Welcome to
the Software
Innovation Institute
With a focus on ethical computing, data science, and privacy, SII provides an opportunity for new graduates and practising professionals to skill up in the practice of software engineering and data science. We provide a world-leading integrated learning environment for students, while addressing today's complex data challenges across privacy and personal data management. With decades of experience in artificial intelligence, machine learning, data mining, data analytics, and data science, we are developing new ways to add value to data whilst retaining our personal privacy. Through client projects that focus on delivery of actual product, providing software engineering and data science skills, we support both ANU research projects and externally funded projects to mentor the next generation of Software Engineers and Data Scientists.
Technology for
public good
The institute works with clients to create software systems and practices that solve their data problems, ethically and with a focus on privacy. The systems we create provide the information to drive business decisions and to support self-determination. We bring together leading researchers, senior and industry experienced software developers, industry experts and students to translate research through design into solutions for complex problems, cognizant of cultural context and the preservation of privacy.
Our Focus
We work with clients to provide cross disciplinary teams of experts from academia and industry to advise and to develop new data science and software solutions. Our teams engage to understand the problem space, develop and deploy new research methods, and use best of breed tools, with a focus on ethical applications and the protection and portability of personal data. We specialise in key emerging areas in Data Science and Software Engineering, and in the teaching of both disciplines. Our state-of-the-art technology stack includes flutter and SOLID.
Distributed Personal Privacy
Centrally collected personal data is increasingly recognised as presenting dangers to personal privacy. Data breaches and government release of personal data for political reasons have become increasingly apparent. We need software and data systems where individuals manage, maintain, monitor, and share their own data. This growing area of research, particularly in the context of AI for good, is crucial for our societies future engagement with data. Personal online data stores (PODs), social linked data (SOLID), entity resolution, data matching, and machine learning all play a role in this cross disciplinary research. How do we manage personal privacy against the tremendous benefits we gain from sharing our data? Our projects are developing this key technology for our future.
Confidential Computing
Security and privacy-preserving techniques including homomorphic encryption and differential privacy are being developed and deployed in industry to enable safe and scalable analysis of confidential commercial data across entities. This allows secure sharing of the data insights while preserving privacy of the underlying data. Activities include entity resolution, data matching, and machine learning over data sources that have strict privacy and security restrictions.
Systems Analysis and Design
The value of most systems developed today is in the data that is the foundation of the system. Applications of the data are beyond the purpose of any one system. We analyse your business and system needs to design for trust and security, using techniques from the cutting edge of best practice computer science, with distributed data governance and privacy management, privacy-preserving record linkage, machine learning and vulnerability assessment. This gives you and your users, software tools which separate the data from the application, providing security and enabling trust.
Reasoning over Graphs
Graph analytics has seen a resurgence over the past few years and is used to fight crime and terrorism, detect fraud, and optimise routes. Today knowledge graphs capture significant information from the data nodes which machine learning can turn into knowledge. Turning this knowledge into a capability for reasoning over graphs remains a challenge. The SII team is developing tools and technology to support these activities.
Interpretable / Explainable Machine Learning
Interpretable and explainable Machine Learning has become more urgent as learning models are becoming more complex and being used more widely to inform daily decisions, product and service offerings and organisational decisions. Decision makers need to have confidence in the knowledge/models being used to make decisions, and to understand any bias or conflicts within the models. Today we can aid in transparent and understandable data-driven decision making.
Natural Language Processing
Most data today remains largely untapped in unstructured collections collected by many organisations. We can help organisations unleash the inherent value stored in these vast amounts of unstructured data using the latest NLP techniques to develop scalable solutions.
Education and Training
The Institute also offers a leading teaching and training program in analytics, data science, software engineering and AI. We have developed an innovative module-based approach to support the delivery of micro-credentials. Our bespoke technical and executive training is provided to organisations in both the public and private sectors. Opportunities include:
- Technical Upskilling in Analytics and Data Science
- R & Python Programming for Analytics, Data Science and Data Engineering
- Strategic Executive Training in Data Literacy and Data Science
- Data Literacy and Data Science for Management and Leadership
- Secure Software Development
- Systems Engineering
- Strategic Advisory
- AI Ethics/Bias/Fairness
Want to work with us?
We are currently recruiting software developers and designers.Visit Opportunities for details.
The Leadership Team
We are hiring!
Our mission is to deliver technology for public good. We are always looking for talented people to work with. We are regularly recruiting and there are exciting opportunities to join the team of software engineers and research fellows.
Looking to apply your skills in software development, data science or data engineering to interesting projects?
Find out more on SII.anu.edu.au
Haotian Weng, Jingjing Shi & Alex Sneddon work on technology solutions to support the COVID-19 response.
Find out more on cecs.anu.edu.au
Listen to former Director Jochen Trumpf talking about the mission of the Institute.
Find out more on Youtube.com
Engage
The Software Innovation Institute is based at in the College of Engineering and Computer Science at the Australian National University in Canberra, Australia.
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