Download Research Projects List 2015

International Relations Office
Dear University Partners,
We would like to welcome your undergraduate students to apply for a Summer Research
Attachment at National University of Singapore (NUS) which will take place from May/June to
September 2015 for a period of minimum 8 weeks. Longer attachments of 12 weeks are strongly
encouraged.
Your students are welcome to apply for a position from a list of pre-defined research projects below.
If your students are interested in projects outside this list, they are encouraged to browse the
websites of NUS faculties and research institutes and identify a project/research area that interests
them or a faculty member they wish to work with.
Faculty of Engineering
http://www.eng.nus.edu.sg/research/R_focus.htm
Faculty of Science
http://www.science.nus.edu.sg/about-fos/aboutfos-overview/departments
School of Computing
http://www.comp.nus.edu.sg/research/
Faculty of Arts and Social
Sciences
http://www.fas.nus.edu.sg/research/index.html
School of Business
http://bschool.nus.edu.sg/FacultyDepartments/ExpertiseGuide/tabid/589/Default.aspx
School of Design and
Environment
http://www.sde.nus.edu.sg/rsh/SDE_rsh_overview.html
Faculty of Law
http://law.nus.edu.sg/research_publications/research_area.asp
University-level Research
Institutes/Centres
http://www.nus.edu.sg/dpr/research/university.html
Deadlines and Important Dates:
Students Nomination to NUS:
Selection by NUS faculties:
8 March 2015
18 March 2015
Application Procedure
The following documents are required of students who wish to apply for a research attachment at
NUS.
- NUS Application Form (Annex 1)
- Updated CV
- A Recommendation Letter
- A Copy of Academic Transcript
3rd Storey, Unit 03-03, Shaw Foundation Alumni House, 11 Kent Ridge Drive, Singapore 119244
Tel: (65) 6516 4356 Fax: (65) 6778 0177
Website: www.nus.edu.sg/iro
Company Registration Number: 200604346E
Research Projects List 2015
(for undergraduate students only)
Project
Number
Research Title
Number of
Vacancies
Host Department
1.
Family and Population Studies in Asia
2
Centre for Family and Population
Research (CFPR), Faculty of Arts and
Social Sciences
2.
Integrating Safety Considerations into
Construction Process Simulations
2
Department of Building, School of
Design and Environment
3.
Evaluation of an Individualised Mobility
Analysis and Rehabilitation System (iMARS)
2
Department of Computer Science,
School of Computing
4.
Migrating out of Poverty Research Programme
Consortium: Intra-household Dynamics,
Migration Industry and Policy Processes
1
5.
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
6.
Contributing to the Development of a Shape
Grammar Interpreter
1
Department of Architecture, School of
Design and Environment
7.
Cooperative Brains: EEG Hyper-Connectivity
Between Operator Pairs whilst Actively
Performing Demanding Interdependent Goaloriented Tasks
1
Singapore Institute for
Neurotechnology (SINAPSE),
Cognitive Engineering Laboratory
8.
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
9.
Neural Bases of Creativity
1
Singapore Institute for
Neurotechnology (SINAPSE),
Cognitive Engineering Laboratory
1
Singapore Institute for
Neurotechnology (SINAPSE),
Cognitive Engineering Laboratory
2
Singapore Institute for
Neurotechnology (SINAPSE),
Cognitive Engineering Laboratory
10.
11.
Social Brains: EEG Hyper-connectivity
between Operator Pairs whilst Actively
Performing Demanding Interdependent GoalOriented Tasks
Concurrent EEG/fMRI: Neuroimaging Of Brain
Activity and Connectivity with High Spatial And
Temporal Resolution
Asia Research Institute
12.
Dynamic Connectomics of Lower Limb Motor
Cortex for Exoskeleton Robots
1
Singapore Institute for
Neurotechnology (SINAPSE),
Cognitive Engineering Laboratory
13.
The Controlled Activation of Carbon-Boron
Bonds
1
Department of Chemistry, Faculty of
Science
Total Number of Projects Available: 13
Page 2 of 18
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:
http://www.fas.nus.edu.sg/cfpr/
http://profile.nus.edu.sg/fass/socywj/stf_socywj.htm
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.
2.
3.
Number of vacancies:
2
Description of student required:
Literature review on factors that affect China and India’s population change
Project documentation and research analysis
Administration in the Centre for Family and Population Research
Faculty / School
Field of Specialisation
Arts and Social Sciences







