Grace Billiris

Software Engineer & PhD Candidate

I am a Software Engineer at Macquarie Group and a PhD candidate in Software Engineering at the University of Technology Sydney. I am motivated by solving complex problems and understanding the systems behind them, with research focused on data privacy risks in agentic AI systems.

About Me

I am a Software Engineer at Macquarie Group and a PhD candidate in Software Engineering at the University of Technology Sydney. I have always been motivated by solving complex problems and understanding the systems behind them. What began as an early curiosity for technical challenges has grown into a focus on addressing real-world problems in software engineering and artificial intelligence.

My research focuses on data privacy risks in agentic AI systems that process personally identifiable information. Previously, my honours research explored the intersection of generative AI and copyright law, resulting in the development of the Copyright Health Checker (CHC) tool and a publication in the ACM Digital Library.

Alongside my research, I contribute to software engineering education through teaching and mentoring roles at the University of Technology Sydney. I am passionate about building trustworthy technology and collaborating across teams.

I value continuous learning and see each opportunity—whether through research, industry work, or collaboration—as a way to deepen my understanding of complex systems and grow as an engineer.

Research Experience

Doctor of Philosophy (PhD) — Current

University of Technology Sydney

2025 – Present

My PhD research investigates data privacy risks in agentic and adaptive AI systems and develops practical architectures, methods, and tools for building reliable and observable multi-agent software systems. This work spans the AI software development lifecycle and combines systematic literature reviews, empirical taxonomies, design science, and prototype development.

The research has produced taxonomies of data risks in AI, quantum computing, and data privacy; an accepted systematic literature review for the SAI Computing Conference 2026; and a federated observability architecture pattern published in Information and Software Technology. Current work also includes the Context Processing Layer (CPL), an SSRN-accepted preprint proposing semantic observability for multi-agent AI systems.

  • Developing evidence-based taxonomies and systematic reviews of privacy and data risks in AI systems.
  • Designing federated and semantic observability patterns for reliable agentic AI software systems.
  • Building and evaluating multi-agent prototypes that translate the research into practical developer tooling.

Honours Project

University of Technology Sydney

January 2023 – August 2024

  • A year-long research project investigating the intersection of Generative Artificial Intelligence (GAI) and copyright law, culminating in the development and validation of the Copyright Health Checker (CHC) tool.
  • Achieved High Distinction – 41029 Engineering Research Preparation (95/100) and 41030 Engineering Capstone (95/100).
  • Published work on CHC available on ACM Journal & ACIS2024 Conference

Publications

Featured Publication

A Federated Observability Architecture Pattern for Reliable Agentic AI Software Systems Across the AI Software Development Lifecycle

Published in the A-ranked journal Information and Software Technology, Volume 199, Article 108260 (2026).

FOAP introduces a seven-layer, schema-agnostic architecture for federating, normalising, retaining, and observing heterogeneous telemetry across the AI software development lifecycle.

  1. Billiris, G., & Gill, A. (2026). A federated observability architecture pattern for reliable agentic AI software systems across the AI software development lifecycle. Information and Software Technology, 199, Article 108260. https://doi.org/10.1016/j.infsof.2026.108260
  2. Billiris, G., Gill, A., Haggag, O., Bandara, M., & Grundy, J. (2026). CPL: A context processing layer for semantic observability in multi-agent AI systems [Preprint accepted by SSRN]. SSRN 7194446. SSRN 7194446
  3. Billiris, G., Gill, A., & Bandara, M. (2026). Systematic literature review of data privacy risks in AI systems. Accepted for the SAI Computing Conference 2026.
  4. Billiris, G., Gill, A., & Bandara, M. (2025). Privacy in the age of AI: A taxonomy of data risks. arXiv. https://doi.org/10.48550/arXiv.2510.02357
  5. Billiris, G., Gill, A., & Bandara, M. (2025). A taxonomy of data risks in AI and quantum computing (QAI): A systematic review. arXiv. https://doi.org/10.48550/arXiv.2509.20418
  6. Billiris, G., Gill, A., Oppermann, I., & Niazi, M. (2024). Towards the development of a copyright risk checker tool for generative artificial intelligence systems. Digital Government: Research and Practice, 5(4), Article 41. https://doi.org/10.1145/3703459
  7. Billiris, G., & Gill, A. Q. (2024). An initial review of the copyright concerns of generative artificial intelligence. ACIS 2024 Proceedings, Article 17. ACIS 2024 Proceedings

Experience

Macquarie Group

Software Engineer

Macquarie Group

February 2024 - Present

Contributes to reliable software systems in a large-scale financial services environment, with experience across AWS cloud governance, compliance, security, data management, cloud operations, and cost optimisation.

University of Technology Sydney

Casual Academic

University of Technology Sydney

February 2023 - Present

Leads tutorials, blended learning activities, and demonstrations, and supports marking, student consultations, and academic administration.

Tommy Hilfiger

Sales Consultant

Tommy Hilfiger

November 2019 - October 2025

Completed various duties including customer service, register work, stock lifecycle, cleaning, and overseeing the daily store operations.

University of Technology Sydney

Faculty Assessment Partner

University of Technology Sydney

July 2023 - November 2023

Faculty Assessment Partner at UTS, specialising in GenAl initiatives and academic integrity review, enhancing student experience through support, redesign, consultations, and resource creation.

UTS

Apple Foundation Program Participant

UTS

January - February 2023

The Apple Foundation Program at UTS provided me with a challenge-based learning environment where I could get firsthand knowledge of the creative process required to address real-world issues, work in diverse teams, and create apps using the iOS ecosystem.

