Page 303 - Postgraduate Catalog 2026-27

302 303

(LLMs), covering their architecture, introduce advanced autonomy DEN723 – Advanced Intelligent image analysis, encouraging students experimental or analytical results, and
training paradigms, and system-level concepts including behavior cloning, Software Development to work on collaborative projects, discussion of findings, demonstrating PhD in
considerations. Students explore path-tracking methods such as pure Credit Hours: 3 produce technical reports, and the candidate’s ability to contribute
agentic AI workflows, including pursuit, and the robotics software engage in research assignments to meaningfully to the advancement of Engineering
tool use and multi-step reasoning, architecture using ROS. Students Prerequisite: Graduate status demonstrate their understanding. intelligent systems engineering and
through hands-on design and gain practical experience with robot This course provides students with related disciplines. Doctoral research Management
implementation using modern modeling, coordinate frames, sensor an advanced hands-on experience DEN735 – Special Topics in is expected to produce original
frameworks. The course concludes data flow, mapping, localization, of recent advancements in mobile Intelligent Systems insights and scholarly outputs that
with generative and multimodal and navigation within simulated and Internet computing technologies Credit Hours: 4 expand knowledge and support
deep learning applications, including robotic environments. The course and their applications. Students Prerequisite: Graduate status innovation in the field.
generative models, 3D and vision– concludes with emerging approaches design multiple advanced mobile and Core Courses
language intelligence, and real-world in robotics using foundation models Progressive Web Applications (PWAs). This course will include advanced Successful completion of the
deployment scenarios such as object and multimodal AI, including vision- The course begins by covering topics of contemporary interest in dissertation requirement is
tracking, detection, deep diagnostics, language and vision-language-action technologies including Android MLKit, selected areas of intelligent systems demonstrated through a formal DEN701 – Advanced Probability
and federated learning. Assessment systems that enable higher-level CameraX, and Ionic and use them engineering. Particular topics vary dissertation defense before the and Stochastic Processes
is based on proctored assignments, reasoning and decision making in to develop AI-powered features in from term to term depending on Dissertation Committee. During the
a course project, a review paper, autonomous robots. Throughout addition to navigation, persistence, the interests of the students and the defense, the candidate presents Credit Hours: 3
and a final presentation, enabling the course, students implement and localization. Students also specialties of the instructor. the research contributions and Prerequisite: Graduate status
students to develop both practical and extend real robotic algorithms, experience integration of advanced responds to technical questions and This course provides an advanced
implementation skills and critical evaluate system performance, services for machine learning and scholarly evaluation by the committee exploration of probability and
analysis abilities using TensorFlow and document their work in computer vision by off-loading, Research Dissertation members. stochastic processes, emphasizing
and Keras. technical reports and a final project. external API access, and on-device The committee assesses the their applications in modern
The emphasis is on integrating originality, technical depth,
DEN775 – Advanced Intelligent perception, control, and intelligent implementation. Students also learn DEN799 – PhD Research methodological rigor, and significance engineering and scientific fields.
Robots decision making into complete how to externally train and import Dissertation of the research, as well as the Topics include probability theory,
AI models to mobile applications.
Credit Hours: 3 autonomous systems. Students work on utilizing AI services Credit Hours: 30 candidate’s ability to articulate and discrete and continuous random
variables, probability distribu-tions,
Prerequisite: Graduate status DEN733 – Advanced Edge AI to solve complex problems from Prerequisite: Completed 8 Credit defend the findings in a professional joint distributions, and statistical
The objective of this course is to Credit Hours: 3 different domains. Hours academic setting inference methods. Students will
provide students with advanced, Prerequisite: Graduate status DEN721 – Advanced Intelligent The final and central requirement The dissertation course sequence gain in-depth knowledge of random
processes, including stationary and
hands-on experience in autonomous Vision Systems for awarding the Ph.D. degree in is structured as a series of stages,
robotics systems that integrate This course focuses on the Credit Hours: 3 Intelligent Systems Engineering DEN799A, DEN799B, DEN799C, Gaus- sian processes, as well as their
sensing, perception, control, and integration and optimization of is the successful completion of a and DEN799D, followed by the final applications in signal processing
and communication systems.
modern AI techniques. Through a artificial intelligence at the network Prerequisite: Graduate status significant and original independent dissertation defense. The dissertation
sequence of guided laboratories and edge, focusing on real-time This course provides an in-depth research project that demonstrates phase must be completed over a The course highlights the role of
probability in modeling, analysis, and
a major project, students develop computing frameworks and the study of computer vision and image advanced technical competence, minimum of four regular Fall or
and analyze autonomous vehicle intersection of AI with embedded processing techniques, focusing on scholarly rigor, and the ability to Spring semesters. Summer terms, decision-making under uncertainty,
capabilities using both classical systems through scholarly research both foundational and advanced generate new knowledge in the if offered, may support research equip- ping students with skills to
solve real-world problems. Research-
robotics methods and contemporary and practical application. It delves topics. The areas of study include field. The dissertation represents the activities but do not substitute for
machine learning approaches. The into computation models, embedded digital image acquisition, rep- culmination of the doctoral program the required minimum number of focused projects will enable students
to design and evaluate stochastic
course begins with foundations operating systems, real-time systems, resentation, and color processing; 2-D and provides evidence that the regular semesters unless formally
in system design and embedded and middleware with an emphasis and 3-D image transforms and point candidate has developed the capacity approved by the graduate program. models for complex systems,
interaction, including state-based on research method-ologies for operations; image filtering techniques to design, conduct, and communicate Each stage corresponds to a Fall or fostering a deeper understanding of
their implications in engineering and
modeling, signal communication, evaluating performance metrics, for edge detection and morphological high-quality research consistent with Spring semester and represents a
and sensor-driven behaviors such multi-objective optimization, and operations; feature detection, image professional and academic standards. defined milestone in the doctoral scientific innovations.
as line following. It then progresses energy management in embedded registration, and contour analysis; The dissertation involves the research lifecycle, including proposal DEN702 – Advanced Research
to perception and control for AI applications. The course prepares and image matching, transformations, systematic investigation of a clearly development, progress evaluation, Communication
autonomous navigation, including students to conduct rigorous and advanced local features like SIFT defined research problem through research implementation, and Credit Hours: 3
PID control, computer vision for research and develop innovative and MSER. Students will use MATLAB the application of appropriate dissertation completion. Students
lane detection, and integration of solutions for AI deployment in edge, to implement these techniques in theoretical frameworks, research are required to demonstrate Prerequisite: Graduate status
vision with control systems. Students fog, and cloud architectures, aligning lab exercises and projects, apply- methodologies, data collection and satisfactory progress at each stage This course teaches advanced written
further explore modern perception with advanced scholarly activities in ing their knowledge to develop analysis techniques, and critical before enrolling in the subsequent and oral communication skills to
techniques such as object detection the field. solu-tions for real-world challenges interpretation of results. stage to ensure steady advancement graduate students. It covers the
using YOLO, object tracking, such as background segmentation The completed dissertation document toward the successful completion and fundamentals of research including
segmentation, and filtering methods and object tracking. The course presents the research background, defense of the doctoral dissertation. methodologies, and ethics. The
used in robotics. Later modules emphasizes practical applications in literature review, methodology,

Abu Dhabi University | Postgraduate Catalog 2026 - 2027 Abu Dhabi University | Postgraduate Catalog 2026 - 2027