Prerequisites and other
requirements (if any):
Nil
Financial Support (from host):
Nil
Page 3 of 18
Chinese Language
Chinese Studies
Economics
Geography
Psychology
Social Work
Sociology
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:
http://www.bdg.nus.edu.sg/People/Faculty/staff_bdggym.htm
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:
Project Description:
1.
2.
3.
4.
Learning Objectives:
1.
2.
3.
Number of vacancies:
2
Description of student
required:
Prerequisites and other
requirements (if any):
Financial Support (from host):
Identify and document the key processes of the site
Collect data from sites, e.g. time taken for different activities, number of
plants used, common unsafe behaviours and safety rules
Derive probability functions of different parameters and heuristic rules
used by workers
Develop a hybrid simulation model of the work process
Appreciate the factors influencing productivity
Appreciate the factors influencing construction safety and health
Develop a simple simulation model of construction activities
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
- 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
Nil
Page 4 of 18
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:
www.smcnus.org
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.
2.
Number of vacancies:
2
Effective communication within a multidisciplinary research team
Designing and/or testing technology solutions in populations with special
considerations (e.g., the elderly, patients)
Faculty / School
Field of Specialisation

Computer Science

E-Commerce

Computer Engineering

Information Systems
Computing
Description of student
required:
Engineering


Computer
Electrical
Science


Physics (Physics in Technology)
Statistics
Design and Environment

Industrial Design
Prerequisites and other
requirements (if any):
-
Financial Support (from host):
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
Nil
Page 5 of 18
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:
http://www.ari.nus.edu.sg/people_details.asp?peopleid=121&categoryid
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
1.
Learning Objectives:
2.
3.
Number of vacancies:
Develop library research skills leading to a better understanding of migration,
development and poverty issues in Southeast Asia
Learn fieldwork skills through participation in a research project that combines
quantitative and qualitative research
Acquire teamwork and cross-cultural sensibilities by working in a transnational
research team involving academics and NGO practitioners
1
Faculty / School
Description of student
required:
Arts and Social Sciences
Prerequisites and other
requirements (if any):
-
Financial Support (from host):
Nil
Field of Specialisation

Geography

Sociology

South Asian Studies

Southeast Asian Studies
Ability to speak Bahasa Indonesia is an advantage
Research interests in migration and Southeast Asia preferred
Page 6 of 18
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:
http://www.arch.nus.edu.sg/people/cv/rudi.htm
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.
Project Description:
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.
2.
3.
Number of vacancies:
Description of student
required:
Prerequisites and other
requirements (if any):
Financial Support (from host):
The application of performance analysis to urban planning or design
Insight into the use of data mining to alleviate data issues in urban planning
or design
Contribute to research
1
Faculty / School
Field of Specialisation
Design and Environment
Architecture
Urban design or planning skills
Nil
Page 7 of 18
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:
http://www.arch.nus.edu.sg/people/cv/rudi.htm
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.
Project Description:
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.
2.
3.
Number of vacancies:
Gain an understanding of the workings of a shape grammar interpreter
Contribute to the continued development of the SortalGI “sortal grammar”
interpreter
Contribute to research
1
Page 8 of 18
Description of student
required:
Faculty / School
Computing
Field of Specialisation

