6 Common Pitfalls for Forecast Evaluation
A topic I covered last year in some talks and papers are the “6 common pitfalls for forecast evaluation”. I’m discussing what are the most typical mistakes people new to forecasting would make. So this is relevant, for example, for Data Scientists that may not have any specialised training in forecasting, but in ML and Stats. It is a more lightweight take on the same topic covered in our quite detailed and more formal full paper here.María Zambrano (Senior) Fellowship at University of Granada, Spain
I’m very fortunate as I have been offered a María Zambrano (Senior) Fellowship at the University of Granada, Spain. My alma mater where I did the PhD. I’ve taken on this role now, and for the next 2.5 years I will be on a research position with minimal teaching to be able to focus further on my forecasting research. I’ll stay in connection and continue collaborating with my colleagues and friends at Monash University, where I now hold the appointment of an Adjunct Senior Research Fellow.Visiting Researcher at Meta
Since about a week I’m on a sabbatical for 6 months in the Infrastructure Data Science and Engineering team at Meta Platforms Inc. in Menlo Park, California. I’m fortunate that Zeynep Erkin Baz, Dario Benavides, and Ashish Kelkar have given me this opportunity to work with them in their great team. I’m looking forward to tackling interesting forecasting problems and learning a lot more about forecasting and other things along the way.Recent publications
- Jahan C Penny-Dimri, Christoph Bergmeir, Christopher M Reid, Jenni Williams-Spence, Luke A Perry, Julian A Smith (2023) Tree-based survival analysis improves mortality prediction in cardiac surgery. In: Frontiers in Cardiovascular Medicine, 10. Abstract bib
- Rakshitha Wathsadini Godahewa, Geoffrey I. Webb, Daniel Schmidt, Christoph Bergmeir (2023) SETAR-Tree: A Novel and Accurate Tree Algorithm for Global Time Series Forecasting. In: ECML-PKDD 2023, Turin, Italy. Abstract bib
- Rakshitha Godahewa, Geoffrey I Webb, Daniel Schmidt, Christoph Bergmeir (2023) SETAR-Tree: A Novel and Accurate Tree Algorithm for Global Time Series Forecasting. In: Machine Learning, 112, pp. 2555-2591. Abstract pdf bib
- Jahan C Penny-Dimri, Christoph Bergmeir, Christopher M Reid, Jenni Williams-Spence, Andrew D Cochrane, Julian A Smith (2023) Paying attention to cardiac surgical risk: An interpretable machine learning approach using an uncertainty-aware attentive neural network. In: Plos one, 18, (8), pp. e0289930. Abstract bib
- Dilini Rajapaksha, Christoph Bergmeir, Rob J Hyndman (2023) LoMEF: A framework to produce local explanations for global model time series forecasts. In: International Journal of Forecasting, 39, (3), pp. 1424-1447. Abstract bib
Recent and upcoming talks
- SETAR-Tree: A Novel and Accurate Tree Algorithm for Global Time Series Forecasting. (19 September 2023) More info...
- Short open problem talk: Hierarchical summary forecasting. (6 September 2023) More info...
- Probabilistic and Summary Forecasting, and some Pitfalls in Forecasting Practice. (25 June 2023) More info...