Lianna Zhao

Lianna Zhao

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Lianna Zhao completed her PhD in Design Engineering at the Dyson School of Design Engineering, Imperial College London in 2024, under the supervision of Professor Robert Shorten. Her research primarily focused on distributed ledger technology and algorithm design for the network layer and her study was generously funded by the IOTA Foundation. Prior to this, she received an M.S. in Control Engineering from the College of Information Science and Engineering, Northeastern University, China, in 2020, and a BSc in Automation from the College of Engineering, Qufu Normal University, China, in 2017.

Her research interests include directed acyclic graph - based distributed ledger technologies and their applications, blockchain privacy and security, machine learning with a focus on healthcare, and control theory, particularly in multi-agent systems.

Please feel free to reach out should you be interested in his research.

Work or Intership experience

  • 2024: Internship at JPMorgan Chase
    • Associate in the Global Technology Applied Research (GTAR) team at JPMorgan, developing a private, auditable distributed ledger (PADL) with zero-knowledge proofs to enhance blockchain privacy and security.
  • 2024: Postdoc Project at University of Sheffield
    • Principal Researcher for an Aortic Dissection Charitable Trust project, collaborating with Leeds Teach- ing Hospitals NHS to enhance the diagnosis of Acute Aortic Syndrome (AAS) using AI.

PhD projects – Network layer design for directed acyclic graph - based distributed ledger (Github link)

  • Secure Access Control for IOTA Tangle (Oct 2020 - Apr 2021)
    • Led a project to identify vulnerabilities in the IOTA Tangle’s access control protocol. Implemented data- driven resilience measures, including a probabilistic model based blacklisting algorithm, significantly enhancing network security and robustness. (Published in IEEE IoT Journal Paper link).
  • Enhancing user quality of service with IOTA Tangle (Apr 2021 - Jun 2022)
    • Co-led the design of a user-node interaction mechanism for a directed acyclic graph (DAG)-based distributed ledger. Utilized probabilistic models and data analytics to optimize user traffic distribution across nodes, ensuring consistent service quality. (Published in ACM DLT Paper link).
  • An attack resilient policy on the tip pool of IOTA Tangle (Jan 2023 - August 2023)
    • Led a project to address the unique challenges of the IOTA Tangle, including managing block addition rates and mitigating spam attacks. Developed a novel filter to limit the appending transaction size, enhancing the security and efficiency of the network. (Published in BLOCKCHAIN’23 Paper link).
  • Personalised feedback control and compliance strategies design for ensembles (Apr 2021 - Jul 2023)
    • Designed a scheme using Distributed Ledger Technologies to create personalized social nudges and influence agent behavior in smart cities. Developed a pricing model for personalized risk in sharing economy applications, demonstrating proven convergence of the proposed stochastic system. (Published in IEEE IoT Journal Paper link)
  • A smart mask design to enforce social contracts based on IOTA Tangle (Apr 2022 - Jul 2023)
    • Led the development of a distributed ledger application in a smart mask prototype to monitor mask- wearing status, leveraging distributed ledger technology for secure algorithm communication and data immutability. (Published in PLOS ONE: Paper link).