Any
Science

Applied Mathematics
Prerequisites and other
requirements (if any):
Computer programming (Java and/or Python)
Financial Support (from host):
Nil
Page 9 of 18
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:
http://www.sinapseinstitute.org/projects/cognitiveengr/
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.
2.
3.
Number of vacancies
1
Description of student
required:
Understand the experiment design for hyper connectivity studies
Obtain the skills of electro-physiological signal processing
Obtain the skills for hyper connectivity analysis
Faculty / School
Computing
Field of Specialisation

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
Page 10 of 18
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:
http://www.sinapseinstitute.org/projects/cognitiveengr/
The association of functional connectivity patterns with particular cognitive tasks
has long been a topic of interest in neuroscience. However, the highdimensionality 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.
Project Description:
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.
2.
3.
Number of vacancies:
1
Obtain the skills of electro-physiological signal processing
Obtain the skills of electro-physiological functional connectivity analysis
Obtain the skills for machine learning
Faculty / School
Field of Specialisation

Computing
Description
required:
of
student
Engineering
Computer Science
Knowledge of MATLAB, Shell scripts, Signal Processing
and Computational Intelligence ToolBox required


Computer
Electrical
Knowledge of MATLAB, Shell scripts, Signal Processing
and Computational Intelligence ToolBox required
Science
Prerequisites
and
requirements (if any):
other
Financial Support (from host):

Statistics
As above
Nil
Page 11 of 18
PROJECT 9
Research Title:
Neural Bases of Creativity
Supervisor / Department:
Professor Tassos Bezerianos
Singapore Institute for Neurotechnology (SINAPSE), Cognitive Engineering Lab.
Link to host’s online bio /
research page:
http://www.sinapseinstitute.org/projects/cognitiveengr/
Innovation is a key quality of leadership and an indispensable property of
evolutionary procedures. Creative ideas, as the basis of innovation, are intrinsic
mental processes of the human species that played a crucial role in human
evolution and resulted to great social, technological and medical breakthroughs.
The Cognitive Engineering group in the Singapore Institute for Neurotechnology
(SINAPSE) is currently using sophisticated, multi-modal imaging methods to
study the brain at work so as to study the neural bases of creative thinking.
The Cognitive Engineering group is interested in studying neural processes
leading to creative ideas by mapping and comparing the brain networks that are
activated during generating new creative ideas and during recalling already
existing ones. Brain mapping will be based on experimental data collected with
electroencephalography (EEG) and will be analysed in terms of functional
connectivity measures and graph theoretic properties.
Project Description:
The Cognitive Engineering Group in SINAPSE is seeking a highly motivated and
committed student to assist in collection and analysis of EEG data as a subproject of this ongoing work. The ideal candidate should have a background in
psychology or neuroscience and a keen interest in working in the rapidlygrowing field of cognitive neuroscience. Previous experience working with
human experimental participants is desirable.
Learning Objectives:
1.
2.
3.
Number of vacancies
1
Understand the electro-physiological mechanism of creative thinking
Obtain the skills of electro-physiological signal processing
Become familiar with graph theory models
Faculty / School
Field of Specialisation

Psychology
Arts and Social Sciences
Knowledge of MATLAB, Shell scripts required


Description
required:
of
student
Computer Science
Computer Engineering
Computing
Knowledge of MATLAB, Shell scripts and Signal
Processing ToolBox required
Engineering



Bioengineering
Computer
Electrical
Knowledge of MATLAB, Shell scripts and Signal
Processing ToolBox required
Prerequisites
and
requirements (if any):
other
Financial Support (from host):
As above
Nil
Page 12 of 18
PROJECT 10
Research Title:
Social 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:
http://www.sinapseinstitute.org/projects/cognitiveengr/
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 interactions, and a new method to
quantify the neural hyper connectivity extending their previous analysis using
source localisation to graph theoretical approach on cross participant function
connectivity.
Project Description:
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.
2.
3.
Number of vacancies:
1
Understand the experiment design for hyper connectivity studies
Obtain the skills of electro-physiological signal processing
Obtain the skills for hyper connectivity analysis
Faculty / School
Field of Specialisation

