Our Students


  • Anahita is a PhD scholar at UNSW and DATA61 CSIRO Australia. The driving interest of her research is around adversarial machine learning. She has hands on experience using big data analytics tools and in-depth technical knowledge of data science particularly in machine learning, statistical analysis, credit scoring and customer segmentation. her current research interests encompass adversarial machine learning, Artificial Intelligence, IoT, and cybersecurity.
  • Publications: Google Scholar
  • Tags: Adversarial Machine learning | IoT
  • Arthur is a penultimate student, studying a combined Engineering/Commerce degree. He is currently working with CSIRO Data61 to study the effectiveness of website cloning attacks against modern anti-phishing software. Although his expertise is in web development, he is also interested in data science, and how software can be applied to financial mathematics.
  • Tags: Software Engineering | Cybersecurity
  • Benjamin is a PhD candidate at the University of Queensland (UQ) and the CSIRO Responsible Innovation Future Science Platform (RI FSP), and is funded as part of the CSIRO-UQ Collaboration. His current research interests are focused on the intersection of ethical and methodological issues in data science, and on the formalisation of moral decision-making in automated systems.
  • Publications: ORCID
  • Tags: Moral philosophy | Philosophy and ethics of technology | Research ethics | Responsible innovation
  • Bushra is a Data61 PhD student from the University of Adelaide working on Adversarial Machine learning in the Cyber-security domain. Specially she is working on evasion and poisoning attacks and defences in Cyber-security systems such as phishing, spam, malware, intrusion and data exfiltration detectors. Previously, she worked on two studies after commencing her PHD which are under review.
  • 1. Machine Learning for Detecting Data Exfiltration: A Review (ACM Computing Survey)
    2. Impact of Adversarial Examples on Phishing URL Classifiers (IEEE symposium of Security and Privacy)
  • Publications: IMTDE
  • Tags: Adversarial Machine Learning | Deep learning | Cybersecurity
  • Chaoran received a Bachelor of Information Technology degree from Deakin University in 2018. He is currently working towards a PhD degree at Swinburne University of Technology. His research interests include malware detection and adversarial machine learning. Deep learning techniques have recently been developed to cope with the booming increase of malware in various platforms, rendering investigating vulnerabilities and enhancing the robustness even more critical.
  • Publications: Google Scholar
  • Tags: Malware Detection | Adversarial Machine Learning
  • Chehara is a PhD Candidate at the Faculty of Information Technology, Monash University Melbourne where she is part of the Cyber Security and Systems research organisation. She is bringing hands-on background experience in data mining, machine learning and image processing technologies. The main objective of her research is to preserve building automation data and user behavioural patterns from outsiders as building automation systems share their sensitive data with stakeholders to gain benefits or reduce overall cost. Therefore, by creating an interface to protect the smart building data, it is possible to avoid tenants being identified, profiled and tracked.
  • Tags: Data Mining | Cyber-security and Privacy | Image and Signal Processing | Machine Learning
  • Highlight: Being surrounded by people who are just as keen on cybersecurity as I am, and understanding the competitiveness of the discipline is motivating me to progress even more.
  • David is a Cyber Security CRC PhD student from the Edith Cowan University (ECU) in Perth, Western Australia. David’s PhD project relates to the semantic modelling of digital twins from a cyber security defence automation perspective. David also has an interest in the blending of blockchain technology into the digital twin and cyber-physical system domains. 
David comes to the research environment with a Master of Network Technology, a Master of Cybersecurity and extensive experience in private enterprise, where, as a network engineer, he worked for over 25 years in Australia and in other countries around the world providing business end-user network technical support.
  • This business experience gives David a unique perspective on the mutually beneficial returns from the interaction between research and commerce where his focus is on making research relevant to the business model.

  • Publications: Orcid: https://orcid.org/0000-0002-8644-4387
  • Tags: Network Engineering | Honeypots | Semantic Modelling | Digital Twins | Blockchaining


David is a PhD candidate at the UNSW Sydney and Cybersecurity CRC. His current research interests lie in developing machine learning techniques applied to Cybersecurity. Existing research focuses on graph neural networks to improve existing deception capabilities across various forms of media. David has also spent several years working in industry as a commercial manager and machine learning engineer within Australian and international technology companies. 