AgriWebb

Software Engineering (Intern)

AgriWebb

February 2022 - June 2022

The UTS Software Development Studio's partnership with AgriWebb provided me with an opportunity to develop a Python machine learning algorithm, as well as experience in complex data querying and analysis in Snowflake SQL Data Warehouse.

InfoPoint

Software Engineer (Intern)

InfoPoint

July 2021 - February 2022

• Executed full lifecycle software development • Integrated software components into a fully functional software system • Developed software verification plans and quality assurance procedures • Documented and maintained software functionality • Worked collaboratively with the directors, stakeholders, and other technical team members • Regularly reported to the technical lead on a formal and informal basis about the status of assigned tasks • Provided timely technical support and issue resolution to customers

Mimco

Sales Assistant

Mimco

November 2019 - February 2020

Completed a variety of tasks, including stock management, customer service, register work, and housekeeping.

Education & Skills

University of Technology Sydney

Doctor of Philosophy

2025 - 2027Australia

    University of Technology Sydney

    Bachelor's of Engineering, majoring in Software (Honours)

    Bachelor's of Science, majoring in Mathematics

    2020 - 2023Australia

    • Achieving a 6.57/7 GPA (High Distinction Average)
    • Achieved High Distinction in Programming Fundamentals, Database Fundamentals
    • Achieved High Distinction in Introduction to Data Analytics, Data Structures and Algorithms
    • Achieved High Distinction in Business Requirements Modelling

    Riverside Girls High School

    NSW Higher School Certificate

    2014 - 2019Australia

    • Years 7-10 Student Representative Council Member

    Programming Languages

    C++C#JavaJavaScriptTypeScriptHTMLPython

    Applications

    Visual Studio CodeJetBrains RiderPostManMongoDBGrayLogMicrosoft Office SuiteAdobe Creative Suite

    Professional Skills

    Organisation and Time ManagementTeamwork & CollaborationCommunication

    Languages

    English (native)Greek (fluent)

    Featured Projects

    Data Engineering Layer for Telemetry Federation

    UTS

    PhD Research Project

    A data engineering solution for federating telemetry data, enabling efficient data collection, processing, and analysis across distributed systems.

    Data EngineeringTelemetryFederationDistributed Systems

    Privacy Anonymisation Risk Assessor (PARA)

    UTS

    PhD Research Project

    A tool for assessing privacy risks in data anonymisation processes, helping organisations evaluate and improve their data privacy measures.

    PrivacyRisk AssessmentData AnonymisationSecurity

    VERSA (Versatile Extensible Risk and Security Assessor)

    UTS

    PhD Research Project

    A versatile and extensible tool for assessing security risks across various domains, providing comprehensive security evaluation capabilities.

    SecurityRisk AssessmentExtensible Architecture

    AIPRATool: AI Privacy Risk Assessment Tool

    UTS

    PhD Research Project

    A specialized tool for assessing privacy risks in AI systems, helping developers and organisations ensure compliance with privacy standards.

    AIPrivacyRisk AssessmentCompliance

    Say Find - Interactive Party Game

    Personal

    Creator

    A fun, fully interactive team-based quiz game combining knowledge, wit, and competition. Features team management, flexible game setup, real-time scoring, and the ability to share victories. Built with vanilla HTML, CSS, and JavaScript and deployed as a static GitHub Pages site.

    HTMLCSSJavaScriptGitHub PagesParty Game

    Copyright Health Checker (CHC)

    UTS

    Honours Research Project

    Generative Artificial Intelligence (GAI) marks a transformative shift in creative landscapes, blurring the lines between human and machine-generated content. This capstone project developed the Copyright Health Checker (CHC) tool to identify and assess GAI system's copyright concerns through analysis of regulations, legislations, and legal cases spanning Australia, the UK, the US, and Europe.

    The CHC tool has been developed based on the analysis of selected, publicly available copyright cases and academic literature. While it serves as an initial health checker for GAI system developers, it provides important insights for responsible GAI development and policy formulation in the digital era.

    ResearchLegal AnalysisGAICopyright Law

    TextInsights

    UTS

    Software Engineer

    A web application that uses Natural Language Processing to examine and provide insights into text, developed as part of the Software Innovation Studio subject.

    NLPWeb DevelopmentText Analysis

    Quality Assurance & Feature Development

    InfoPoint

    Software Engineer

    Implemented comprehensive testing suite including Component, End-to-End, and Integration tests. Developed new Registers feature with Excel integration and enhanced search functionality.

    TestingQAFeature DevelopmentExcel Integration

    Machine Learning Algorithm Development

    AgriWebb

    Software Engineer (Intern)

    Developed Python machine learning algorithms and performed complex data querying and analysis using Snowflake SQL Data Warehouse.

    PythonMachine LearningSnowflake SQLData Analysis

    ShuffleCook

    UTS Apple Foundation Program

    iOS Developer

    Developed an iOS mobile application that helps users decide what to cook by providing random recipe suggestions and generating shopping lists for ingredients.

    iOSSwiftUI/UX DesignMobile Development

    GroupBuddies

    UTS

    Software Engineer

    Developed a web application for intelligent student-group management, featuring smart group sorting based on complementary student profiles and manual management options for students and tutors.

    Web DevelopmentAlgorithm DesignUser Management

    eRestaurant

    UTS

    Software Engineer

    Created a web application for Le Bistrot D'Andre restaurant, implementing table booking and food ordering functionality with menu management features.

    Web DevelopmentBooking SystemRestaurant Management

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