Research Projects List 2015

(for undergraduate students only)

Project Number / Research Title / Number of Vacancies / Host Department
Family and Population Studies in Asia / 2 / Centre for Family and Population Research (CFPR), Faculty of Arts and Social Sciences
Integrating Safety Considerations into Construction Process Simulations / 2 / Department of Building, School of Design and Environment
Evaluation of an Individualised Mobility Analysis and Rehabilitation System (iMARS) / 2 / Department of Computer Science, School of Computing
Migrating out of Poverty Research Programme Consortium: Intra-household Dynamics, Migration Industry and Policy Processes / 1 / Asia Research Institute
The Application of Data Mining to Support Performance Analysis in Urban
Design/Planning: A Case Study / 1 / Department of Architecture, School of Design and Environment
Contributing to the Development of a Shape Grammar Interpreter / 1 / Department of Architecture, School of Design and Environment
Cooperative Brains: EEG Hyper-Connectivity Between Operator Pairs whilst Actively Performing Demanding Interdependent Goal-oriented Tasks / 1 / Singapore Institute for Neurotechnology (SINAPSE), Cognitive Engineering Laboratory
Characterisation of Brain States in Multi-task, Multi-workload Experiments: Machine Learning Techniques for EEG Signal Analysis / 1 / Singapore Institute for Neurotechnology (SINAPSE), Cognitive Engineering Laboratory
Neural Bases of Creativity / 1 / Singapore Institute for Neurotechnology (SINAPSE), Cognitive Engineering Laboratory
Social Brains: EEG Hyper-connectivity between Operator Pairs whilst Actively Performing Demanding Interdependent Goal-Oriented Tasks / 1 / Singapore Institute for Neurotechnology (SINAPSE), Cognitive Engineering Laboratory
Concurrent EEG/fMRI: Neuroimaging Of Brain Activity and Connectivity with High Spatial And Temporal Resolution / 2 / Singapore Institute for Neurotechnology (SINAPSE), Cognitive Engineering Laboratory
Dynamic Connectomics of Lower Limb Motor Cortex for Exoskeleton Robots / 1 / Singapore Institute for Neurotechnology (SINAPSE), Cognitive Engineering Laboratory
The Controlled Activation of Carbon-Boron Bonds / 1 / Department of Chemistry, Faculty of Science
Total Number of Projects Available: 13
PROJECT 1
Research Title: / Family and Population Studies in Asia
Supervisor / Department: / Professor Yeung Wei-Jun, Jean
Centre for Family and Population Research (CFPR), Faculty of Arts and Social Sciences
Link to host’s online bio / research page: /

Project Description: / Work involved includes:
-Assist in data analysis that involves China and India’s population and family changes
-Literature review for research projects prepare documentation for the study, administrative work involved in the project, descriptive statistic work if possible
-Assist in the work related to summer training workshops offered by CFPR
CFPR has many interdisciplinary faculty members who can supervise the intern.
Learning Objectives: /
  1. Literature review on factors that affect China and India’s population change
  2. Project documentation and research analysis
  3. Administration in the Centre for Family and Population Research

Number of vacancies: / 2
Description of student required: / Faculty / School / Field of Specialisation
Arts and Social Sciences /
  • Chinese Language
  • Chinese Studies
  • Economics
  • Geography
  • Psychology
  • Social Work
  • Sociology

Prerequisites and other requirements (if any): / Nil
Financial Support (from host): / Nil
PROJECT 2
Research Title: / Integrating Safety Considerations into Construction Process Simulations
Supervisor / Department: / Assistant Professor Goh Yang Miang
Department of Building, School of Design and Environment
Link to host’s online bio / research page: /
Project Description: / The aim is for the interns to model processes in a construction site or precast yard in Singapore and use the model to improve the efficiency of the processes while balancing safety concerns. The students are expected to conduct the following tasks under the guidance of a full-time research assistant and the reporting officer:
  1. Identify and document the key processes of the site
  2. Collect data from sites, e.g. time taken for different activities, number of plants used, common unsafe behaviours and safety rules
  3. Derive probability functions of different parameters and heuristic rules used by workers
  4. Develop a hybrid simulation model of the work process

