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.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
- 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, (forthcoming). Abstract pdf bib
- Igor Grossmann, Amanda Rotella, Cendri A. Hutcherson, Konstantyn Sharpinskyi, Michael E. W. Varnum, Sebastian Achter, Mandeep K. Dhami, Xinqi Evie Guo, Mane Kara-Yakoubian, David R. Mandel, Louis Raes, Louis Tay, Aymeric Vie, Lisa Wagner, Matus Adamkovic, Arash Arami, Patricia Arriaga, Kasun Bandara, Gabriel Banok, Frantisek Bartos, Ernest Baskin, Christoph Bergmeir, Michal Bialek, Caroline K. Borsting, Dillon T. Browne, Eugene M. Caruso, Rong Chen, Bin-Tzong Chie, William J. Chopik, Robert N. Collins, Chin Wen Cong, Lucian G. Conway, Matthew Davis, Martin V. Day, Nathan A. Dhaliwal, Justin D. Durham, Martyna Dziekan, Christian T. Elbaek, Eric Shuman, Marharyta Fabrykant, Mustafa Firat, Geoffrey T. Fong, Jeremy A. Frimer, Jonathan M. Gallegos, Simon B. Goldberg, Anton Gollwitzer, Julia Goyal, Lorenz Graf-Vlachy, Scott D. Gronlund, Sebastian Hafenbradl, Andree Hartanto, Matthew J. Hirshberg, Matthew J. Hornsey, Piers D. L. Howe, Anoosha Izadi, Bastian Jaeger, Pavol Kacmar, Yeun Joon Kim, Ruslan Krenzler, Daniel G. Lannin, Hung-Wen Lin, Nigel Mantou Lou, Verity Y. Q. Lua, Aaron W. Lukaszewski, Albert L. Ly, Christopher R. Madan, Maximilian Maier, Nadyanna M. Majeed, David S. March, Abigail A. Marsh, Michal Misiak, Kristian Ove R. Myrseth, Jaime M. Napan, Jonathan Nicholas, Konstantinos Nikolopoulos, O. Jiaqing, Tobias Otterbring, Mariola Paruzel-Czachura, Shiva Pauer, John Protzko, Quentin Raffaelli, Ivan Ropovik, Robert M. Ross, Yefim Roth, Espen Roysamb, Landon Schnabel, Astrid Schutz, Matthias Seifert, A. T. Sevincer, Garrick T. Sherman, Otto Simonsson, Ming-Chien Sung, Chung-Ching Tai, Thomas Talhelm, Bethany A. Teachman, Philip E. Tetlock, Dimitrios Thomakos, Dwight C. K. Tse, Oliver J. Twardus, Joshua M. Tybur, Lyle Ungar, Daan Vandermeulen, Leighton Vaughan Williams, Hrag A. Vosgerichian, Qi Wang, Ke Wang, Mark E. Whiting, Conny E. Wollbrant, Tao Yang, Kumar Yogeeswaran, Sangsuk Yoon, Ventura R. Alves, Jessica R. Andrews-Hanna, Paul A. Bloom, Anthony Boyles, Loo Charis, Mingyeong Choi, Sean Darling-Hammond, Z. E. Ferguson, Cheryl R. Kaiser, Simon T. Karg, Alberto Lopez Ortega, Lori Mahoney, Melvin S. Marsh, Marcellin F. R. C. Martinie, Eli K. Michaels, Philip Millroth, Jeanean B. Naqvi, Weiting Ng, Robb B. Rutledge, Peter Slattery, Adam H. Smiley, Oliver Strijbis, Daniel Sznycer, Eli Tsukayama, Austin van Loon, Jan G. Voelkel, Margaux N. A. Wienk, Tom Wilkening, The Forecasting Collaborative (2023) Insights into the accuracy of social scientists? forecasts of societal change. In: Nature Human Behaviour. Abstract pdf bib
- 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
- Abishek Sriramulu, Nicolas Fourrier, Christoph Bergmeir (2023) Adaptive Dependency Learning Graph Neural Networks. In: Information Sciences. 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
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...