  • Publications: Orcid
  • Tags: Machine Learning | Graph Neural Networks | Cybersecurity | Deception Technology


Erik is a Computer Science PhD candidate at UNSW Sydney and is working with the Cyber Security Collaborative Research Centre. His research focuses on the question of how collected data can be used safely for research purposes without harming privacy, e.g., preventing the re-identification of individuals from a shared dataset. Before coming to Sydney, Erik completed both his bachelor’s and master’s degree at the RWTH Aachen in Germany. Ever since his first seminar during his bachelor’s degree, Erik worked on projects that aim at the improvement of user privacy. For his bachelor’s thesis, he developed a platform that gives the users control over their own data and the decision of who is allowed to utilize it. In his master’s thesis, Erik developed a prototype for a privacy-preserving exchange platform that allows exchanging process parameters in industrial settings.

  • Personal Bio Website: https://erikbuchholz.de/
  • Publications: Google Scholar
  • Highlights: Personal privacy is a human right, and privacy protection plays a crucial role in today’s interconnected world. I am very excited to help finding solutions that allow the protection of individuals’ privacy without preventing sensible utilization of data and without hindering progress. By protecting everyone’s privacy, I want to contribute to making this world a safer and better place.
  • Tags: Privacy-enhancing Technologies | Cybersecurity | Sensitive Information Sharing
  • Feixue received a Master of Software Engineering Degree from the Zhejiang University of China. She currently is a Data61 PhD student from the Swinburne University of Technology, Australia. The focus of Feixue’s PhD is providing interpretability for cyber-security systems, related to AI. She is engaged in explaining complex and obscure neural networks. Previously, she worked on a critical functional department, with her specialty of engineering such as software design, architecture development and system reconstruction.
  • Publications: dblp |Google Scholar
  • Tags: Interpretability | Software Engineering | Machine Learning
  • Gnana is a PhD student attached to the School of Computing & Mathematics, Charles Sturt University. His interests are in privacy preserving data collection techniques for statistical aggregation. Currently his area of interest lies around Local Differential Privacy. He is being supported by a scholarship from the Cyber Security Corporate Research Centre.
  • Publications: Orcid ; ResearchgateGoogle scholar;
  • Tags: Data Privacy | Differential Privacy | Local Differential Privacy.
  • Guoxin is currently pursuing the Ph.D. degree with the Electrical and Electronic Engineering Department, the University of Melbourne. His research interests lie in the domain of cyber-physical security, machine learning, game theory and system theory. He received the B.S. degree in 2017 and the M.E. degree in 2019 from the University of Melbourne.
  • Publications:Orcid: https://orcid.org/0000-0003-0534-2440
  • Tags: Cyber-Physical security | Machine learning | Game theory | System theory


Highlight: Working as a summer intern in CSIRO’s Data61 with brilliant people inspired me to become part of this leading digital research network. I believe when great minds collide, giant leaps are made.

  • Hetong is a first year PhD student at The University of Queensland. He received his bachelor degree majoring in mechanical engineering from the Queensland University of Technology, Australia in 2018, and Master of IT degree from The University of Queensland, Australia in 2020. His research interests include data provenance, distributed Storage and any cyber security-related areas.

