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Research Methods

Short name: RM
SITS code: COIY055H7
Credits: 15
Level: 7
Module leader: Michael Zakharyaschev

Module outline

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


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 16 October 2019. The first lecture is followed by refreshments, giving an opportunity for students and staff to meet each other.

Learning Outcomes

Outline of Lectures

Lecture 1 and Lecture 2:

16 Oct. 2019 (Wed), 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.

16 Oct. 2019 (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 3:

29 Oct. 2019 (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:

5 Nov. 2019 (Tue), 18:00-21:00, Room 151. Logic and Language Theory Part II - Roman Kontchakov.
Topics covered: Logical systems and complexity of reasoning.

Lecture 5:

13 Nov. 2019 (Wed), 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.

13 Nov. 2019 (Wed), 19:00-21:00, Room 151. Graph algorithms: from Theory to Practice - Felix Reidl.
Topics covered: Network Science vs Graph Theory. A roadmap to "practical" algorithms. Case studies: Motif-counting, Flow decomposition of RNA sequences, Metagenome neighbourhoods.

Lecture 6:

19 Nov. 2019 (Tue), 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 7:

26 Nov. 2019 (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 8:

4 Dec. 2019 (Wed), 18:00-20:00, Room 151. Machine Learning - George Magoulas.
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 9:

10 Dec. 2019 (Tue), 18:00-21:00, Room 151. Satifiability-Based Problem Solving - Carsten Fuhs.
Topics covered: SAT solving, SMT solving, practical applications.

Lecture 10:

14 Jan. 2020 (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 11:

14 Jan. 2020 (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 12:

21 Jan. 2020 (Tue), 18:00-20:00, Room 151. Experimental Analysis of distributed systems - Stelios Sotiriadis.
Topics covered: Experimental analysis and benchmarking process: how to use real world workloads for database systems (SQL, NoSQL), systems workload generation, introduction to benchmarking and evaluating big data processing frameworks (Hadoop, Spark and other) using a variety of benchmarks (microbenchmarks, machine learning models, SQL, websearch, graph and streaming benchmarks on Hadoop).

Lecture 13:

21 Jan. 2020 (Tue), 20:00-21:00, Room 151. Pursuing research in Computer Gaming. - Keith Mannock.
Topics covered: Areas for gaming; techniques; models; educational gaming; languages; testing and evaluation.

Lecture 14:

28 Jan. 2020 (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 15:

04 Feb. 2020 (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 16:

11 Feb. 2020 (Tue), 18:00-21:00, Room 151. Oded Lachish

Reviewing the Research Literature
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.

Writing Papers and the Review Process
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.

Writing the PhD Thesis and the PhD Examination Process
Topics covered: Planning the thesis. Writing the thesis. Thesis structure. Writing up schedule. The oral examination.


All dates and timetables are listed in programme handbooks, found in the downloads section of individual programme pages.

Enrolled students can find their personal teaching timetable and location of classes on their My Birkbeck profile.