I study the mechanisms and consequences of collective behavior in biological and social systems. I am especially interested in understanding how animal groups make collective decisions and coordinate collective action, and in particular how these processes are affected by the social relationships between group members and the communication strategies they employ. I work across a range of study systems to tackle these questions, in close collaboration with researchers across a variety of disciplines.

Originally from Chicago, I did my undergraduate degree in Physics at Swarthmore College, then did my PhD in Quantitative and Computational Biology at Princeton University. I then moved across the pond to Europe, where I held post doc positions at the Max Planck Institute for Ornithology and the University of Zurich before moving to Konstanz in 2018. When not working, I enjoy traveling (especially via Swiss transit), cooking, eating, riding my bicycle, and learning German.

I am a behavioural ecologist interested mainly in the topics of mammalian vocal communication in social settings. For the past 9 years, I have focused on the interplay between different aspects of the social environment with different aspects of signalling tactics and signal structure. I have investigated how the presence, composition and attentive state of conspecific audience affect individuals` signalling behaviour. On the flip side, I have explored how individuals` are able to maximize their gain from signalling and reach a more abundant and attentive audience by correctly timing their signalling events and also producing signals which are more effective in gaining and maintaining audience attention.

Currently, I am in the process of conceptually and methodologically developing a project dealing with the motivational phase of vocal signalling in an attempt to detect the animals' preparations and intentions to vocalize. Additionally, I am also interested in investigating animals’ ability to maintain continuous vocal interactions which include multiple interactions turns and dynamic informational content.  I have a very strong preference for field-based, experimental studies, as they allow us to witness animal behaviour in its natural ecological and biological contexts. 

My current research aims to understand how differences in early experiences can affect an individual’s ability to coordinate effectively with group members later in life and whether and if so, how these differences ultimately affect individual fitness. I address these questions using two study systems, the domestic chicken and the common pheasant, and make use of the fact that both species are highly vocal and use acoustic signals to coordinate group activities. This work is in close collaboration with Prof Madden (University of Exeter) and Prof Radford (University of Bristol).

I completed my PhD on meerkat group coordination and decision-making at the University of Zurich, after which I studied the effect of anthropogenic disturbances on the social cohesion of California ground squirrels in collaboration with Dr Smith at Mills College. I also did a postdoc with Dr Meroz at Tel Aviv University to study the self-organisation of mutually shading sunflower plants. When not at work I love everything related to the arts and crafts and always appreciate a donation of wine-corks.

I am a physicist stumbling into the exciting field of animal ecology. In all generality, my research is about adapting machine- and deep-learning methods to scientific domains, such as bioacoustics.

Originally from Berlin, I have a somewhat scattered cv where I started as a trained audio technician, worked briefly in the film industry, and then studied physics, where I did a Bachelor's and Master's thesis in Geophysics. Then, I completed my doctorate in nonlinear quantum optics and collective many-body effects in nanoparticles. After a PostDoc at ETH Zurich, where I led the machine-learning team in the Nanostructures and Ultrafast X-ray Science group of Daniela Rupp, I am now working on representation learning of animal vocalizations.

The questions I am trying to answer are primarily concerned with finding a measure for similarity in animal vocalization (For example, for unsupervised classification of call types, subsequent identification of individuals, or sorting calls w.r.t. external levels of threat), where I use techniques from self-supervised learning.

When not sitting in front of a PC, I spend my remaining time with my family, where my daughter recently discovered that she is the boss of it all.

As a behavioral ecologist focused on group-living animals, I study how variation between individuals impacts their social interactions, how social interactions shape group-level properties, and how group-level properties affect individual experiences and fitness. While I am interested in many facets of social behavior, most of my work aims to understand how collective decisions, competitive regimes, and movement patterns arise from social processes and relate to fitness in wild animals. To do so, I combine information afforded by long-term monitoring of recognized individuals with fine-scale behavioral tracking technologies. Currently, I am collaborating with several field-based research projects to investigate these dynamics in meerkats, white-nosed coatis, and spotted hyenas.

Before joining CoCoMo, I received my B.S. from George Washington University, where I studied the socio-spatial behavior of juvenile chimpanzees in Gombe, Tanzania, and my Ph.D. from Stony Brook University, where I studied the relationship between individual variation and collective behavior of baboons in Amboseli, Kenya. When I’m not watching or thinking about animals, I like to watch or think about movies and to go to the beach with my friends.

I feel the most important questions in animal behaviour pertain to multi-scale spatiotemporal problems. Animals, unlike particles, behave in ways that can satisfy complicated rules accounting for their own pasts, presents, and anticipated futures. My work takes a holistic approach to understanding behaviour at both the individual and collective levels. In my postdoc and PhD in the CoCoMo group, I have shown that meerkats, coatis, and hyenas all seem to follow quantitatively similar decision-making principles to switch between behavioural states from moment to moment. I generally enjoy dealing with data from complex dynamic processes. My technical skills are primarily in accelerometry, machine learning, simulations (individual-based and others), and advanced programming.

Before Konstanz, I was in the Indian Institute of Science at Bangalore for an MSc and a BS in Biology. Apart from science, I enjoy reading, learning new languages, writing and satire, and picking up esoteric skills.

I’m a behavioural ecologist broadly interested in communication and collective movement in social groups. My research focuses on understanding the proximate and ultimate drivers of fission-fusion dynamics, as these processes offer insight into the costs and benefits of group living.

