ACIT4620 Computational Intelligence: Theory and Applications Course description

Computational Intelligence is concerned with modern, bio-inspired approaches to artificial intelligence (AI) and is an umbrella term for the fields of neural networks (NN), fuzzy systems (FS) and evolutionary computation (EC). This course offers a comprehensive and systematic introduction to the fundamental concepts, principles, and methods in the three fields, a part of machine learning and deep learning, and several advanced topics (neuro-fuzzy systems, neuro-evolution, or fuzzy clustering). The course will illustrate major CI concepts, principles and methods using various application examples in engineering, biomedicine and business. In addition, the overview, history, state-of-the-art, and future trends of AI and CI field will be covered. The main modules for lectures include:

• AI and CI: Overview and history
• Fundamentals of neural networks
• Introduction to deep learning
• Fuzzy sets, logic and systems
• Topics in evolutionary computation
• Advanced topics
• AI and CI: State-of-the-art and future

On completion of the PhD Programme in Engineering Science, each student shall have achieved the following learning outcomes, in accordance with the Norwegian Qualifications Framework for Lifelong Learning:

Knowledge

On graduation, the student:

• is at the forefront of knowledge within the engineering science topic of his/her thesis and masters the field's scientific theories, principles and methods.
• is at the forefront of knowledge in his/her professional field of engineering
• has breadth of knowledge and an ability for cross-disciplinary work in engineering science.
• can evaluate the expediency and application of theories, methods and processes in research, scholarly projects and professional engineering projects specific to his/her field of engineering.
• can contribute to the development and documentation of new knowledge and methods within her/his field of engineering science.

Skills

On graduation, the student can:

• formulate research questions, plan and conduct independent research and scholarly work within engineering science.
• carry out independent research and scholarly work at a high international level.
• deal with complex professional issues with an academic approach and reflect critically on established knowledge and practice in the field.
• apply technologies, scientific methods, digital and simulation tools suitable for solving complex engineering problems.
• develop innovative, sustainable engineering solutions and transform the latest scientific discoveries into enabling new technologies.

General competence

On graduation, the student can:

• identify, discuss and reflect upon ethical and societal implications of his/her own research as well as of the applications it enables.
• produce scientific publications and communicate research and development work through recognised national and international channels.
• participate in debates and present his/her research at national and international fora.
• assess the need for, initiate and drive innovation.

Students are expected to have the following learning outcomes in terms of knowledge, skills and general competence.

Knowledge

On successful completion of the course, the students have:

• an overview on different perspectives, history and future of AI and Computational Intelligence (CI) fields.
• familiarity with the essential terminologies, concepts, ideas, elements and principles in the three pillar fields of CI.
• an in-depth understanding of state-of-the-art CI methods (fuzzy systems, neural networks, evolutionary computation, deep learning, and hybrid AI techniques).
• knowledge and understanding of open problems and future challenges and opportunities in the AI and CI field.

Skills

On successful completion of the course, the students can:

• determine when to use and deploy the CI methods learned for real-world applications.
• apply appropriate CI models and algorithms to address modeling and optimization problems in real-world applications.
• analyze complex and uncertain datasets with CI algorithms.

General competence

On successful completion of the course, the students can:

• program the CI models/algorithms.
• deploy CI systems/models in real-world applications.
• solve complex search, optimization or decision-making problems using evolutionary algorithms.

The course consists of lectures (theory), labs (practical exercises and computer simulations/experiments), group discussions, Q&As, as well as group projects. The group projects will be assigned from a list of the suggested topics/areas. The students will work in groups and finally submit the project report as well as the code.

Practical exercises: Lab and Q&A sessions.

The following two group assignments must be approved before the student can take the final exam:

• 1 - Group report and presentation: Group written report and oral presentation on the assigned topic.
• 2 - Group project proposal: A group project proposal (1000 - 1200 words) on the assigned topic, containing project description, the available dataset(s), method/algorithm to be employed, and references (including several most recent journal publications).

The final exam consists of two parts:

• Part 1 - Group project report with code: A group (2-4 students) project implementation, including a project report (5000 - 7000 words, excluding references) and code as an appendix (counts 50% towards the final grade). Both the code and the report will be evaluated. The comprehensiveness of the code is evaluated under the assumption that each member of the group has worked on the project for 60 hours.
• Part 2 - Individual written exam: An individual, closed-book, written exam (3 hours) (counts 50% towards the final grade)

Both parts must be passed in order to pass the course (i.e., if a student fails in one part, they automatically fail the course).

The exam results can be appealed.

New/postponed exam

In case of failed exam or legal absence, the student may apply for a new or postponed exam. New or postponed exams are offered within a reasonable time span following the regular exam. The student is responsible for registering for a new/postponed exam within the time limits set by OsloMet. The Regulations for new or postponed examinations are available in Regulations relating to studies and examinations at OsloMet.

All aids are permitted for the group project, provided the rules for plagiarism and source referencing are complied with (Exam - Part 1).

For the closed-book, individual written exam (Exam - Part 2), students will work on a computer in an exam room (with invigilators), can use pen and a simple, non-programmable calculator, but will not have access to Internet, books, notes or other aids.

The legal basis for this plan is laid down in Act of 1 April 2005 No. 15 relating to universities and university colleges and in the Regulations relating to the Degree of Philosophiae Doctor (PhD) at OsloMet - Oslo Metropolitan University (hereinafter referred to as "PhD Regulations").

