially significant students may be required to assign their rights to the University. 

For further information please see:

• University Regulation 5.4 covering Intellectual Property
• Regulation 3.16 covering Patents and The Exploitation of Inventions
• The Copyright for Researchers webpage

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Geosciences Princeton University

Congratulations to dr. naomi intrator for successfully defending her ph.d. thesis.

Anti-racism author accused of plagiarising ethnic minority academics

Robin DiAngelo alleged to have copied parts of doctoral thesis from Asian-American scholars

The bestselling author of a book about “white fragility” has been accused of plagiarising sections of the work of two Asian-Americans in her doctoral thesis.

Robin DiAngelo, an anti-racism consultant who argues that racial divisions have been entrenched by “defensive” white people, committed 20 cases of plagiarism, according to a complaint filed with her alma mater, the University of Washington.

Ms DiAngelo’s book White Fragility became a New York Times bestseller when it was published in 2018, and also experienced a surge in popularity following the death of George Floyd and the Black Lives Matter protests in 2020.

The 67-year-old has previously written about the importance of properly attributing the work of ethnic minority writers in a section on her website about how white people must “continually educate” themselves on race.

Her thesis allegedly lifts two paragraphs from Thomas Nakayama, an Asian-American professor with Northeastern University, and his co-author, Robert Krizek, without attribution, The Washington Free Beacon reported .

In making its case the newspaper published large excerpts from her work alongside the text she is accused of copying, with the similarities highlighted in red.

In one section, Prof Nakayama and Prof Krizek wrote: “While this discourse recognises a part of its historical constitution … this reflexivity does not necessarily mean that there has been a recognition of the power relations embedded in that history.”

Similarly, Ms DiAngelo wrote in her 2004 thesis: “While this discourse recognises in part a historical constitution, this does not necessarily indicate that there is a recognition of the power relations embedded in that history.”

Her “Whiteness in Racial Dialogue” dissertation is also reported to have lifted material from Stacey Lee, an Asian-American professor of education, summarising the work of a third scholar.

Prof Lee wrote that David Theo Goldberg “argues that the questions surrounding racial discourse should focus not so much on how true stereotypes are, but on how the truth-claims they offer are a part of a larger worldview, and what forms of action that worldview authorises”.

Ms DiAngelo wrote: “Goldberg … argues that the questions surrounding racial discourse should not focus so much on how true stereotypes are, but how the truth claims they offer are a part of a larger worldview that authorises.”

‘Never appropriate’

Peter Wood, the president of the National Association of Scholars, likened the practice to “forgery.”

“It is never appropriate to use the secondary source without acknowledging it, and even worse to present it as one’s own words,” said Mr Wood, a former provost of Boston University. He added: “That’s plagiarism.”

Ms DiAngelo has previously emphasised the importance of providing proper academic citation, writing on her website: “Always cite and give credit to the work of BIPOC [black, indigenous and people of colour] people who have informed your thinking.”

She added: “When you use a phrase or idea you got from a BIPOC person, credit them.”

The University of Washington defines plagiarism as “borrowing the structure of another author’s phrases or sentences” without credit, or citing a source but reproducing their exact words without quotation marks.

Among her other alleged examples of plagiarism, Ms DiAngelo seemingly lifts two sentences from Bronwyn Davies, a professorial fellow at the University of Melbourne .

Both write of how “an individual emerges through the processes of social interaction” as “one who is constituted and reconstituted through the various discursive practices in which they participate”.

“It does look like plagiarism,” Prof Davies told The Washington Free Beacon.

In her book, Ms DiAngelo characterised “white fragility” as the “defensive moves that white people make when challenged racially, characterised by emotions such as anger, fear, and guilt”, entrenching racial inequalities.

Ms DiAngelo and her publisher, Beacon Press, have been approached for comment.

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