  • Publications:
  • Tags: Data Provenance | Distributed Storage | Cyber Security
  • Hossein Rahimpour is a PhD student at UNSW and CSIRO’s Data61. He is the recipient of the Australian Government Research Training Program (RTP) scholarship as well as the Cybersecurity Cooperative Research Centre scholarship 2021-2024. Hossein is a Chartered Professional Electrical Engineer and holds Mphil degree in Electrical Engineering from the University of Newcastle. He worked over 15 years in various roles in power industry with expertise in high voltage, transformers and asset management. Hossein’s PhD project explores the application of AI techniques in cyber protection of smart transformers in modern electrical network. The continuing digitisation of power grid and the evolving cyber-attacks motivated him to pursue a higher degree research in this area.
  • Tags: Cyber Security | Artificial Intelligence | Smart Grid | Smart Transformers
  • Huihui is a PhD candidate at Faculty of Engineering and Information Technologies, the University of Sydney, under the supervision of Dr. Chang Xu and Dr. Siqi Ma (CSIRO’s Data61). His main research areas are machine learning and adversarial examples. Specifically, he is working at how to improve the performance and robustness of deep neural networks.
  • Publications: Google scholar
  • Tags: Machine Learning | Adversarial Examples
    • Ivo is a PhD student at the University of Queensland in UQ Cyber Security. His research centres on improving neural network interpretability for use in human centric cyber security applications and defence against adversarial attacks. His primary interests include machine learning, networking, cyber security, and adversarial attacks. Prior to beginning his PhD in 2021, Ivo completed his Bachelor of Software Engineering at UQ in 2020, where his honours thesis focused on the automated detection and classification of illicit content on the dark web.
    • Tags:  Machine Learning | Deep Learning | Human Centric Cyber Security | Neural Network Interpretability
    • Jorge is a Queensland University of Technology PhD student and a Cyber Security Cooperative Research Centre 2021 Cyber Security scholarship recipient. His research interests lie in using cutting-edge computational methods, AI, and Big Data, to study humans in digital environments from both text and photo analysis. His current PhD research project in the area of information warfare in cyberspace focuses on developing AI enabled technologies capable of performing in depth psychological assessment with the intended purpose of identifying fake social media accounts in real time.
    • Tags: Cyber Security | Information Warfare | Artificial Intelligence | Big Data | Facial Recognition | Psychological Assessment
    • Highlight: Passionate about packing a punch to help hit back at state-based actors and individuals causing harm in cyberspace pretending to be something they are not, by combining neuropsychology with computer science to develop next generation AI offensive/defensive capability intelligence technologies. Love the challenge of creating things that people think are impossible.
    • Julie is an honours thesis student at UNSW and the Cybersecurity CRC, working on applications of SOLID, the new data-sharing architecture for the web proposed by Tim Berners-Lee. Her interests are in web technologies, distributed systems, security, and privacy.


  • Kane is a Computer Science PhD candidate at UNSW working with The Cyber Security Cooperative Research Centre on security of distributed machine learning. Previously completed a Bachelor of Computer Science (1st class) at UNSW which culminated in a thesis on satellite image retrieval using unsupervised machine learning models. Kane began his career in the healthcare setting but developed a passion for deep learning and is now dedicated to ensuring Australia can use this amazing technology in a safe and secure way.


Publications: orcid

Tags: Machine Learning | Cybersecurity | Federated Learning
  • Kevin is a commercially-minded QUT PhD candidate with over 20 years of experience in a diverse range of fields. These include cloud services (before it ever had such a name), banking, public health, energy, mining, and cybersecurity. He has the unusual distinction of having worked for 4 of CSIRO’s major business units in various capacities. He enjoys all things technical and reads as much as reasonably possible, and then some more.
  • Le is a PhD student at the University of Wollongong (UOW), sponsored by a CSIRO’s Data61 scholarship. In 2011, he received his Master Degree in Mathematics from Ho Chi Minh City University of Science, Vietnam, after a bachelor at the same university. From 2007 to 2016, he worked as a mathematics teacher in high school. Le also spent time as a research student in Japan. His current research interests include post-quantum cryptography, focusing especially on lattice-based cryptography.
  • Publications: Google scholar
  • Tags: Post-quantum Cryptography | Lattice-based Cryptography
  • Highlight: I am very grateful to CSIRO’s Data61 and respectable professors at both CSIRO’s Data61 and University of Wollongong for giving me a wonderful chance to work with them, helping me to push my passion and my research up.
  • Lihong received her Bachelor degree with Honours from Deakin University, Australia. She is currently a PhD student with CSIRO’s Data61. She is working on Android malware detection and evolution analysis. Her research interests include Android malware analysis, adversarial attacks under the Android context, human-centric research, and explainable machine learning. Understanding the evolution of Android malware facilitates the development of defending techniques by proactively capturing the features of Android malware. This work is aimed at supporting comprehensive modelling on malware’s evolution and providing a detailed explanation of the reason why Android malware evolved in those ways.
  • Publications: ORCID
  • Tags: Android Malware | System Security
  • Lu Yang is a PhD Candidate and a Sessional Teaching Staff in the Queensland University of Technology. He is a Domestic Full-Time Australian Government RTP Scholarship holder and a CSIRO Data61 Student Scholarship holder. In 2016, he received a Bachelor of Electronic and Communication System Engineering from the Australian National University. In 2018, he received a Master of Networking and Communication Engineering from the Queensland University of Technology. In the last year of the Bachelor of Engineering study, he worked in the Optical Biofluidics Imaging Group in the Australian National University. In the Master of Engineering study, he worked in the Inorganic Nanomaterials Lab in the Queensland University of Technology. He specializes in signal processing methods and electronic system design. In the PhD study, his main areas of research interests include Internet of Things, Physical Layer Security, and Communication Theory.
  • Publications: ORCID
  • Tags: IoT | Physical Layer Security | Communication Theory


