Riccardo Fusaroli
@fusaroli.bsky.social
Cognitive Science at Aarhus Uni. Curious about social interactions, symbolic behaviors, and meta-science. Focus on stats, computational modeling, machine learning, complex systems, language, exp semiotics and neuropsychiatric conditions. He/They.
Pinned
Hello new followers! I am a curious cognitive scientist, with a background in semiotics, a strong focus on quantitative and computational methods and meta-science and scattered interests in how we think, learn and function through conversations.
For a taste of my work, a thread of threads: 1/
For a taste of my work, a thread of threads: 1/
Uuuh new stuff to add! bsky.app/profile/aveh...
Posterior-SBC now also with peer-review stamp in Statistics and Computing doi.org/10.1007/s112... (update your bib files)
February 9, 2026 at 7:44 PM
Uuuh new stuff to add! bsky.app/profile/aveh...
Reposted by Riccardo Fusaroli
New (competition funded) PhD opportunity with me,
@iaciac.bsky.social and @dralgernon.bsky.social
www.findaphd.com/phds/project...
Higher-order networks and animal communication. Suited to someone keen on network science theory/computational modeling and keen to adapt this to ecology & evolution.
@iaciac.bsky.social and @dralgernon.bsky.social
www.findaphd.com/phds/project...
Higher-order networks and animal communication. Suited to someone keen on network science theory/computational modeling and keen to adapt this to ecology & evolution.
February 9, 2026 at 2:41 PM
New (competition funded) PhD opportunity with me,
@iaciac.bsky.social and @dralgernon.bsky.social
www.findaphd.com/phds/project...
Higher-order networks and animal communication. Suited to someone keen on network science theory/computational modeling and keen to adapt this to ecology & evolution.
@iaciac.bsky.social and @dralgernon.bsky.social
www.findaphd.com/phds/project...
Higher-order networks and animal communication. Suited to someone keen on network science theory/computational modeling and keen to adapt this to ecology & evolution.
awesome, thanks!
February 6, 2026 at 2:22 PM
awesome, thanks!
interesting. My last use was trying to feed pathfinder values back into brms, so it took a long time. I'll go back and use cmdstanr directly to try this magic :-)
February 6, 2026 at 2:12 PM
interesting. My last use was trying to feed pathfinder values back into brms, so it took a long time. I'll go back and use cmdstanr directly to try this magic :-)
love it when I'm teaching in class (at 8am😱), and the uni calls for cancelling in-person teaching due to snow, and the students look out to the winter wonderland and still decide to keep having the class :-)
February 6, 2026 at 7:41 AM
love it when I'm teaching in class (at 8am😱), and the uni calls for cancelling in-person teaching due to snow, and the students look out to the winter wonderland and still decide to keep having the class :-)
nice to know about beta-binomials, I'll cover them in my course in 6-7 weeks. As to whether it's worth: it's kind of a hassle to convert the pathfinder outcomes into initial values (or I haven't found a good way yet), so if it saves less than an hour, it's kind of pointless for me :-)
February 6, 2026 at 7:36 AM
nice to know about beta-binomials, I'll cover them in my course in 6-7 weeks. As to whether it's worth: it's kind of a hassle to convert the pathfinder outcomes into initial values (or I haven't found a good way yet), so if it saves less than an hour, it's kind of pointless for me :-)
Now the first lecture is live, but since I was so excited I forgot to share the screen on the recording for the first half of the class 🤦♂️:
- Video: youtu.be/YLEhNc5sOFE
- Slides: www.dropbox.com/scl/fi/okiys...
- Video: youtu.be/YLEhNc5sOFE
- Slides: www.dropbox.com/scl/fi/okiys...
February 5, 2026 at 1:59 PM
Now the first lecture is live, but since I was so excited I forgot to share the screen on the recording for the first half of the class 🤦♂️:
- Video: youtu.be/YLEhNc5sOFE
- Slides: www.dropbox.com/scl/fi/okiys...