Learning Objectives: /
  1. Appreciate the factors influencing productivity
  2. Appreciate the factors influencing construction safety and health
  3. Develop a simple simulation model of construction activities

Number of vacancies: / 2
Description of student required: / Faculty / School / Field of Specialisation
Business /
  • Operations & Supply Chain Management

Computing /
  • Business Analytics

Design and Environment /
  • Project & Facilities Management

Engineering /
  • Civil
  • Computer
  • Engineering Science
  • Industrial & Systems

Prerequisites and other requirements (if any): / -Able to communicate in English and willing to work on construction sites
-Knowledge of basic statistics and probability
-Experience in simulation (e.g. discrete event simulation) and/or Java programming preferred
Financial Support (from host): / Nil
PROJECT 3
Research Title: / Evaluation of an Individualised Mobility Analysis and Rehabilitation System (iMARS)
Supervisor / Department: / Associate Professor Wang Ye
Department of Computer Science, School of Computing
Link to host’s online bio / research page: /
Project Description: / This project is in line with two of the core themes of the laboratory: (1) leveraging mobile (“smart”) technology platforms to create personalised solutions for healthcare delivery; and (2) translating large quantities of (meta)data into metrics and interfaces that are directly relevant to the needs of doctors, therapists, and researchers for various healthcare applications.
Learning Objectives: /
  1. Effective communication within a multidisciplinary research team
  2. Designing and/or testing technology solutions in populations with special considerations (e.g., the elderly, patients)

Number of vacancies: / 2
Description of student required: / Faculty / School / Field of Specialisation
Computing /
  • Computer Science
  • E-Commerce
  • Computer Engineering
  • Information Systems

Engineering /
  • Computer
  • Electrical

Science /
  • Physics (Physics in Technology)
  • Statistics

Design and Environment /
  • Industrial Design

Prerequisites and other requirements (if any): / -Motivated and self-driven ability to tackle new or unfamiliar concepts
-Ability to draw on skills and techniques from multiple disciplines (computer science, rehabilitation science, biostatistics)
-Willing to ask questions
-Familiar with designing and/or testing technology solutions in populations with special considerations (e.g., the elderly, patients)
-Excellent written and spoken English
-Background in programming (MATLAB/Python/Octave, SQL, Java, iOS/Android), smartphone app design, signal processing of sensor and/or accelerometry data and machine learning techniques is an advantage
Financial Support (from host): / Nil
PROJECT 4
Research Title: / Migrating Out of Poverty Research Programme Consortium: Intra-household Dynamics, Migration Industry and Policy Processes
Supervisor / Department: / Professor Brenda Yeoh
Asia Research Institute
Link to host’s online bio / research page: /
Project Description: / The Research Assistant will be required to assist in the following tasks:
-Library research and literature review relating to migration and poverty alleviation in South and Southeast Asia
-Editing and formatting documents/reports
-Assisting with questionnaire design and conducting surveys in Singapore
-Transcribing and/or translation work for qualitative interviews
-Organising academic workshops and dissemination meetings
-Simple clerical/office duties such as photocopying and scanning
Learning Objectives: /
  1. Develop library research skills leading to a better understanding of migration, development and poverty issues in Southeast Asia
  2. Learn fieldwork skills through participation in a research project that combines quantitative and qualitative research
  3. Acquire teamwork and cross-cultural sensibilities by working in a transnational research team involving academics and NGO practitioners

Number of vacancies: / 1
Description of student required: / Faculty / School / Field of Specialisation
Arts and Social Sciences /
  • Geography
  • Sociology
  • South Asian Studies
  • Southeast Asian Studies

