Welcome to
the Software
Innovation Institute
With a systems approach and 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 pathway for current and recently graduated students into a professional practice of software engineering, 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 the
good of society
The institute works with clients to create software systems and practices that solve their data problems, ethically, with a focus on privacy, and within the context of our society. 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.
- View our Solid Pods based apps at Solid Community AU. These include podnotes, cvpod, keypod, and innerpod
- Our packages to support SOlid Pod app development in Flutter
and Dart are available from pub.dev
as solidpod,
solid_auth,
solid_encrypt,
and rdflib.
- A foundational project has been a collaboration lead by the Gurriny Yealamucka Health Services Aboriginal Corporation and the Yarrabah Leadership Forum to demonstrate technology for health data sovereignty to improve health outcomes.
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 Society, is crucial for humanities 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.
An End-to-End System
All software lives within an end-to-end System. 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 purview of any one system. We need to be able to share data across systems. We need systems that deliver 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.
Reasoning over Knowledge
Graph analytics, capturing knowledge in graph structures, has seen a resurgence over the past few years and is used to improve health, fight crime and terrorism, detect fraud, optimise routes, improve our financial security. 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 that we are tackling.
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 owned by many organisations. We are beginning to unleash the inherent value stored in these vast amounts of unstructured data using the latest language-based techniques to develop new systems to aid society.
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
Contribute to our projects.
Our projects are open source. You are welcome to contribute. Let us know.
The Leadership Team
We are delivering!
Our mission is to deliver technology for public good and in particular delivering technology and projects to support your privacy. We have been grateful to the teams of talented people working with us. Some of our projects include podnotes, solidpod, yarrabah, and solid community au.
Graduate software engineers applying their skills in software development, data science or data engineering to interesting projects.
Haotian Weng, Jingjing Shi & Alex Sneddon work on technology solutions to support the COVID-19 response.
Listen to former Director Jochen Trumpf talking about the mission of the Institute.
Engage
The Software Innovation Institute is based at in the College of Engineering and Computer Science at the Australian National University in Canberra, Australia.
