KDD 2024

AI for Environment Special Day

Tuesday, August 27th 2024

@ Centre de Convencions Internacional de Barcelona

What is this about?

Environmental problems such as air pollution monitoring and prevention, flood detection and prevention, land use, forest management, river water quality, wastewater treatment supervision, etc. are more complex than typical real-world problems usually AI faces to. This added complexity rises from several aspects, such as the randomness shown by most of environmental processes involved, the 2D/3D nature of involved problems, the temporal aspects, the spatial aspects, the inexactness of the information, etc.

In fact, environmental problems belong to the most difficult problems with a lot of inexactness and uncertainty, and possibly conflicting objectives to be solved according to several classifications such as the one by Funtowicz & Ravetz (Funtowicz & Ravetz, 1999), which states that there are 3 kinds of problems. Also, they are non-structured problems in the classification proposed by H. Simon (Simon, 1966).

All this complexity means that to effectively solve those problems a lot of knowledge is needed. This knowledge can be theoretical knowledge expressed in mechanistic models, such as the Gravidity Newton’s Theory, or it can be empirical knowledge that can be expressed by means of empirical models, originated by some data and observations (data-driven knowledge) or by the expertise gathered by people when coping with such problems (model-driven knowledge, particularly expert-based knowledge).

Thus, the importance of KDD in Environmental Systems is very high, as many data can be explored/mined to get very useful knowledge for managing or supervising or planning environmental problems. Considering all above explained, the relevance of AI in Environmental Systems is really high.

Program Outline

Here's the program outline with details on each of the events happening.


Opening Remarks

Special Day Opening Remarks


Invited Talk 1 (Dr. Ranveer Chandra)

How data-driven farming could transform agriculture


Invited Talk 2 (Nikola Sivacki)

Optimising Recycling With Deep Learning


Invited Talk 3 (Prof. Peter Struss)

Environment – (How) Can We Help?


Tea Break


Invited Talk 5 (Prof. Uwe Schlink)

How can KDD advance personal exposure assessment?


Invited Talk 6 (Dr Karina Gibert)

Data-driven models in environmental problems


Distinguished Panelists

Ask me Anything on AI for Environment


Here are the speakers who will be presenting at the event.

Ranveer Chandra, Managing Director, Research for Industry, and CTO Agri-Food

Ranveer Chandra

Managing Director, Research for Industry, and CTO Agri-Food

Nikola Sivacki, Head Of Deep Learning, GreyParrot AI

Nikola Sivacki

Head Of Deep Learning, GreyParrot AI

Prof. Peter Struss, Prof. of Computer Science at Technical University of Munich

Prof. Peter Struss

Prof. of Computer Science at Technical University of Munich

Dr Karina Gibert, Full Prof. Universitat Politècnica de Catalunya-BarcelonaTech (UPC)

Dr Karina Gibert

Full Prof. Universitat Politècnica de Catalunya-BarcelonaTech (UPC)


Here are the organizers who are making this event possible.

TBD Organizers

Dr Miquel Sànchez-Marrè

Associate Prof.
Universitat Politècnica de Catalunya–BarcelonaTech (UPC)

Member of the Knowledge Engineering and Machine Learning Group (KEMLG-IDEAI) and Intelligent Data Science and Artificial Intelligence Research Centre (IDEAI-UPC). He co-founded

the spin-off company “Sanejament Intel·ligent S.L. (SISLtech)” [2003-2017] devoted to Advanced Control and Supervision of Environmental Systems. He is a pioneer member of ACIA (Catalan Association of Artificial Intelligence) and member of AEPIA (Spanish Association of Artificial Intelligence). He is a Fellow of the International Environmental Modelling and Software Society (iEMSs). He co-organized the first Environment and AI Workshop in Europe: Binding Environmental Sciences and Artificial Intelligence (BESAI 98) at ECAI conference in 1998. He has organised some international events in the AI field related to Environment (BESAI-ECAI, AAAI, iEMSs). His main research topics are Case-Based Reasoning, Intelligent Decision Support Systems, Recommender Systems, Machine Learning, Data Science, Knowledge Engineering, Integrated AI architectures, and AI applied to Environmental, Industrial and Health systems.

Dr Karina Gibert

Dr Karina Gibert

Full Prof.
Universitat Politècnica de Catalunya-BarcelonaTech (UPC)

Bachelor, Master and PhD in Computer Science with specialisations in computational statistics and artificial intelligence. Director and co-founder of the Intelligent Data Science and Artificial Intelligence

research centre at UPC (IDEAI-UPC, 2018-). Dean of the Illustrious Official College of Informatics Engineering of Catalonia (COEINF, 2023-). Expert and co-author of the Catalan Strategy for Artificial Intelligence Catalonia.AI (Catalan Government, 2018-). Advisor to the Catalan, Spanish, and European Commission governments on AI ethics and digital transformation. Awards: WomenTech Award 2023 (Women360), National Award for Informatics Engineering 2023 (General Council of InformaticsEngineering Colleges of Spain), Ada Byron Award 2022 (College of Computer Engineering of Galicia), donaTIC2018 Award (GenCat). Creu Casas Mention 2020-2021 (IEC).

TBD Organizers

Dr Tok Wee Hyong

Partner Director of Products, with the Cloud and AI organization at Microsoft

Seasoned Data and AI leader with a proven track record of running successful businesses and growing it from zero to sustained industry leadership positions.

He is the author of more than 10+ books, covering topics ranging from products and artificial intelligence including: “Practical Weak Supervision”, Practical Automated Machine Learning", and more. Prior to his current role, Wee Hyong led AI strategy and innovation. He was Head of AI Labs, where he led a global team of data scientists to deliver cutting-edge AI solutions from customers spanning different industries. Wee Hyong co-founded the AI for Earth Engineering and Data Science team, which seeded the foundation for many of the AI for Good initiatives, in using AI to solve some of the world's toughest sustainability challenges using AI/ML. Wee Hyong has a PhD in Computer Science from National University of Singapore.