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.

Read Moreā€¦

FUZZ-IEEE Explainable Energy Prediction Competition

My PhD student Dilini Sewwandi Rajapaksha and I made first place in the FUZZ-IEEE Explainable Energy Prediction Competition. The winners were announced at the IEEE International Conference on Fuzzy Systems, Luxembourg, 2021.

We proposed a novel algorithm to provide Local Interpretable Model-agnostic Rule-based Explanations for Forecasting, a paper and more descriptions will be available hopefully soon.

IEEE-CIS Technical Challenge on Predict+Optimize for Renewable Energy Scheduling

We’ve just launched the IEEE-CIS Technical Challenge on Predict+Optimize for Renewable Energy Scheduling, with US$20k in prize money. You’ll need to forecast energy demand and solar power production for a couple of buildings on the Monash Clayton campus, and then use the forecasts to optimally schedule lectures and battery charging/discharging. We’re looking forward to your great submissions!

More information is here

Recent publications

  • Md Mohaimenuzzaman, Christoph Bergmeir, Ian West, Bernd Meyer (2023) Environmental Sound Classification on the Edge: A Pipeline for Deep Acoustic Networks on Extremely Resource-Constrained Devices. In: Pattern Recognition, 133, pp. 109025. Abstract bib
  • Gautier Pialla, Hassan Ismail Fawaz, Maxime Devanne, Jonathan Weber, Lhassane Idoumghar, Pierre-Alain Muller, Christoph Bergmeir, Daniel Schmidt, Geoffrey Webb, Germain Forestier (2022) Smooth Perturbations for Time Series Adversarial Attacks. In: Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 485-496. Abstract bib
  • Aidan Quinn, Melanie Simmons, Benjamin Spivak, Christoph Bergmeir (2022) RNN-BOF: A Multivariate Global Recurrent Neural Network for Binary Outcome Forecasting of Inpatient Aggression. In: 2022 International Joint Conference on Neural Networks (IJCNN), pp. 1-8. Abstract bib
  • Md Mohaimenuzzaman, Christoph Bergmeir, Bernd Meyer (2022) Pruning vs XNOR-Net: A Comprehensive Study of Deep Learning for Audio Classification on Edge-Devices. In: IEEE Access, 10, pp. 6696-6707. Abstract DOI bib
  • Priscila Grecov, Ankitha Nandipura Prasanna, Klaus Ackermann, Sam Campbell, Debbie Scott, Dan I Lubman, Christoph Bergmeir (2022) Probabilistic causal effect estimation with global neural network forecasting models. In: IEEE Transactions on Neural Networks and Learning Systems. Abstract bib

Recent and upcoming talks

  • ACML 2020 Tutorial: Forecasting for Data Scientists. (18 November 2020) More info...
  • Facebook Forecasting Summit: Forecasting for Data Scientists. (6 October 2020) More info...
  • Recurrent Neural Networks for Forecasting. (21 November 2019) More info...