- Video: youtu.be/YLEhNc5sOFE
- Slides: www.dropbox.com/scl/fi/okiys...
that's exactly what I'm using :-) I'll share the materials when I get there with the course (in 4-5 weeks I think)
February 4, 2026 at 4:46 PM
that's exactly what I'm using :-) I'll share the materials when I get there with the course (in 4-5 weeks I think)
ahah, I have targets on my list, but I am always so worried that I'll rabbithole there forever :-)
February 4, 2026 at 4:41 PM
ahah, I have targets on my list, but I am always so worried that I'll rabbithole there forever :-)
do you have any tip, selling point? my idea is to make my prior sensitivity checks more systematic and perhaps computationally efficient, but I haven't tried yet
February 4, 2026 at 4:18 PM
do you have any tip, selling point? my idea is to make my prior sensitivity checks more systematic and perhaps computationally efficient, but I haven't tried yet
5. Priorsense (n-kall.github.io/priorsense/) and DeclareDesign (declaredesign.org/r/declaredes...) are on my list to try out :-)
Prior Diagnostics and Sensitivity Analysis
Provides functions for prior and likelihood sensitivity analysis in Bayesian models. Currently it implements methods to determine the sensitivity of the posterior to power-scaling perturbations of the...
n-kall.github.io
February 4, 2026 at 1:37 PM
5. Priorsense (n-kall.github.io/priorsense/) and DeclareDesign (declaredesign.org/r/declaredes...) are on my list to try out :-)
I also want to hear about your favorite recent (<5 years 😅) Stan and Stan-adjacent developments that changed your bayesian framework (thinking about models, validating models, fitting models and checking their fit and how they break)!
as I'm revising my course materials, I keep stumbling upon cool @mc-stan.org developments.
Current favorites:
1. your model has funnels and you exhausted reparametrization ideas: metric = "dense_e" makes your HMC learn about covariance btw parameters. Sloooow, but effective!
1/
Current favorites:
1. your model has funnels and you exhausted reparametrization ideas: metric = "dense_e" makes your HMC learn about covariance btw parameters. Sloooow, but effective!
1/
February 4, 2026 at 1:35 PM
I also want to hear about your favorite recent (<5 years 😅) Stan and Stan-adjacent developments that changed your bayesian framework (thinking about models, validating models, fitting models and checking their fit and how they break)!
4. Simulation based calibration (mc-stan.org/docs/stan-us...) is a really neat theoretically grounded alternative to parameter recovery.
5/
5/
mc-stan.org
February 4, 2026 at 1:30 PM
4. Simulation based calibration (mc-stan.org/docs/stan-us...) is a really neat theoretically grounded alternative to parameter recovery.
5/
5/
2. quickly iterate for whatever reason: pathfinder (mc-stan.org/docs/referen...) is an amazing quick approximation for HMC.
3. bonus point: for *some* models, using the pathfinder's approximated results as initial values makes the HMC go vrooom! (no idea yet as to a priori which models)
3/
3. bonus point: for *some* models, using the pathfinder's approximated results as initial values makes the HMC go vrooom! (no idea yet as to a priori which models)
3/
Pathfinder
mc-stan.org
February 4, 2026 at 1:30 PM
2. quickly iterate for whatever reason: pathfinder (mc-stan.org/docs/referen...) is an amazing quick approximation for HMC.
3. bonus point: for *some* models, using the pathfinder's approximated results as initial values makes the HMC go vrooom! (no idea yet as to a priori which models)
3/
3. bonus point: for *some* models, using the pathfinder's approximated results as initial values makes the HMC go vrooom! (no idea yet as to a priori which models)
3/
as I'm revising my course materials, I keep stumbling upon cool @mc-stan.org developments.
Current favorites:
1. your model has funnels and you exhausted reparametrization ideas: metric = "dense_e" makes your HMC learn about covariance btw parameters. Sloooow, but effective!
1/
Current favorites:
1. your model has funnels and you exhausted reparametrization ideas: metric = "dense_e" makes your HMC learn about covariance btw parameters. Sloooow, but effective!
