Detailed information about the course

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Title

The Use of Machine Learning in the Behaviour, Ecology and Evolution

Dates

TBA soon

Organizer(s)

In collaboration with the Doctoral Program in Organismal Biology of the University of Neuchâtel

Dr. Andrés E. Quiñones, University of Neuchâtel
Dr. Christoph Dahl, University of Neuchâtel
Prof. Klaus Zuberbühler, University of Neuchâtel

Speakers

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

Description
Objectives

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

Content

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.

Location

University of Neuchâtel

Credits

1.0 ECTS

Evaluation

Full attendance and active participation

Information

When? dates tba soon

09h00-17h30

Where? University of Neuchâtel

Room TBA

Questions?

Marta Bellone
@: ecologie-evolution@cuso.ch
Phone: +41 (0)26 300 88 91

Expenses
Reimbursement:

PhD students of the DPEE are eligible for reimbursement of incurred travel expenses by train (half-fare card, and 2nd class). Please send the original tickets along with the reimbursement form to:

 Marta Bellone  Doctoral Program in Ecology and Evolution
 PER04 building
 University of Fribourg
 Chemin du Musée 10
 CH-1700 Fribourg

 

NO reimbursement of your individual meal expenses

 

Regarding reimbursement of accomodation, please contact the coordinator of the doctoral program (ecologie-evolution(at)cuso.ch) BEFORE the beginning of the course. NO reimbursement of accomodation without the agreement in advance of the course of the coordinator of the doctoral program.

Registration

CUSO PhD students: through your MyCUSO account. 

External participants (non-CUSO PhD students, post-docs, etc...): use the icon "registration" at top of page and the last gray box "non-CUSO student" ("personne hors myCUSO").

Registration fees:

CUSO DPEE PhD Students: free

Other CUSO members: please expect a registration fee to cover for social dinner and coffee breaks - you will be contacted by the coordinator of the program at the moment of your registration

External participants (i.e. from a non-CUSO university): Please contact ecologie-evolution(at)cuso(dot)ch before registering!

Places

30

Deadline for registration
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