CV

Current Role

• Senior Machine Learning Engineer, Ofcom, Apr 2025 - Current
  • Shaping guidelines for major social media platforms to meet the Online Safety Act requirements.
  • Developed accreditation process for technologies that meet the minimum accuracy standards for detecting CSEA and terrorism content.
  • Providing expert technical advice to policymakers, and contribute to strategic decision that inform regulatory policies direction for Online Safety.
  • Planning for future research directions and initiatives.
  • Leading the planning and development of an in-house application to conduct research experiments and perform algorithmic assessment of recommender systems.
• Machine Learning Engineer, Ofcom, Jan 2024 - Apr 2025
  • Initiated pilot research into how to assess recommender system algorithms that underpins online services to meet the Online Safety Act.
  • Developed assessment metrics for the recommender systems for the online services to show compliance with the Online Safety Act.
  • Provided expert technical advice to policymakers on regulatory policies for Online Safety, including Protection of Children and Illegal Harms.
  • Scrum Master for the team, responsibilities include project planning, sprint planning, and facilitate meetings such as daily stand-ups and retrospectives.

Career Experience

• XAI Researcher, SMARTBEAR EU Project, Dec 2020 - Dec 2024
  • Developing a big data platform that will provide evidence-based personalised support for several pressing health care issues faced by the aging EU societies.
  • Led the XAI-driven research as part of PhD study to personalise health interventions and promote independent living for elderly patients from six EU countries.
  • Designed a data-driven pipeline for Hearing Loss patients that provides clinicians with decision-making support by leveraging AI and XAI techniques. Further improved collaboration skills while working in a large and complex team.

Education

• PhD in Explainable AI, City St.George’s, University of London, 2020-2024
  • First Supervisor: Dr Christos Kloukinas, Reader
  • Second Supervisor: Prof. Artur d’Garcez, Professor
• MSc in Data Science, City St.George’s, University of London, 2019-2020
• BSC in Mathematics, University of Surrey, 2015-2019 (with placement)

Skills

• AI Safety and Governance
  • Translating Technical Research for Policy
  • Providing Technical Advice to Policymakers
• Technical
  • Explainable AI (XAI)
  • Machine Learning Experimentation
  • Model Evaluation and Interpretability
  • Recommender Systems
  • Natural Language Processing
  • Time Series
  • Big Data
  • Python
  • MATLAB
  • Java
  • TensorFlow
  • PyTorch

Publications

FocusLearn: Fully-Interpretable, High-Performance Modular Neural Networks for Time Series

Su, Q.; Kloukinas, C.; Garcez, A (2024) "FocusLearn: Fully-Interpretable, High-Performance Modular Neural Networks for Time Series." 2024 International Joint Conference on Neural Networks (IJCNN), Yokohama, Japan, 2024, pp. 1-8, doi: 10.1109/IJCNN60899.2024.10651481

The SMART BEAR Project: An Overview of Its Infrastructure

Su, Q.; Peretokin, V.; Basdekis, I.; Kouris, I.; Maggesi, J.; Sicuranza, M.; Acebes, A.; Bucur, A.; Mukkala, V.; Pozdniakov, K.; Kloukinas, C.; Koutsouris, D.; Iliadou, E.; Leontsinis, I.; Gallo, L.; De Pietro, G. and Spanoudakis (2023) "The SMART BEAR Project: An Overview of Its Infrastructure." Information and Communication Technologies for Ageing Well and e-Health. ICT4AWE ICT4AWE 2021 2022. Communications in Computer and Information Science, vol 1856. Springer, Cham.

Predicting and Explaining Hearing Aid Usage Using Encoder-Decoder with Attention Mechanism and SHAP

Su, Q. and Iliadou, E.(2022). "Predicting and Explaining Hearing Aid Usage Using Encoder-Decoder with Attention Mechanism and SHAP." In 2022 16th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) (pp. 308-315). IEEE Computer Society.

Profiling Hearing Aid Users through Big Data Explainable Artificial Intelligence Techniques

Iliadou, E., Su, Q., Kikidis, D., Bibas, T. and Kloukinas, C. (2022) "Profiling hearing aid users through big data explainable artificial intelligence techniques." Frontiers in Neurology, 13.

Overview of the SMART-BEAR Technical Infrastructure

Peretokin, V.; Basdekis, I.; Kouris, I.; Maggesi, J.; Sicuranza, M.; Su, Q.; Acebes, A.; Bucur, A.; Mukkala, V.; Pozdniakov, K.; Kloukinas, C.; Koutsouris, D.; Iliadou, E.; Leontsinis, I.; Gallo, L.; De Pietro, G. and Spanoudakis, G. (2022). "Overview of the SMART-BEAR Technical Infrastructure." In Proceedings of the 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health - ICT4AWE. Pages 117-125.

Side Projects for Fun

Film Logging and Recommendation Streamlit App

Film Logging and Recommendation iOS App

Fortnite Stats Analysis

Languages

• Chinese: Fluent (verbal & written)
• English: Fluent (verbal & written)
• Spanish: Conversational

Certifications

• Piano: ABRSM Grade 5 and Central Conservatory of Music (China) Grade 7
• HE Teaching: Associate Fellow