  • Mariya is a final year student pursuing a Bachelor of Software Engineering at UNSW. Currently, she is collaborating with Data61 on her research thesis which involves orchestrating phishing detection algorithms to triage phishing emails. Her interests lie in problem solving in relation to software engineering and team collaboration.
  • Tags: Software Engineering


Mark is a PhD student at the University of South Australia. His research focus on further understanding Fake News and other deceptive online content on social media, and how it can be detected and prevented. In particular, he’s interested in examining trends and propagation of deceptive content and its spread on the right wing and populist areas of the social media website, Reddit.

  • Publications: Google Scholar
  • Tags: Machine Learning | Big Data | Data Science | Social Media | Fake News



  • Michael is a PhD student from the University of Adelaide focusing on binary vulnerability analysis using fuzzing techniques. He is particularly interested in manipulating and executing binaries in order to analyse them in new and unique ways.
  • Publications: Google Scholar
  • Tags: Cyber Security | Fuzzing | Emulation | Virtual Machine


  • Mohammad is a PhD student at Monash University, sponsored by a CSIRO’s Data61 scholarship. Formerly, he developed essential skills to be prepared for commencing a PhD by working around 8 years in industry, 3 years in academia and disseminating research findings in leading venues, simultaneously. Mohammad is currently pursuing his PhD at the Faculty of Information Technology at Monash University, under the supervision of Dr. Adel Nadjaran Toosi and Dr. Raj Gaire. Motivated by his passionate for expanding existing knowledge of distributed systems, his research is intended to extend the elasticity of cloud computing to the edge of the network to improve the performance of IoT/Smart applications and Microservices. Previously, he developed elasticity-related optimizations in cloud, but the emergence of Edge/Fog Computing and 5G networks made him enthusiastic about bringing the elasticity benefits to the edge to improve the Quality of Service (QoS) from both service providers and end-users’ perspective.
  • Publications:  Google Scholar; Publons; Research Gate; LinkedIn; ORCID
  • Tags: Distributed Systems | Cloud Computing | Edge/Fog Computing | Serverless Computing | Autonomic Computing
  • Highlight:  Reaching realistic solutions for challenging real-life problems in IT domain is what I am eager for. To be fulfilled, I am always looking for a chance to collaborate with not only CSIRO’s Data61 and Monash University researchers, but also other talented, experienced and like-minded researchers in the distributed systems community around the world. Working with people smarter than I always helps me to learn and make encouraging progress.
  • Nauman is a PhD research student at the School of Science, RMIT University, Melbourne, Australia, and a researcher at CSIRO’s Data61.  He is working on lightweight cryptographic protocols for the Internet of Things, looking at communication security and cryptographic schemes to maintain the confidentiality of data at smart nodes as well as during communication between smart devices or with the cloud platform.  He worked on an SNMP based cybersecurity monitoring system during his Masters.  He also worked on MPI programming to optimize the Galois/Counter Mode (GCM). His research interests include network security, Internet of Things security, digital forensics and cryptography.
  • Publications:  Orcid , Google Scholar , LinkedIn
  • Tags:  IoT | Security | Lightweight Cryptography | Network Security | Digital Forensics
  • Robert worked as a Research Assistant at QUT in 2019 investigating blockchain within industry application. Currently Robert is undertaking a PhD degree with QUT, CSIRO, and Data61 researching “Distributed and Privacy Preserving Analytics of Smart Grid Data”. Robert has over a decade of hands on experience in the ITC industry, including working for 5 years as the Network Administrator for the Statistical Institute of Belize.
  • Tags: Machine Learning | Blockchain Technology | Cybersecurity