The PhD Programme in Engineering Science is firmly rooted in the broad international tradition of PhD studies in engineering technology and engineering science. The programme builds on the scientific strengths of the engineering departments at the Faculty of Technology, Art and Design and on the research groups at Simula Metropolitan Center for Digital Engineering (SimulaMet).

The programme supports the needs for highly qualified expertise in engineering in industry, the public sector and in academia. The programme prepares students for positions in industry as well as in academia, and is designed to ensure that they are able to take on demanding and important roles in the private and public sectors, where in-depth expertise and knowledge of engineering science are required.

In this PhD programme, the term engineering science is defined as follows:

Engineering science is a discipline that concerns with the physical and mathematical basis of engineering and technology. In the modern world it implies chemical engineering, electrical engineering, computer science, bioengineering, civil engineering, mechanical engineering, aeronautical engineering and environmental engineering.

The three key elements of this definition are applied mathematics and physics in the broad sense, engineering and technology. The interrelationship between these terms is as follows: from the basis of applied mathematics and physics, engineers are able to understand physical phenomena, which in applied form leads to engineering solutions to problems in society. Technology can be seen both as the tool used in the engineering process and as the result of the process itself.

In the PhD programme, the students are exposed to applied mathematics and physics, engineering and technology in the context of developing products and solutions for the advancement and well-being of society. This will be done through a doctoral thesis (150 ECTS credits), compulsory coursework in research methods and ethics (10 ECTS credits), and elective coursework in various aspects of engineering science (20 ECTS credits).

The thesis will address a defined set of challenges in society, and will consist of research into the application and development of knowledge in applied mathematics, physics, engineering and/or technology to address these challenges. 

The programme is aimed at persons with a background in engineering, information technology and similar technological disciplines who wish to acquire research skills at the highest level within the field of engineering science, and who wish to obtain a skillset that is valuable both in an academic research setting and in society as a whole.

On completion of the programme, the students will be qualified for careers in engineering and engineering management, in advanced technical consulting, and in research and teaching at universities and research institutes

The programme will build on a master's degree in an engineering discipline, applied mathematics or physics, or a similar master's degree relevant to the PhD programme.

Formal requirements:

3.1.Norwegian master's degree in an engineering discipline, applied mathematics or physics worth 120 ECTS

OR

3.2.Foreign degree-equivalent in an engineering discipline, applied mathematics or physics, equivalent to a master's degree in the Norwegian higher education system. In cases where the foreign master¿s degree does not comprise 120 ECTS, admission may be granted subject to individual assessment, provided the qualification presented grants access to PhD studies in the country of origin.

3.3.The average grade awarded for the bachelor's degree must not be lower than a C.

3.4.The average grade awarded for the master's degree must not be lower than a B.

3.5.A minimum grade of B must be awarded to the master's thesis.

Documentation of the completed education on which the decision regarding admission should be based (certified copies of original certificates) must be submitted.

Students seeking admission to the programme, must submit an application providing the following information:

1. A description of the research work that will lead to the thesis. This description shall consist of:

• A problem statement that is related to a societal problem that can be solved - completely or partly - through engineering preferably pointing out interdisciplinary aspects.
• A project plan describing the background and identifying a research gap to demonstrate that the student has an overview of the research field.
• The project plan should include a proposed research design to solve the problem.
• A milestone plan for finishing the thesis.
• A publication plan.
• A plan for internationalisation.
• Specification of language in which the dissertation will be written
• Information about any possible restrictions connected to intellectual property rights that may affect the planned project.
• If the project calls for special academic or material resources, this must be documented in the application.

2. A list of coursework to fulfill the 30 ECTS coursework requirement

3. Supervisor's signature

4. A funding plan.

5. An account of prospective judicial and/or ethical issues the project may present.

6. Information on whether the project requires approval by research ethics committees, other public authorities or private actors. This kind of approval should be collected pre-submission when possible, and attached to the application.

Excellent English language skills are required for all participants in this PhD programme. International students must document this before appointment by taking one of the following tests and achieving the stipulated minimum total scores:

• TOEFL - Test of English as a Foreign Language, internet-based test (IBT). Minimum total score: 92. Or Paper based test with a minimum score of 600
• IELTS - International English Language Testing Service. Minimum overall band score: 6.5. Certificate in Advanced English (CAE) and Certificate of Proficiency in English (CPE) from the University of Cambridge.
• PTE Academic - Pearson Test of English Academic. Minimum overall score: 62.

The following applicants are exempt from the abovementioned language requirements:

• Applicants from EU/EEA countries
• Applicants who have completed one year of university studies in Australia, Canada, Ireland, New Zealand, the UK or the US
• Applicants with an International Baccalaureate (IB) diploma

Decisions on admissions are based on an overall assessment of the applications. The doctoral committee at the Faculty of Technology, Art and Design at OsloMet shall consider admission applications.

Admissions to the PhD Programme in Engineering Science are considered on an ongoing basis. Pursuant to the PhD Regulations, section 2-6, admission to PhD programmes is formalised by a written contract between the PhD student, the supervisor(s) and the Faculty of Technology, Art and Design.

An application for admission to the PhD programme should normally be submitted within three (3) months after the start of the research project which will lead to the degree.