The use of machine learning models in behaviour, ecology & evolution - joint with CUSO EE

POSTPONED TO 2020 - date tba

Course in collaboration with the CUSO Doctoral Program in Ecology & Evolution


Flyer (coming soon)


Machine learning and artificial intelligence have shown outstanding advances in the last decade. The building blocks of these technologies have the potential to aid in many steps of scientific workflows, such as modelling, data collection and data analysis. Furthermore, those algorithms can be used as a metaphor for understanding human and animal minds.

In this workshop, we will have lectures and discussions lead by people that use machine-learning technologies to answer questions in ecology and evolution.


  • Dr. Kristin Branson, Howard Hughes Medical Institute, USA
  • Prof. Tamás Vicsek, Eötvos University, Hungary
  • Dr. Brenden Lake, New York University, USA
  • Prof. Shimon Edelman, Cornell University, USA
  • Prof. Rineke Verbrugge, University of Groningen, Netherlands
  • Dr. Philip Wadewitz, University of Göttingen, Germany


In recent years, technological advances in the field of Artificial Intelligence and machine learning have revolutionized many areas of the world’s economy. AI technologies and machine learning in particular is in the process of gaining access to nearly every research domain due to their unprecedented capability of extracting knowledge from high-dimensional and complex data sets.

In behavioural sciences two research applications are emerging: firstly, the advent of digital sensor technology allows continuous data recording of animals freely and naturally interacting in wild or semi-wild conditions. For example, it is possible now to track the movements of animals in real time, as well as their vocalization and social interactions. The challenge becomes how to find meaningful patterns in such highly complex data. Machine learning provides the means of capturing typicalities in behaviour that would have remained unnoticed by human observers (traditional approach). The digital revolution and machine learning together shape traditional research domains toward interdisciplinary research lines.

Secondly, latest developments in computer technology allow modelling more complex simulations of naturally observed phenomena, resulting in sets of algorithms matching, and in some cases surpassing, human cognitive abilities that were previously considered unique to our species. Despite their impressive performance, machine-learning algorithms are still very far from the flexibility and versatility of natural cognitive systems. The achievements and limitations of machine learning technologies raise questions about the similarities and differences between natural and artificial cognitive systems.

These two types of AI applications have the potential to revolutionize the way we understand and study behaviour. However, research groups focusing on animal and human behaviour tend to be in departments that lack the technical expertise to offer courses in the application AI technologies. More generally, the use of these technologies requires the interdisciplinary link between researchers with the conceptual background in animal behaviour and researchers with the technical expertise in these technologies.

In this course, we provide the missing link by inviting a group of speakers working at the interface of these fields. This course offers insights into these growing research fields through interactive lectures.

General information

This course has been post-poned to 2020. The new dates will be announced soon

Dates: 28-29 November 2019

Schedule: 8.55-17.00

Venue:  University of Neuchâtel, Faculté des Sciences, Emile-Argand 11, UniMail, building X, room TBA

ECTS: 1.0 (Scientific activities)

Evaluation: Full attendance and active participation

Information: Please contact Dr. Andrès Quinones or the doctoral program coordinator Dr Sara Santi, or refer to the webpage of the CUSO doctoral program in Ecology & Evolution

Registration fee: free for PhD student enrolled in the Organismal Biology and CUSO EE doctoral programs. Other participants: please refer to the webpage of the event or contact Dr. Marta Bellone, coordinator of the CUSO EE program.

Travel expenses: For participants of the Interuniversity doctoral program in organismal biology (DP-biol ): see reimbursement conditions

For participants of the CUSO doctoral program in Ecology and Evolution: see CUSO E&E web site

Make sure to sign the attendance sheet each and every day and take your certificate of attendance at the end of the course (no attestation will be sent by mail)


  • This course open to all PhD students, however until DATE tba priority is given to "Interuniversity doctoral program in organismal biology" and CUSO Ecology and Evolution participants.
  • Post-docs are welcome as long as places are available.
  • Maximum number of participants: 30

Registration through the web only: opening in 2020

Cancellation fees: free before the deadline, after the deadline: CHF 50.

Please note the cancellation policy

Deadline: date tba