data61-CSIRO Summer Research Scholarship
If you are enrolled in your final year of a bachelor degree or postgraduate by coursework program, this scholarship could provide financial assistance while you undertake a full-time research project for 12 weeks.
Value and duration
The scholarships are valued at $6000 each for the duration of 12 weeks during the summer of 2016/2017.
The project runs for 12 weeks from November 2016 to February 2017 (excluding the Christmas holiday period). The precise start and end dates of the project can be discussed with the project supervisor.
Number of scholarships available
To be eligible for this scholarship you must:
- be enrolled in your final year of a bachelor degree or postgraduate by coursework program with an interest in pursuing a PhD
- be studying in the field of electronic and communication, telecommunication, or software engineering, computer science, or IT
- have the relevant academic background stated in the project description
- be available to work full time (9am to 5pm, Monday to Friday) on your research project for the duration of the internship/scholarship
- select one of the projects described below
- attend the Summer Scholars Showcase event (date to be confirmed) to present your research findings
- be available to attend an interview for selection if requested.
As part of your application you will be asked to indicate your preferred area of research by selecting a project. Each project will be jointly supervised by RMIT University and data61-CSIRO researchers.
Massive Access Networks - A Stochastic Geometry Based Study
A/Prof Kandeepan Sithamparanathan (RMIT)
Dr Ming Ding (data61, CSIRO)
With the immense increase in the number of wireless network users, in order to improve spectral efficiency and effective throughput, massive access networks are being studied in the recent years. In this project the student is expected to study and characterize the performance of massive access network using the stochastic geometry tool/framework, considering massive IoT connections with small packets and periodic transmissions.
The student is expected to have a good background in probability and statistics, programming with
Matlab, and any prior knowledge in stochastic geometry will be an added advantage.
4G (LTE) Over Satellites
Dr Karina Gomez (RMIT),
A/Prof Kandeepan Sithamparanathan (RMIT)
Dr Ming Ding (data61, CSIRO)
The need to cover at least 99% of the population in a nation with 4G (LTE) is being continuously pushed by many governments around the world. Satellite technology is the only way to feasibly (and economically) cover regional areas with low population density in providing 4G services. In this project the student will study the state of the art on LTE over satellite and analyze the performance of various approaches to deliver 4G coverage via satellite. The student is also encouraged to propose an improved strategy for delivering 4G over satellite. The student will also focus on the satellite-to-ground channels, the energy efficiency issues and the impact of long latency on LTE protocols
The student is expected to have a good background in LTE and satellite communications, programming with Matlab, and programming with a network simulator such as OMNET++/NS3 will be an added advantage.
Scalable and Personalized Travel Itinerary Recommendation
Dr Jeffrey Chan (RMIT)
Dr Cheng Soon Ong (Data 61)
Kwan Hui Lim (UoM)
Tourism is an important industry involving more than a billion international tourists, who generated more than US$1.2 trillion of revenue in 2014. Despite the importance of the tourism industry, planning a tour itinerary remains a challenging and time-consuming task for tourists, especially in unfamiliar cities. Major touristic cities typically comprise hundreds of Points-of-Interests (POIs), which can be broadly classified under categories such as "Museums", "Cathedrals", "Shopping", among others. As tourists are often limited by time, the task of tour itinerary planning involves selecting a subset of POIs that are most relevant and interesting to the tourist, and then finding the most optimal route among these POIs that fulfils their available time for touring. Adding to the complexities of tour planning are various considerations such as preferring to start/end from a specific place (e.g., a tourist's hotel), having limited time to finish the tour (e.g., 5 hours), preference for certain transport modes (e.g., no walking more than 300m) and interest alignment between tourists and recommended POIs. These diverse considerations and the importance of tourism makes the problem of tour itinerary planning an interesting and significant research problem.
In this proposed research, we intend to utilize data mining approaches and combinatorial optimization techniques to solve the problem of tour itinerary planning. Geo-tagged photos will be the main dataset used as such photos are typically posted by tourists and indicative of their real-life visits. Data mining approaches will be then used to extract information about tourist visit patterns and determine the implicit interest preferences of tourists. Following which, we will formulate a formal representation of the tour itinerary planning problem as a combinatorial optimization problem such as the Orienteering problem. Solving this tour itinerary planning problem optimally is computationally intensive and we plan to speed up this process by: (i) clustering POIs based on their category and location to reduce the search space; and (ii) grouping similar users into broad tourist categories, and recommending personalized itineraries modified from template itineraries.
Real- time Secure Monitoring in IoT/Cloud Environment
A/Prof. Ibrahim Khalil (RMIT)
Prof. Arkady Zaslavsky (CSIRO)
The focus of the project is to remotely monitor various activities using IoT devices in a robust and secure manner. It also involves end-to-end IoT monitoring and sharing information using secure protocols in cloud infrastructure. The tasks of this project can be classified into various parts
a. Using two Arduinos to collect information from two sensors (light and temperature) and pass the information to be displayed graphically on a machine/virtual machine/cloud connected to these Arduinos using either Ethernet or wifi.
b. Collected information should be passed to a server/ cloud virtual machine (e.g. AWS) using MQTT protocol. The information can be fetched and displayed graphically on real time basis using MQTT as well.
c. Using key exchange mechanism initialize the connection between these two Arduinos and the machine/cloud. Once the secret exchange is achieved, any suitable symmetric encryption technique can be used.
Chiminey: Cloud-enabling Blockchain Verification
Nicholas May (eResearch),
Dr Maria Spichkova (RMIT)
Dr Mark Staples (data61)
With Treasury, DATA61 is currently evaluating Blockchain, a distributed transaction algorithm underlying Bitcoin. DATA61 are exploring the potential of disruptive applications such as in future Australian digital financial transaction or election processes. The software systems group in DATA61 has a long history of software verification notably in SEL4 but also in other applications to software dependability.
