Talks & awards

Invited talks

Guest lectures

  • 2017 – present, Guest Lecturer @ Imperial College Business School, “Machine learning for credit risk evaluation,” annual lecture for MSc students in Financial Economics and Business Analytics
  • 2020 webinar with FDP Institute, “Challenges of Algorithmic Fairness in Financial Services” Link
  • 2017 Panellist @ UCL, “Creating unbiased algorithms in a biased society,” invited on a panel as a part of the London Data Science Festival


  • 2021 Speaker @ Credit Scoring and Credit Control Conference XVII, “Spelling errors & non-standard language in peer-to-peer loan applications and the borrower’s probability of default”
  • 2021 Speaker @ AI, Ethics, and Society Conference, “Risk Identification Questionnaire for Unintended Bias in Machine Learning Development Lifecycle”
  • 2021 Speaker @ ACM CHI Conference on Human Factors in Computing, “Landscape and gaps in open source fairness toolkits”
  • 2020 Speaker @ Oxbridge Women in Computer Science, “Spelling errors in peer-to-peer (P2P) loan applications and probability of default”
  • 2020 Speaker @ Alan Turing Institute, AI UK Virtual Poster Session
  • 2019 Speaker @ AI@Oxford, lightning talk on “Silver lining of AI: fairness in a biased society”
  • 2018 Speaker @ Oxbridge Women in Computer Science, “Fairness trade-offs in machine learning”
  • 2017 Speaker @ Women in Data Science London, “New risks of artificial intelligence”
  • 2017 Speaker @ Deloitte Shared Services Conference, “EMILIE Chatbot”
  • 2017 Speaker @ Data Natives Berlin, “Governing AI Risks”
  • 2017 Panellist @ Data Natives Berlin, “Chatbots Panel”
  • 2016 Speaker @ QCon London, “Applied machine learning: predicting criminal recidivism”



  • 2022 2nd Place, Google-Deloitte Sustainability Hackathon
  • 2021 Winner, Best Paper Award, ACM CHI Conference on Human Factors in Computing
  • Standout 35 winner in the 2020 Innovate Finance Women in FinTech Powerlist. Link
  • 2020 Winner, Best presentation in “one-minute madness,” Oxbridge Women in Computer Science
  • 2020 Longlisted Most Influential Women in UK Tech, Computer Weekly. Link
  • 2019 Winner, ACM SIGAI Essay Competition on Artificial Intelligence
  • 2019 Winner, AI@Oxford Student Essay Competition on “Greatest opportunities and challenges of AI”
  • 2018 Shortlisted Nominee for Digital Professional of the Year, Digital Technology Leaders Awards
  • 2018 Top 5 in Europe: “Best use of data to achieve social impact” @ DatSci Awards for pro bono project forecasting demand for homeless shelters around the UK

Non-academic awards

  • 2022 winner, Oxford-Cambridge Varsity Blind Wine Tasting Competition (London, UK) Documentary Link
  • 2022 5th place, Agro Blind Wine Tasting Competition (Reims, France)

In the press: Features

Computer Lab feature “Improving diversity ‘would benefit society'” (2021). Link

“Most Influential Women in UK Tech: The 2020 longlist.” Computer Weekly (2020). Link

“Aviva-Cambridge Annual Report 2019-2020” University of Cambridge (2020). Link

Featured researcher: Aviva PhD student Michelle Seng Ah Lee” Link

67 Pall Mall documentary: Oxford vs. Cambridge Varsity Blind Wine Tasting Match Link