Prerequisites and other requirements (if any): / -Ability to speak Bahasa Indonesia is an advantage
-Research interests in migration and Southeast Asia preferred
Financial Support (from host): / Nil
PROJECT 5
Research Title: / The Application of Data Mining to Support Performance Analysis in Urban
Design/Planning: A Case Study
Supervisor / Department: / Associate Professor Rudi Stouffs
Department of Architecture, School of Design and Environment
Link to host’s online bio / research page: /
Project Description: / The student will apply his/her knowledge and skills of urban planning or design towards the development and execution of a case study involving data mining to support performance analysis for urban planning or design. The student will assist a PhD researcher, whose research is focused on investigating and demonstrating the applicability of data mining to urban planning and design, with the development of a case study to demonstrate a specific application of data mining in the context of performance analysis for urban planning or design.
The student may introduce an urban planning/design brief/solution that he/she has worked on previously, or select a brief from urban planning or design education at NUS. In relationship to this brief, and in consultation with the PhD researcher, the student will identify one or more performance aspects that would benefit from the application of a performance analysis technique or tool to quantitatively (and qualitatively) assess this or these performance aspects. Subsequently, the investigation is focused on any barriers that may impede the assessment of these performance aspects or the application of selected performance analysis techniques or tools is. For example, these could be missing input data for a particular tool or technique, e.g., the lack of sufficiently detailed design data. Subsequently, an approach will be devised to use data mining in overcoming these barriers. For example, input data may be synthesised from other data sets, or cases may be extracted from other data sets for the application of case-based reasoning. The final objective is to develop a computational workflow, in collaboration with the PhD researcher, which applies data mining to enable the quantitative (and qualitative) assessment of one or more performance aspects within an urban planning or design case study.
The work will mainly consist of these five steps:
  1. Collect urban information in relation to the brief
  2. Identify the issues to be investigated
  3. Define the analyses to be performed
  4. Identify where data mining may assist the analysis and design process
  5. Identify a computational workflow that ties everything together

Learning Objectives: /
  1. The application of performance analysis to urban planning or design
  2. Insight into the use of data mining to alleviate data issues in urban planning or design
  3. Contribute to research

Number of vacancies: / 1
Description of student required: / Faculty / School / Field of Specialisation
Design and Environment / Architecture
Prerequisites and other requirements (if any): / Urban design or planning skills
Financial Support (from host): / Nil
PROJECT 6
Research Title: / Contributing to the Development of a Shape Grammar Interpreter
Supervisor / Department: / Associate Professor Rudi Stouffs
Department of Architecture, School of Design and Environment
Link to host’s online bio / research page: /
Project Description: / The student will contribute to the development of a Shape Grammar Interpreter. Shape grammars are a formal rewriting system for producing languages of shapes. Shape grammars commonly consider only shapes composed of line segments and points, the latter with labels as attributes, but the concept of shape grammars can easily be extended to other types of data relevant to design. “Sortal grammars” are a formalism (or rather, a class of formalisms) for design grammars that extends on shape grammars and “colour grammars”, both of which allow for (a limited) variation in the formalism they prescribe.
Shape grammar interpreters are difficult to implement. Part of the difficulty stems from technical considerations, e.g., relating to representational, mainly geometric, issues and relating to emergence. Recognising emergent shapes requires determining a transformation under which a shape is a part of the original shape. Another part of the difficulty is developing ways of enabling designers to employ grammatical rules in a manner that does not impede their act of designing. The latter is not a focus of this project, though enabling others to use the shape grammar interpreter here developed in addressing this difficulty is.
SortalGI is a “sortal grammar” interpreter under development for the processing programming environment. The student will contribute to the development of this grammar interpreter in one of three possible ways, to be selected based on the student’s skills and interests:
  1. Addressing known technical problems of the grammar interpreter in the Java language. Student will gain an understanding of the workings of the grammar interpreter and of its implementation architecture, and develop and implement technical solutions for existing issues
  2. Re-implementing parts of the grammar interpreter in the Python language. Student will gain an understanding of the workings of the grammar interpreter and its implementation architecture, and develop and implement a similar architecture in Python
  3. Exploring the use of Rosetta, a Programming Language for Generative Design, to enable access to the grammar interpreter in the Java language from the Python language. Student will gain a specific understanding of Rosetta and a general understanding of grammar interpreters, and develop and implement basic access to the grammar interpreter in the Java language from the Python language.

