- Post-doc in the Akcay Lab at the University of Pennsylvania in Philadelphia
- Using theoretical and empirical experiments to study social learning dynamics and cultural evolution
- Passionate about facilitating discussions between researchers of different scientific fields, as well as between scientist and non-scientists
- Chair of the Association of Early-career Social Learning Researchers
- Editor of Cultured Scene, a journal for early-career researchers studying social learning and cultural evolution
The interplay of social networks and cultural dynamics
Where learning is predominantly social what an individual can learn is restricted by what information is retained in its social environment. This suggests a tight link between network structure and cultural learning dynamics. However, previous work has largely focused on fixed networks. Together with Erol Akcay, I am developing a model where both culture and network structure can evolve freely in response to different environmental conditions. The goal is to better understand how culture affects network structure and to complement the previous findings on how network structure affects culture.
Early-career Social Learning Researchers (ESLR)
In 2016, I set up small meetings specifically for early-career researchers. My goal was to form a network of like-minded scientists at a similar career-stage and with similar questions but (potentially) vastly different approaches. As social learning research is highly interdisciplinary from the get go I wanted to have representation form as many different research areas as possible. This all culminated in the formation of the ESLR society, which is now a fully formed society, equipped with its own journal, Cultured Scene. Aside from the journal, we organise an annual workshop and are currently working on a handbook for early-career researchers with crucial information such as where to apply for grants or how to find a job. Stay tuned, become a member, receive our newsletter.
I am curating a website that collects recent papers, conference calls, and online talks on social learning and cultural evolution (Social Learning Digest). This is my attempt to create an information hub for young social learning researchers.
Together with Jamie Soul I am organizing regular meetings of the R-programming community (FLSRGroup) at our faculty. We want to encourage researchers to use R for their daily data analysis, but also for reproducible documentation of their work (see e.g. How to use knitr). We provide code examples from our meetings on github. One of our projects involved a sentiment analysis of Christmas related tweets.
Smolla M, Akcay E. 2018 Cultural selection shapes network structure. bioRxiv 464883 doi: https://doi.org/10.1101/464883
Smolla M, Rosher C, Gilman RT, Shultz S. 2018 Reproductive skew affects social information use.
Smolla M et al. 2018 Second Annual Workshop of the Association of Early-Career Social Learning Researchers in St Andrews, Scotland. Evolutionary Anthropology: Issues, News, and Reviews (doi:10.1002/evan.21746) – FULL TEXT (preprint)
Kranstauber B, Smolla M, Safi K. 2016 Similarity in spatial utilisation distributions measured by the Earth Mover’s Distance. Methods Ecol. Evol. (doi:10.1111/2041-210X.12649) – Full Text – Supplementary Materials – Data and R Code
Smolla M, Alem S, Chittka L, Shultz S. 2016 Copy-when-uncertain: bumblebees rely on social information when rewards are highly variable. Biol. Lett. 12:20160188. (doi:10.1098/rsbl.2016.0188) – Full Text – Press Release – Supplementary Materials – Data and R Code
Smolla, M., Gilman, R. T., Galla, T. & Shultz, S. 2015 Competition for resources can explain patterns of social and individual learning in nature. Proc. R. Soc. B Biol. Sci. 282, 20151405. (doi:10.1098/rspb.2015.1405) – Full Text – Press Release – Supplemental Materials – Conference Poster
Smolla, M., Ruchty, M., Nagel, M. & Kleineidam, C. J. 2014 Clearing pigmented insect cuticle to investigate small insects’ organs in situ using confocal laser-scanning microscopy (CLSM). Arthropod Struct. Dev. 43, 175–181. (doi:10.1016/j.asd.2013.12.006) – Full Text – Animation
In other publications