Academic

Research Interest

I am interested in the theory and application of Bayesian Statistics. In my Master-Thesis, I worked on the application of Bayesian Hierarchical Models to Meta-Analyses. Currently, I am using Approximate Bayesian Computation (ABC) for Earthquake models and work on data analysis for dependent point processess in a commercial context.

Teaching

2020/21 Semester 2:
Modern Regression and Bayesian Methods (PhD level course, Tutoring)
Statistics – Unlocking the World of Data (Massive Open Online Course, Teaching Assistant)
Applied Statistics (Tutoring and Marking)
Spreadsheets, R (Edinburgh Software Carpentry, Helper)

2020/21 Semester 1:
Probability (Tutoring and Marking)

2019/20 Semester 2:
Calculus and its Application (Tutoring and Marking)
Statistics Year 2 (Tutoring and Marking)
Sutton Trust Summer School: Statistics and Machine Learning (Content Creation and Live Session)

Talks

upcoming: EdinbR (May2021), ISBA 2021 World Meeting (June 2021)

  • Warwick Young Researchers Meeting: Bayesian Estimation of Hawkes Processes with Excitation and Inhibition — Tweets and Apparel Wholesale (April 2021, online)
  • Maxwell PG Colloquium Edinburgh: Earthquakes, Tweets, and Apparel Wholesale — Bayesian Estimation of Hawkes Processes (March 2021, online)
  • R Ladies Edinburgh: The ABC of ABC — Workflow and Challenges (Feb 2021, online)
  • SIAM-IAM Chapter Edinburgh: Think Like a Bayesian (Nov 2020, online)
  • MIGS PhD Conference Edinburgh: ABC Learning of Hawkes Processes with Missing or Noisy Event Times (Sept 2020, online)

Publications

Deutsch, I., & Ross, G. J. (2020). ABC Learning of Hawkes Processes with Missing or Noisy Event Times. ArXiv:2006.09015 [Stat]. http://arxiv.org/abs/2006.09015. Under Review.