Learning Objectives: /
  1. Gain an understanding of the workings of a shape grammar interpreter
  2. Contribute to the continued development of the SortalGI “sortal grammar” interpreter
  3. Contribute to research

Number of vacancies: / 1
Description of student required: / Faculty / School / Field of Specialisation
Computing /
  • Any

Science /
  • Applied Mathematics

Prerequisites and other requirements (if any): / Computer programming (Java and/or Python)
Financial Support (from host): / Nil
PROJECT 7
Research Title: / Cooperative Brains: EEG Hyper-Connectivity Between Operator Pairs whilst Actively Performing Demanding Interdependent Goal-oriented Tasks
Supervisor / Department: / Professor Tassos Bezerianos
Singapore Institute for Neurotechnology (SINAPSE), Cognitive Engineering Lab.
Link to host’s online bio / research page: /
Project Description: / Functional neuroimaging has been a major tool for cognitive neuroscience, experimental psychology, and psychiatry. Non-invasive high-resolution imaging would provide tremendous benefits to better understanding of the brain mechanisms behind mental processes, such as perception, attention, learning, etc. Although the traditional approach of functional neuroimaging is usually applied to a single participant at a time, there has been the emerging field of using functional neuroimaging to record the neural activity of multiple participants performing a task at the same time. The Cognitive Engineering Group in SINAPSE has previously conducted experiments exploring the interactions of pilot-copilot pairs during operation of a NASA flight simulator. The interaction between the brains was quantified by the temporal sequence of localised electrical activity sources.
The Cognitive Engineering Group in SINAPSE will develop a physics engine within a flight simulator to control for the pilot-copilot collaboration, and a new method to quantify the hyper connectivity between pilot and copilot, combining their previous analysis using source localisation with graph theoretical approach on cross-participants functional connectivity patterns.
The Cognitive Engineering Group in SINAPSE is seeking highly motivated and committed student for the data analysis of EEG and complex behavioural data. The candidate is expected to be confident with applied mathematics and programming for the data analysis using Matlab and shell scripts.
Learning Objectives: /
  1. Understand the experiment design for hyper connectivity studies
  2. Obtain the skills of electro-physiological signal processing
  3. Obtain the skills for hyper connectivity analysis

Number of vacancies / 1
Description of student required: / Faculty / School / Field of Specialisation
Computing /
  • Computer Science

Engineering /
  • Computer
  • Electrical

Science /
  • Applied Mathematics
  • Mathematics
  • Physics
  • Statistics

Prerequisites and other requirements (if any): / Knowledge of MATLAB, shell scripts, Signal Processing ToolBox
Financial Support (from host): / Nil
PROJECT 8
Research Title: / Characterisation of Brain States in Multi-task, Multi-workload Experiments: Machine Learning Techniques for EEG Signal Analysis
Supervisor / Department: / Professor Tassos Bezerianos
Singapore Institute for Neurotechnology (SINAPSE), Cognitive Engineering Lab.
Link to host’s online bio / research page: /
Project Description: / The association of functional connectivity patterns with particular cognitive tasks has long been a topic of interest in neuroscience. However, the high-dimensionality of the pairwise functional connectivity limits its usefulness in some real-time applications.
In an earlier completed study conducted by the Cognitive Engineering Group in SINAPSE, the methodology of tensor subspace analysis (TSA) was used to reduce the initial high-dimensionality of the pairwise coupling in the original functional connectivity network to a space of condensed descriptive power, which would significantly decrease the computational cost and facilitate the differentiation of brain states. The Group has previously tried to classify mental workload based on a single-task design where task difficulty was parametrically varied across blocks. However, it is unclear whether the Group’s method can be generalised across subjects or tasks.
The goal of this study is thus to utilise multiple task and workload levels in an attempt to create a more general classifier of mental workload. The Cognitive Engineering Group in SINAPSE is seeking highly motivated and committed student for the data analysis of EEG and complex behavioural data. The candidate is expected to be confident with applied mathematics and programming for the data analysis using Matlab and shell scripts.
Learning Objectives: /
  1. Obtain the skills of electro-physiological signal processing
  2. Obtain the skills of electro-physiological functional connectivity analysis
  3. Obtain the skills for machine learning

Number of vacancies: / 1
Description of student required: / Faculty / School / Field of Specialisation
Computing /
  • Computer Science
Knowledge of MATLAB, Shell scripts, Signal Processing and Computational Intelligence ToolBox required
Engineering /
  • Computer
  • Electrical
Knowledge of MATLAB, Shell scripts, Signal Processing and Computational Intelligence ToolBox required
Science /
  • Statistics

Prerequisites and other requirements (if any): / As above