Computer Science
Computing
Knowledge of MATLAB, Shell scripts required
Description
required:
of


student
Computer
Electrical
Engineering
Knowledge of MATLAB, Shell scripts and Signal
Processing required
Science
Prerequisites
and
requirements (if any):
other
Financial Support (from host):

Statistics
As above
Nil
Page 13 of 18
PROJECT 11
Research Title:
Concurrent EEG/fMRI: Neuroimaging Of Brain Activity and Connectivity with
High Spatial And Temporal Resolution
Supervisor / Department:
Professor Tassos Bezerianos
Singapore Institute for Neurotechnology (SINAPSE), Cognitive Engineering Lab.
Link to host’s online bio /
research page:
http://www.sinapseinstitute.org/projects/cognitiveengr/
Functional neuroimaging has been a major tool for cognitive neuroscience,
experimental psychology, and psychiatry. Among non-invasive imaging
techniques, EEG and fMRI provide tremendous benefits to better understanding
of the brain mechanisms behind mental processes, such as perception,
attention, learning, etc. Although they both have limitations when used alone,
their combination becomes a powerful tool for studying brain functions with high
spatial and temporal resolution.
Project Description:
The Cognitive Engineering Group in SINAPSE uses concurrent EEG/fMRI
recordings to investigate brain activity and connectivity responsible for mental
fatigue. For multi-modal data analysis, the Group is first looking for an effective
method to remove gradient artefacts and BCG artefacts from EEG signals
acquired inside the MRI scanner. After the data is cleaned, cortical connectivity
patterns from each modality, i.e., electrophysiological and metabolic, will be
investigated based on graph theoretical analysis. The Group is also developing
advanced methods to implement multi-modal data fusion.
The Cognitive Engineering Group in SINAPSE is seeking a highly motivated and
committed student for EEG/fMRI data analysis. The candidate is expected to be
confident with applied mathematics and programming for the data analysis
using Matlab and shell scripts. Students who are familiar with machine learning
techniques are also welcome.
Learning Objectives:
1.
2.
3.
Number of vacancies
Understand the neural mechanism of mental fatigue
Obtain the skills of electro-physiological signal processing and EEG/fMRI
data analysis
Develop a suitable method for EEG/fMRI data fusion
2
Faculty / School
Arts and Social
Sciences
Computing
Description of student
required:
Field of Specialisation

Psychology

Computer Science
Knowledge of MATLAB, shell scripts, Signal Processing
ToolBox required


Computer
Electrical
Engineering
Knowledge of MATLAB, shell scripts, Signal Processing
ToolBox required
Science




Applied Mathematics
Mathematics
Physics
Statistics
Knowledge of MATLAB, Shell Scripts, Machine Learning
ToolBox required
Page 14 of 18
Prerequisites and other
requirements (if any):
As above
Financial Support (from host):
Nil
Page 15 of 18
PROJECT 12
Research Title:
Dynamic Connectomics of Lower Limb Motor Cortex for Exoskeleton Robots
Supervisor / Department:
Professor Tassos Bezerianos
Singapore Institute for Neurotechnology (SINAPSE), Cognitive Engineering Lab.
Link to host’s online bio /
research page:
http://www.sinapseinstitute.org/projects/cognitiveengr/
The purpose of the research is to apply machine learning on brain (EEG) and
muscle (EMG) signals to improve control strategies of lower limb exoskeleton,
which might help lower limb rehabilitation for stoke patients. In this stage of the
research, the aim is to find a way to make use of machine learning techniques
to identify different lower limbs (leg) activities.
Project Description:
EEG will be recorded during the experiments when the participants raise their
legs or imaging doing it. After signal processing, the data will be used for feature
extraction and classification.
The Cognitive Engineering Group in SINAPSE is seeking highly motivated and
committed student to assist us processing and classifying the EEG data. The
candidate is expected to be confident with applied mathematics and
programming for data analysis using Matlab or Python, a prior knowledge of
machine learning will be a plus.
1.
Learning Objectives:
Number of vacancies:
2.
3.
Understand how research looks like in the field of neural
science/engineering
Obtain the skills of electro-physiological signal processing
Obtain the basic machine learning skills for classification/feature extraction
1
Faculty / School
Field of Specialisation

