
Data-Driven Control Methods for Energy and Manufacturing


Roberto holds an M.Sc. and a Ph.D. in Particle Physics from the University of Torino, Italy. He has worked for several years in fundamental research as a senior fellow and data scientist at the CERN Experimental Physics division and on a research project supported by the Belgian National Fund for Scientific Research (FNRS). In 2018 he moved to EPFL to work on data mining and Machine Learning techniques for the built environment and renewable energies. He has started and led multiple collaborations with academic and industry partners in the energy domain. Roberto joined the SDSC in September 2021 as a Principal Data Scientist with the mission of accompanying industries, NGOs and international organizations through their data science journey.


Carl holds a Ph.D in Mathematics from École des Ponts ParisTech and Université Gustave Eiffel in Paris. He has broad interests in statistics and stochastic control, and works on reinforcement learning, generative methods and time series forecasting, with applications in various domains such as energy, finance and physics. He worked with EDF R&D and Finance des Marchés de l’Energie (FiME) laboratory on applications of machine learning to risk management, including time series generation and deep hedging. He joined the SDSC in 2022 as a senior data scientist in the academic team at École Polytechnique Fédérale de Lausanne (EPFL).


Victor joined as a Data Scientist in the SDSC Innovation team in 2023. He holds a Bachelor's degree in Mechanical Engineering (B.Eng.) from the University of Pretoria in South Africa, as well as Master's degrees in Robotics and Mechatronics (M.Sc.) and Artificial Intelligence (M.Sc.) from KU Leuven in Belgium.Prior to joining SDSC, he worked for several years as a consultant at Capgemini Engineering and as an R&D Engineer at Toyota Motor Europe. Within the Advanced Powertrain and Target Setting team at Toyota, Victor played a crucial role in the pre-development of innovative electric and fuel-cell vehicles. His responsibilities included leading the development and deployment of Natural Language Processing (NLP) tools and pipelines, data science and machine learning, building data analytics dashboards, statistical forecasting, powertrain design, optimal control system design, and strategic technical target setting. He is passionate about leveraging his combined Engineering and Data Science knowledge to solve complex problems in the industry.


After earning a MSc in Theoretical Physics at University of Padua, Giulio graduated in Quantitative Finance from Bocconi University. Before joining the SDSC industry cell in June 2021, he spent a few years working in the financial sector, where he mainly dealt with the application of machine learning to financial risk management. When not coding, Giulio spends his free time playing bass guitar, hiking and cooking.

Presentation
Overview
Controlling processes is a critical aspect of industrial systems, playing a pivotal role in maintaining process efficiency and safety and ensuring the quality of industrial products. Control methods are also used to optimize energy usage, for example, by controlling the operation of a building’s heating system and electric vehicle charging.Existing strategies range from simple feedback control loops to complex algorithms incorporating predictive models and artificial intelligence. During this one-day workshop, we will review the current state-of-the-art in data-driven control methods and discuss the existing challenges and opportunities related to their adoption in a production environment.
Details
Target Audience
Experienced professionals and data scientists from Energy and Manufacturing who wish to acquire hands-on knowledge of data-driven control methods and their usage are invited to attend. The workshop will be in English.
Objectives
By the end of the day, participants will:
- Learn the main principles behind the existing data-driven control methods mostly used in an industrial context.
- See how these methods work on real data collected by companies in manufacturing and energy domains.
- Gain an overview of the challenges related to deploying these methods in production.
Workshop organizers
Eleni Pratsini and Georgios Mavromatidis (Empa), Matthias Graeber (Bühler), Roberto Castello (SDSC).
Contacts: roberto.castello@epfl.ch
Instructors and speakers
Prof. Maryam Kamgarpour, Assistant Professor, System Control and Multiagent Optimization Research Laboratory (EPFL)
Prof. Zoltan Nagy, Assistant Professor at the University of Texas at Austin and Director of the Intelligent Environments Laboratory
Dr. Matthias Graeber, Head of Data Science at Bühler AG
Dr. Felix Bunning, Co-Founder and CEO at viboo
Dr. Georgios Mavromatidis, Head of Urban Energy Systems Laboratory at Empa
Dr. Carl Remlinger, Senior Data Scientist at SDSC, EPFL
Mr. Victor Van Wymeersch, Senior Data Scientist at Digitec Galaxus AG (formerly at SDSC, ETHZ)
Mr. Giulio Romanelli, Data Scientist at SDSC, EPFL
Dr. Roberto Castello, Principal Data Scientist at SDSC, EPFL
Registration Details
Registration fee: 150 CHF per person.
(Limited free seats for Empa, Bühler and SDSC partners. Coffee breaks and lunch are included.)
Maximum number of participants: 50
Please pre-register for the workshop by writing an email to Registrations@datascience.ch including your full name, company name, email address.
Note: Due to the limited number of seats, the participation will be confirmed by email a few weeks after the registration.
Event Location
The workshop takes place at the
Empa Academy
Überlandstrasse 129
CH-8600 Dübendorf
Directions
Program
09:00
Welcome Coffee
9:30
Welcome and introduction: Empa, Bühler, SDSC
9:40
Intro to Model Predictive Controls: Victor Van Wymeersch (Digitec Galaxus AG)
10:10
Intro to Reinforcement Learning: Giulio Romanelli (SDSC)
10:40
Coffee Break
11:00
AI process control at Bühler. From decision support to autonomous operation: Matthias Gräber (Bühler) and Julien Eberle (Arcanite)
11:30
Control systems in the AI age: Prof. Maryam Kamgarpour (EPFL)
12:00
Lunch break
13:30
Keynote (Zoom): “Reinforcement learning for building energy management”:
Prof. Zoltan Nagy (University of Texas)
14:15
Scalability of Building Energy Management Solutions: Carl Remlinger (SDSC)
14:30
Bringing predictive algorithms to smart thermostats: Felix Bünning (viboo)
14:45
Breakout rooms in preparation of the round table: All participants in groups
15:15
Coffee Break
15:45
Round table: “Real-world implementation of data-driven control methods: obstacles and opportunities.”
Matthias Gräber, Felix Bünning, Georgios Mavromatidis, Zoltan Nagy, Roberto Castello (moderator)
16:45
Closing remarks: Empa, Bühler, SDSC
17:00-18:30
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Dr. Olivier Verscheure is the director and founder of the Swiss Data Science Center (SDSC). Olivier also co-leads a joint training program between EPFL and HEC Lausanne, specifically designed for senior executives. Since 2018, Olivier has been a member of the Board of Directors of Lonza, a global leader in the life sciences sector. This company provides products and services to the pharmaceutical, biotechnology, and specialized healthcare industries.Olivier began his career at IBM Research after earning his Ph.D. in computer science from EPFL. He held several research and leadership positions at the IBM T. J. Watson Research Center in New York and co-created and co-directed the IBM Research center in Dublin, Ireland, before joining the EPFL in 2016.


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