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 / 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

PhD Candidate, Carnegie Mellon & Chair, Climate Change AI

Pierre Pinson

Professor, DTU

Franz Langmayr

Managing Director, Uptime Engineering GmbH

Thilo Weber

Developer and Data Scientist, geoimpact AG

Thomas Gall

CEO, ASGAL Informatik GmbH

Frédéric Dubois

Key Account Manager, Innovaud

Pierre Vogler-Finck

R&D Scientist, Neogrid

Dimitri Torregrossa

Founder & CEO, Aurora's Grid

Dylan Harrison-Atlas

Senior Researcher, National Renewable Energy Laboratory

Jan Drgona

Data Scientist, Pacific Northwest National Laboratory

Zoltan Nagy

Professor, The University of Texas at Austin

Jean-Sebastien Brouillon

PhD Candidate, EPFL

Dongjiao Ge

Research Associate, University of Oxford

Portia Murray

Data Scientist, CLEMAP

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 & Pharma

Simone Lionetti, Camille Marini, Enkelejda Miho, Jonas Richiardi, Kurt Stockinger, Patrick Schwab, Kostas Sechidis, Lisa Herzog, André Jaun, Khaled El Emam, Cécile Louwers, Jason Plawinski, Limor Shmerling Magazanik, Agata Mosinska, Marius Garmhausen

09:00-17:00 August 23Online

AI & Online Business

13:30-17:00 September 14Forum Rolex, EPFL and online

AI for Risk in Financial Institutions

09:00-12:30 September 14Forum Rolex, EPFL and online

AMLD / Global partners