Computer Science
Computing
Good Math background required
Description of student
required:


Computer
Electrical
Engineering
Knowledge of Signal processing, Machine learning
required
Science
Prerequisites and other
requirements (if any):
As above
Financial Support (from host):
Nil

Statistics
Page 16 of 18
PROJECT 13
Research Title:
The Controlled Activation of Carbon-Boron Bonds
Supervisor / Department:
Assistant Professor Rowan Young
Department of Chemistry, Faculty of Science
Link to host’s online bio /
research page:
http://www.chemistry.nus.edu.sg/people/academic_staff/youngdr.html
Project Description:
The controlled formation and cleavage of Carbon-Boron bonds has played a
crucial role in the ongoing development of organic chemistry over the previous
few decades. The cleavage of Carbon-Boron bonds has led to new
methodologies for not only the formation of Carbon-Boron bonds but for the
instalment of practically any functional group. Furthermore, protocols for the
formation of Carbon-Boron bonds from readily available and largely inert
Carbon-Hydrogen bonds under mild reaction conditions have matured over the
last 10 years. The installation of Boronate groups through such methods offers
unique selectivity and functional group tolerance not otherwise achievable via
other common carbon-boron bond forming methods. Key to both the formation
and cleavage of Carbon-Boron bonds is the transmetalation of organic groups
either from or to Boron. Despite the importance of the transmetalation step in
organoborane based reactions, the way in which this occurs is still debated, with
contradictory experimental evidence arising from even subtle variations in
reaction conditions. Although such mechanisms have been studied extensively
in silico, experimental evidence rests largely on kinetic evidence, and
mechanistic model systems are under-represented for this important reaction
step.
This project endeavours to develop pincer based ligands to lend understanding
to Carbon-Boron bond breaking and (through micro-reversibility) bond forming
reactions. Furthermore, alternate reaction pathways induced by conformational
demands encroached by the pincer systems will be explored with the possibility
of developing novel carbon-carbon bond forming methodologies. Systems will
be designed to create divergent reaction pathways incurring transmetalation via
either sigma-bond metathesis or oxidative addition of a Carbon-Boron bond.
Learning Objectives:
1.
2.
3.
Number of vacancies:
Description of student
required:
Acquire laboratory techniques for air-sensitive chemistry
Gain fundamental knowledge and understanding of organometallic
transformation
Acquire the ability to plan, conduct and present research
1
Faculty / School
Field of Specialisation
Science

Prerequisites and other
requirements (if any):
Enrolled as a Chemistry major
Financial Support (from host):
Nil
Chemistry
Page 17 of 18
International Relations Office
ANNEX 1: NUS Application Form
SUMMER UNDERGRADUATE RESEARCH EXCHANGE
PROGRAMME
NUS APPLICATION FORM
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Current Studies
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Proposed Research Attachment at National University of Singapore (NUS)
I’d like to apply for a research project predefined in the Research Project List.
I’d like to apply for a research project outside the Research Project List.
Research Subject
Host Institute/Laboratory
Researcher’s Name or Email Address
1
2
3
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A statement discussing research subjects, motivation and relevant qualifications and skills (500 words
maximum)
3rd Storey, Unit 03-03, Shaw Foundation Alumni House, 11 Kent Ridge Drive, Singapore 119244
Tel: (65) 6516 4356 Fax: (65) 6778 0177
Website: www.nus.edu.sg/iro
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