During my PhD, I simultaneously recorded the locations and vocalisations of all members of three wild white-nosed coati social groups in Panama. These data revealed that coatis frequently split into subgroups, often along kin lines, and that vocal communication likely plays a key role in coordinating their collective movements.

In my postdoc, I am investigating how the quantity, quality, and distribution of food resources influence these collective decisions. Building on methods developed during my PhD, I am also studying the patterns and drivers of fission-fusion dynamics across species. By examining these dynamics broadly, I aim to uncover how they shape population structures and wider ecological patterns.

Outside of research, I enjoy hiking, painting, and stroking cats.

I am an ecologist interested in studying how social and collective behaviors influence the survival and resilience of animal societies in dynamic, human-impacted environments. My research focuses on how animal groups make collective decisions and respond to threats, and how these processes are influenced by ecological change. Using long-term data from Murchison Falls National Park, Uganda, I investigate the social organization and collective movement of giraffes, and how oil development and poaching pressures alter their social networks and coordination. By integrating behavioral ecology with conservation science, I aim to elucidate how animal societies adapt to human-driven environmental change and how these insights can inform effective wildlife management and policy.

I am interested in social cognition, communication and decision-making in animal societies. I did my B.Sc. in Psychology at University of Marburg, and my M.Sc. in Ethology at Université Sorbonne Paris Nord. I completed my two master’s theses on vervet monkey friendships at University of Lausanne, and on chimpanzee social cognition at the Max-Planck Institute of Evolutionary Anthropology, respectively. After my master’s, I spent a year doing field work at the Kokolopori Bonobo Research Project in the Democratic Republic of the Congo, where I worked as a data collection coordinator and did extensive behavioral observations of wild bonobos.

For my PhD, I will be studying how spotted hyenas communicate to obtain relevant information which further shapes their decision-making on group coordination. I am excited to combine acoustic, GPS and accelerometer data to address questions on the social decision-making process in spotted hyenas from the Mara Hyena Project in Kenya.

I am originally from Taiwan, a subtropical island with high biodiversity in the Pacific. When I am not working, I enjoy painting with watercolor, camping, traveling with a canoe or my bike, running in the forest or snorkeling in the tropical ocean.

I am a collaborating PhD student from Michigan State University, where I am supervised by Kay Holekamp and Eli Strauss. I completed my undergraduate degree in wildlife ecology at Duke University. I am interested in behavioral ecology, especially foraging and hunting in social carnivores. I am a field biologist at heart and have spent close to 3 years observing spotted hyenas in the wild through the Mara Hyena Project in Kenya.

For my PhD, I am using GPS, audio, and accelerometer data collected through tracking collars to study the foraging behavior of these spotted hyenas. I am especially interested in the social dynamics that influence participation in group hunts.

I am originally from Germany, but moved to the United States when I was younger. I have enjoyed visiting Germany and practicing my German. When not at work, I enjoy riding my bike, lifting weights, reading books, and traveling.

I am interested in Bioacoustics, which nicely combines my passion for music, audio production and evolutionary biology. Within this field, I have been lucky to learn about aspects of sound production and communication in very different groups of animals and scientific contexts.

During my Bachelor’s degree at Universität Münster, I explored sound production and vocal learning in songbirds and hummingbirds. During my Master’s degree at Leiden University I investigated the involvement of visual cues in zebra finch call exchanges using a robotic bird. I also worked on a project focused on compiling high-quality datasets of grasshopper and cicada sounds for training species classifiers, as well as testing new machine-learning methods for encoding high-frequency audio signals.

In my PhD project, which is part of the EU-funded BioAcoustic AI Consortium, I will study the dynamics and functions of vocal interactions in social mammals. I will analyse movement and audio data collected from wild animal groups. I will also explore and implement machine-learning methods that are specifically suited to detect and analyse animal vocalisations from a broad range of species.

I am an audio signal processing researcher fascinated by the stories hidden within soundscapes. My work focuses on developing a more data-efficient machine learning framework designed to help us more effectively listen to and understand the complex animal world.

Currently a PhD student at Tampere University in Finland, I am also a member of the Marie Skłodowska-Curie Actions (MSCA) Bioacoustic AI network, which has brought me here. My academic journey began with a bachelor's in software engineering from Sichuan University in China, followed by a master's at Waseda University in Japan. There, my work on audio classification, speech enhancement and source separation, including an internship at NTT Corporation, solidified my passion for audio. My PhD project now focuses on developing a more data-efficient machine learning pipeline using active learning. The ultimate goal is to free researchers from the heavy burden of manual data annotation, allowing us to make sense of vast bioacoustic datasets more effectively.

I am generally a laid-back and quiet person. When I'm not at the computer, I like to completely recharge through sleeping, animation, music, and painting. After all, while the sea of learning is boundless, it's also important to know when to head for the shore.

I am Céline, a PhD student candidate based in the Netherlands and part of the BioacousticAI doctoral network. I am working with developing deep learning methods for bioacoustics data. More precisely, I investigate how to combine different datasets and bioacoustics tasks together to train deep learning models. I have a background in acoustics, signal processing and software engineering. I am excited to collaborate with Ari's group these next few months, where I will among others test the generalisation of their models to other species. I am also looking forward to know more about animal behaviour and the ongoing research here at the institute!