  • Roelien is a Cyber Security PhD candidate based in Sydney. Her research focuses on quantifying and optimising the performance of Cyber Deceptions. Her research will utilise modern techniques such as natural language processing and simulation testing to determine methods to compare Cyber Deceptions such as honey files. Previously, Roelien worked as a Research Analyst at the European Central Bank in Frankfurt. She holds a Master in Econometrics from the University of Amsterdam.
  • Tags: Semantic Vector Space | Decoy Documents | Cyber Deception | Characteristic Metrics | Cyber Security | Honey files | Natural Language Processing | Data Science
  • Highlight:  I am thrilled to combine my love for coding and statistics to thwart espionage.
  • Rongjunchen is a junior PhD student at CSIRO’s Data61. Rongjunchen Zhang received his Bachelor of Science degree in Software Engineering from both Southwest University, China and Deakin University, Australia in 2018. In the same year, he received a Bachelor of Science (Honours) degree with first-class honours from Swinburne University of Technology. He began his PhD candidature in April 2019 at Swinburne University of Technology. His main research interests are natural language processing, reinforcement learning, and security of chatbot.
  • Tags: Software Engineering | Machine Learning | Reinforcement Learning
  • Sara is currently a PhD student in the Faculty of Information Technology, Monash University, Australia. She received her Bachelor and Master degrees in Electrical and Electronic Engineering from the Sharif University of Technology in 2011 and 2013 respectively. Saras research interests include deep neural networks, physical-layer network coding and applications of lattices in wireless communication.
  • Tags: Deep Learning | Wireless Communication | Coding Techniques | Lattices
  • Saud is a Doctoral Candidate with the School of Engineering at The Australian National University and Data61, CSIRO. He holds a first-class honours equivalent qualification and receives the equivalent Australian Government Research Training Program and CSIRO Postgraduate Research Scholarship. His previous background includes two years of full-time experience overseeing industrial project research at the Kumoh National Institute of Technology, South Korea, funded by the National Research Foundation of Korea (equivalent to Discovery Project of the Australian Research Council). His research focuses on bridging the gap between deep learning, the internet of things, and cybersecurity in the physical layer wireless communication domain.
  • Publications: https://scholar.google.com/citations?user=eEe1-SkAAAAJ&hl=en
  • Tags: Deep Learning | Internet of Things | Wireless Communication | Physical Layer Security
  • Tom is currently a machine learning researcher with a current focus on adversarial machine learning in natural language processing. In a previous life, Tom worked as a data scientist building systems for Telstra, Caltex and Woolworths. He enjoys solving problems, building things, mathematics, writing, and long walks on the beach. You can learn more about Tom at tomroth.com.au
  • Publications: none yet! (but hopefully soon)
  • Tags: Adversarial Machine Learning | Robustness | Reinforcement Learning | Natural Language Processing
  • Highlight: I like breaking a problem down to the fundamentals and making solutions as simple as possible.
  • Viet Vo is a final-year Ph.D. student in the Department of Software and CyberSecurity, Monash University.
    His research interests are in the area of applied cryptography and data privacy, cloud security, and network security. Viet’s aim is to enhance the efficiency and security/privacy of real-world systems.
  • Publications: Google Scholar
  • Tags: Applied cryptography and Data Privacy | Cloud security | Network security
      • Xinyu is a first year PhD candidate in the department of software and cybersecurity at Monash University, whose research is sponsored by Data61 CSIRO. Xinyu’s research focuses on developing post-quantum multiparty signatures based on symmetric primitives (e.g., hash functions, pseudo-random functions, and block ciphers). She is passionate about cryptography, especially digital signatures, and variants (i.e., signatures involving multiple signers). Currently, she is working on constructing post-quantum multi-signature protocol utilising symmetric primitives only. She is also interested in applying the protocol to blockchain-based applications such as cryptocurrencies and blockchain-based supply chain systems.
      • Publications:  Google Scholar
      • Tags: Cryptography | Post-Quantum Cryptography | Symmetric Primitives | Blockchain
    • Highlight:  I do not have a strong mathematical background since I studied Bachelor of Management from 2013 to 2017. Later, I finished my master’s degree in Information Technology at Monash University. During my master’s study, I happened to select a fundamental unit about cryptography which was taught by my university supervisor Joseph Liu. Thanks to him, I immediately fell in love with the subject and got the highest score of the unit in the semester! I published my first paper about ring signature during my master which gave me confidence to keep working on cryptography. Currently, I’m dealing with more challenging crypto schemes which are secure against quantum attacks. I believe our work is crucial since the communication online relies heavily on cryptographic schemes (encryption and digital signature).  
  • Olivia Shen is a first year PhD student at the Faculty of Information Technology, Monash University with research interests in searchable encryption, encrypted database, and privacy preserving crowdsourced data analytics in the broad Cyber Security subject domain.
  • Tags: Metadata Privacy | Searchable Encryption | Encrypted Database | Crowdsourcing | IoT
  • Zian Liu is a first year PhD. student. His research focuses on Malware analysis in Cyber Security.
  • Tags: Malware Analysis | Cyber Security