This summer project uses an existing blockchain model formalised in UPAAL as a plugin to Chiminey, a parallel cloud-enabling tool developed at RMIT for scientific software permitting massive parameterised parallelism and mapping parallel jobs to national compute centres such as the NCI, to the national cloud “NeCTAR” or to commercial clouds such as AWS, using their respective open source schedulers and software stacks. This summer project will follow a current student project in AICAUSE that enables Chiminey to coordinate parallel runs of the PRISM model checker.
The student work within the project will be divided in the following three stages:
Stage 1: An existing recent version of the open source UPPAAL model checker will be adapted as a Chiminey plugin, with a web browser interface for queries.
Stage 2: As a small case study, the existing blockchain model will be coded to be queried by CSIRO users exploring Blockchain technology.
Stage 3: The results of the project including the techniques for model-checker integration will be documented as a technical report that should provide a basis for a further research paper. As an indirect by product, this project may later be of bene_t to SEL4, to develop their own UPPAAL models of high-dependability software components; to integrate their own model checkers for parametric parallel execution.
Note: because of academic licences among other issues, this project will be wholly conducted at RMIT City campus. Some meetings may be arranged at CSIRO, Clayton.
Chiminey: Insect Surface Fingerprints
Dr Ian Thomas (eResearch)
Prof Heinz Schmidt (RMIT)
Stefan Hrabar (data61)
This project brings three existing software packages together and renders the into the hands of CSIRO and citizen researchers:
1. MyTardis for research data curation of insect files. MyTardis is an open-source data curation system used by a number of universities around Australia for handling large instrument datasets. Find out more about MyTardis.
2. Chiminey for cloud-based high-throughput parallel analytics of these digital insect models with future codes and queries written by professional or hobby entomologists. Chiminey was developed by RMIT eResearch and AICAUSE and is a software platform that enables scientists to perform scalable computations on cloud-based and HPC facilities. Find out more about Chimney.
3. A surface roughness package written in RMIT CSSE to analyse surfaces statistically. This has been used to characterise nanosurface digital data sets from microscopy. It is expected that the software will be integrated for researchers in a self-contained deployment within their existing cloud tenancies.
We expect to get access to sample insect data collections of a moderate size from Data61.
Stage 1: The first task of the student will be to ingest and visualise insect data in MyTardis using CSIRO data collections and open-source visualisers.
Stage 2: In this main task, an existing Chiminey+MyTardis integration for biophysics will be used for the data in (1). It will be adapted to distribute data from (1) and small parameterised jobs to cloud VMs, gather and curate the results. This uses toy stub analytics functions available at RMIT or Data61.
Stage 3: The surface roughness package will be adapted to capture approximate roughness conditions from the insect data and integrated in lieu of the stub in (2). Surface `windows’ of interest for fingerprinting and classification, will be specified by the researchers using web-browser interfaces.
This project is well-suited to a student who is able to show agility in face of the demands of integrating applications from different domains and using disparate technologies.
Note. The project will be conducted at RMIT City campus. Video conferencing with CSIRO, Canberra and elsewhere will allow close collaboration with etymologists and eResearchers at CSIRO.
Human-Centered Curriculum Visualization
Dr Maria Spichkova (RMIT)
Dr Ulrich Engelke (data61)
The need for transparency of curricula is growing, especially in Australia, the 4th largest provider of international education (as per UNESCO statistics1 for 2012). Local and international students require an easy-to-understand visualization of study programs in order to analyse them and make well informed decisions. Such visualization would be also a great support for
Program Coordinators and for Study Advisors to provide corresponding support to the student.
This project will focus on a human centred solution to this problem. The student work within the project will be divided in the following three stages:
Stage 1: To analyse of the existing approaches on curriculum representation, and specify a human-centred approach for curriculum visualization, that would decrease cognitive load and increase the understandability of the possible leaning paths.
Stage 2: Implement the specified approach as a Web-application. As input data a number of RMIT study programs will be used, but the solution should be general enough to be later applied to any study program.
Stage 3: The results of the project will be documented as a technical report that should provide a basis for a further research paper.
Optimization for journey planning with consideration of passenger preferences
A/Prof. Xiaodong Li (RMIT)
Dr Simon Dunstall (data61)
Public transport network plays an increasingly important role in a metropolitan city these days. As the use of public transport in cities increases, congestion and pollution decline and so do the associated costs and health problems. It is therefore important for such a network to be easily navigable so as to not discourage potential users. For this reason, public transport journey planners are an essential part of the complex transport networks of today’s metropolises. Most cities with large public transport networks provide journey planners with the aim of providing a journey that suits the traveller’s preferences, yet only a fraction of possible user preferences are taken into account when planning these journeys. One such example is the PTV Journey Planner that we use here in Melbourne:
In this project, you will need to build a journey planning tool using some classic shortest path algorithms such as Dijkstra's algorithm, or other more advanced optimization techniques such as multiobjective optimization methods (other methods will be also considered), taking into account users’ preference information (e.g., less mode changes, faster travel time, and walks as part of the journey), in order to provide tailor-made solutions to the passengers in advance of their journey. You are suggested to make use of the resources provided at OpenTripPlanner (OTP).
In short, you are expected to extend the capabilities of OTP in some interesting way. The project will be carried out by an undergraduate/master or PhD student (with a solid optimization and some math background, plus Java or C programming skills).
How to apply
Applications now closed
Applications now closed.
Applications now closed.
Find out more about data61-CSIRO.
Associate Professor Kandeepan Sithamparanathan
School of Engineering
Phone: 03 9925 2804