Track / Overview

To reach the goals of the Swiss federal energy strategy 2050, the share of renewable energy has to be substantially increased as well as the efficiency in the energy system has to be improved. Strategies to reach these goals include the reduction of the energy demand by building (fabric) renovation, the optimisation of industrial processes, the improvement of the energy distribution, and the improved integration of renewable energy sources into the energy system.

The development of solutions to these problems requires novel approaches combining technical, social, and environmental sciences. A key driver for novel insight is the application of machine learning (ML) and artificial intelligence (AI) methods to analyse and model the massive data from components, markets, and the environment. Applications of data science range from curve fitting, pattern recognition tasks, to segmentation, optimisation and control. 

A key aim of this track is to connect data experts providing novel methods for the analysis and modelling of the data sets with energy experts applying ML and AI to solve their challenging problems on the demand and the production sides to increase the share of renewable energy sources, to achieve net-zero energy buildings and overall an energy system free of carbon emissions during its operation.

Track / Schedule

Introduction of the track

Innovaud session: Sustainable Energy

With Dimitri Torregrossa & Frédéric Dubois

Opening remarks

Towards collaborative and market-based analytics for energy applications

With Pierre Pinson

Unlocking the value in private data: opportunities for federated analytics in low voltage networks

With Ben Bowler

Industry 4.0 and energy transition

With Eva Urbano

Coffee break

Load prediction and flexible device recognition in smart grids

With Thomas Gall

Non-intrusive load monitoring

Analytical solutions to unmonitored neighbourhood power distribution problems

With Bruce Stephen

Bayesian methods for power grid identification

Physics of Failure and Model-based reasoning to facilitate CBM/PDM processes

With Franz Langmayr

Lunch break

Data-driven energy efficiency and flexibility for the building sector

With Pierre JC Vogler-Finck

Applied ML: Boosting the Energy Transition

With Thilo Weber

Calibration of building energy models at district scale

The CityLearn challenge

With Zoltan Nagy

Machine Learning Approach for Prediction of Congressional Voting Records on Climate Mitigation

With Thomas Chen

Coffee break

Surrogate modeling for national scale assessment of wind power technology innovation

With Dylan Harrison-Atlas

Physics-constrained deep learning for energy efficient control of buildings

With Jan Drgona

A deep reinforcement learning framework for fast charging of li-ion batteries

With Saehong Park

Incorporating power system physics into deep learning

With Priya Donti

Concluding remarks

Virtual Apero

Track / Speakers

Saehong Park

Postdoctoral Research Associate, UC Berkeley

Ben Bowler

Senior Research Associate, Lucerne University of Applied Sciences and Arts

Thomas Chen

Student, Academy for Mathematics, Science, and Engineering & Head of Outreach, Climate Data Hub

Bruce Stephen

Senior Research Fellow, University of Strathclyde

Eva Urbano

Researcher and PhD Student, Universitat Politècnica de Catalunya

Priya Donti

Ph.D. Candidate, Carnegie Mellon; Chair, Climate Change AI

Pierre Pinson

Professor, DTU

Franz Langmayr

PhD, Uptime Engineering GmbH

Thilo Weber

Developer and Data Scientist, geoimpact AG

Thomas Gall

CEO, ASGAL Informatik GmbH

Frédéric Dubois

Key Account Manager, Innovaud

Pierre JC Vogler-Finck

R&D scientist

Dimitri Torregrossa

Founder and CEO of Aurora's Grid

Dylan Harrison-Atlas

Senior Data Scientist, National Renewable Energy Laboratory

Jan Drgona

Data Scientist, Pacific Northwest National Laboratory

Zoltan Nagy

Professor, The University of Texas at Austin

Track / Co-organizers

Philipp Schütz

Professor, HSLU

Emanuele Fabbiani

Chief Data Scientist, xtream and PhD candidate, University of Pavia

Braulio Barahona

Senior Scientist, Lucerne University of Applied Sciences and Arts

Andreas Melillo

Research Associate, Lucerne University of Applied Sciences and Arts

Patrick Meyer

Researcher, HSLU

Esther Linder

Research associate, HSLU T&A

AMLD EPFL 2021 / Tracks & talks

AI & Sustainable Energy

Saehong Park, Ben Bowler, Thomas Chen, Bruce Stephen, Eva Urbano, Priya Donti, Pierre Pinson, Franz Langmayr, Thilo Weber, Thomas Gall, Frédéric Dubois, Pierre JC Vogler-Finck, Dimitri Torregrossa, Dylan Harrison-Atlas, Jan Drgona, Zoltan Nagy

09:00-17:00 April 26Online

AMLD Conversations: Oren Etzioni

Oren Etzioni

18:00-20:00 April 27Online

AI & Topology

Bryn Keller, Shusen Liu, Marco Armenta, Nicolas Berkouk, Elizabeth Munch

18:00-22:00 May 10Online

AMLD / Global partners