Skip to content Search
Search our website:

Research Methods

Organised by Michael Zakharyaschev
Department of Computer Science and Information Systems
Birkbeck, University of London

Aims

This is a short course on research methods for research in Computer Science and Information Systems. The course does not have any coursework but it is part of our training programme for research students and research staff.
Attendance is compulsory for all first-year research students, both full-time and part-time, as well as MRes students. Other research students and research staff are most welcome to attend. The course will start on 18 October 2017. The second lecture on 24 October 2017 is followed by refreshments, giving an opportunity for students and staff to meet each other.

Outline of Lectures

Lecture 1:

18 Oct. 2017 (Wed), 19:30-20:30, Room 151. Simulation - George Magoulas.
Topics covered: The computer simulation approach: Importance of models. What is simulation? Time and randomness in simulation. Applications of simulation. How a simulation model works? The process of simulation. The elements of a simulation model. Performing simulation studies. Examples.

Lecture 2:

24 Oct. 2017 (Tue), 18:00-19:00, Room 151. Introduction (followed by drinks and snacks) - Mark Levene.
Topics covered: How to get a PhD. The CSIS Birkbeck PhD programme. Developing a research proposal. Planning your research. The wider community. Resources and Tools. Having a grounding in Computer Science. Career development.

Lecture 3:

31 Oct. 2017 (Tue), 18:00-19:30, Room 151. Logic and Language Theory Part I - Peter Wood.
Topics covered: Automata and formal languages, with applications to database research.

Lecture 4:

2 Nov. 2017 (Thu), 18:00-21:00, Room 151. Logic and Language Theory Part II - Roman Kontchakov.
Topics covered: Logical systems and complexity of reasoning.

Lecture 5:

8 Nov. 2017 (Wed), 18:00-20:00, Room 151. Data Research Methods in Computer Vision - Steve Maybank.
Topics covered: Digital images, image compression, linear classification, application of probabilities, salience.

Lecture 6:

8 Nov. 2017 (Wed), 20:00-21:00, Room 151. Machine Learning - Dell Zhang.
Topics covered: What is machine learning and how does it relate to other disciplines; Basic concepts and techniques of machine learning illustrated with examples; Various applications of machine learning.

Lecture 7:

14 Nov. 2017 (Tue), 18:00-19:00, Room 151. Information Systems - Dave Wilson.
Topics covered: Ontology and epistemology of IS research viz-a-viz Research in Computer Science. Common Methods in IS Research: Case study, Action research, Ethnography. Mixing methods in a research project.

Lecture 8:

14 Nov. 2017 (Tue), 19:00-20:00, Room 151. Pursuing Collaborative Research - Life Sciences Informatics - Nigel Martin.
Topics covered: Pursuing collaborative research. What is life sciences informatics? Genomics and proteomics. Life sciences informatics techniques and resources. Challenges for the computer scientist: biological data management, biological data analysis. Current research themes and approaches.

Lecture 9:

21 Nov. 2017 (Tue), 18:00-21:00, Room 151. Theoretical Computer Science - Trevor Fenner.
Topics covered: Design and analysis of algorithms. Computational complexity and computability. Formal models of computation. Mathematical models: discrete mathematics, graph theory, probability.

Lecture 10:

28 Nov. 2017 (Tue), 18:00-21:00, Room 151. Parameterised algorithms. - Igor Razgon.
Topics covered: Runtime of an algorithm, polynomial runtime, NP-hardness, ways to cope with NP-hardness. Fixed-parameter tractability, examples of parameterised algorithms. Fixed-parameter intractability.

Lecture 11:

9 Jan. 2018 (Tue), 18:00-19:00, Room 151. What Makes Good Research in Software Engineering? - Keith Mannock.
Topics covered: Problem selection, research paradigm, and validation of results.

Lecture 12:

9 Jan. 2018 (Tue), 19:15-20:15, Room 151. Programming Languages as a research topic​. - Keith Mannock.
Topics covered: Why might we need a new language? Syntax, semantics, and execution. Do I need to write a whole language? Testing and evaluation.

Lecture 13:

16 Jan. 2018 (Tue), 18:00-19:00, Room 151. Pursuing Collaborative Research with Arts, Humanities and Social Sciences - Alex Poulovassilis.
Topics covered: Challenges of pursuing collaborative research. Methodology approaches. Exemplars of collaborative research projects in learning technologies and digital humanities.

Lecture 14:

16 Jan. 2018 (Tue), 19:00-20:00, Room 151. Reviewing the Research Literature - Oded Lachish.
Topics covered: Finding out about your research area. Literature search strategy. Writing critical reviews. Identifying venues for publishing your research. Preparing and submitting research papers.

Lecture 15:

23 Jan. 2018 (Tue), 18:00-19:00, Room 151. Pursuing research in Computer Gaming. - Keith Mannock.
Topics covered: Areas for gaming; techniques; models; educational gaming; languages; testing and evaluation.

Lecture 16:

23 Jan. 2018 (Tue), 19:00-20:00, Room 151. Writing Papers and the Review Process. - Oded Lachish.
Topics covered: The conference review process. Making use of the referees' reports. Preparing and presenting your paper. The journal
review process. Group exercise in reviewing research papers.

Lecture 17:

6 Feb. 2018 (Tue), 18:00-20:00, Room 151. Ubiquitous and Pervasive Computing - George Roussos.
Topics covered: The ubiquitous computing paradigm, elements of ubiquitous computing, auto-identification, sensing, actuation, networking, trust, applications, conducting experimental research in ubiquitous computing.

Lecture 18:

14 Feb. 2018 (Wed), 18:00-19:00, Room 151. Writing the PhD Thesis and the PhD Examination Process - Alex Poulovassilis.
Topics covered: Planning the thesis. Writing the thesis. Thesis structure. Writing up schedule. The oral examination.