1/
February 4, 2026 at 1:30 PM
as I'm revising my course materials, I keep stumbling upon cool @mc-stan.org developments.
Current favorites:
1. your model has funnels and you exhausted reparametrization ideas: metric = "dense_e" makes your HMC learn about covariance btw parameters. Sloooow, but effective!
1/
Current favorites:
1. your model has funnels and you exhausted reparametrization ideas: metric = "dense_e" makes your HMC learn about covariance btw parameters. Sloooow, but effective!
1/
I remember him talking about the appropriation of the semiotic modes of production in this context, which is very fitting :-)
February 4, 2026 at 1:04 PM
I remember him talking about the appropriation of the semiotic modes of production in this context, which is very fitting :-)
darn those pesky null models! ;-)
February 4, 2026 at 12:55 PM
darn those pesky null models! ;-)
Reposted by Riccardo Fusaroli
The handaxe enigma continues!
Brand-new method shows: one can shape a handaxe without cultural models. Paper open access: www.sciencedirect.com/science/article/pii/S0305440326000154
Brand-new method shows: one can shape a handaxe without cultural models. Paper open access: www.sciencedirect.com/science/article/pii/S0305440326000154
February 4, 2026 at 11:26 AM
The handaxe enigma continues!
Brand-new method shows: one can shape a handaxe without cultural models. Paper open access: www.sciencedirect.com/science/article/pii/S0305440326000154
Brand-new method shows: one can shape a handaxe without cultural models. Paper open access: www.sciencedirect.com/science/article/pii/S0305440326000154
very much in line with how Eco described semiotic guerrilla as a reaction to passive media reception: disruptnow.org/disruptive-s...
Towards a Semiological Guerrilla Warfare by Umberto Eco (1986)
Eco argues that controlling the message is less important than controlling the possible interpretations of the message. To disrupt the mainstream mass media, Eco suggests using guerilla tactics, such ...
disruptnow.org
February 4, 2026 at 12:42 PM
very much in line with how Eco described semiotic guerrilla as a reaction to passive media reception: disruptnow.org/disruptive-s...
Reposted by Riccardo Fusaroli
New preprint! So, what's a multiverse analysis good for anyway?>
With @jessicahullman.bsky.social and @statmodeling.bsky.social
juliarohrer.com/wp-content/u...
With @jessicahullman.bsky.social and @statmodeling.bsky.social
juliarohrer.com/wp-content/u...
February 4, 2026 at 10:24 AM
New preprint! So, what's a multiverse analysis good for anyway?>
With @jessicahullman.bsky.social and @statmodeling.bsky.social
juliarohrer.com/wp-content/u...
With @jessicahullman.bsky.social and @statmodeling.bsky.social
juliarohrer.com/wp-content/u...
wanna learn about cognitive modeling and love pizza? I am revising my cognitive modeling course notes and could use some feedback (or you might just enjoy learning about cog modeling in R and Stan): fusaroli.github.io/AdvancedCogn...
(only chapter 1-3 are in place, the others will come)
(only chapter 1-3 are in place, the others will come)
Chapter 2 The Pizza Experiment | Advanced Cognitive Modeling Notes
My notes for the advanced cognitive modeling course - 2026
fusaroli.github.io
January 30, 2026 at 9:08 AM
wanna learn about cognitive modeling and love pizza? I am revising my cognitive modeling course notes and could use some feedback (or you might just enjoy learning about cog modeling in R and Stan): fusaroli.github.io/AdvancedCogn...
(only chapter 1-3 are in place, the others will come)
(only chapter 1-3 are in place, the others will come)
my youngest has been playing his favorite boardgame with very different comments now...
January 30, 2026 at 8:16 AM
my youngest has been playing his favorite boardgame with very different comments now...
Reposted by Riccardo Fusaroli
📣 Our introduction to structural causal models in science studies is now published:
doi.org/10.1162/QSS....
@tklebel.bsky.social and I tried to make our introduction as accessible as possible. We illustrate the theory by three case studies based on a simulated model of Open Science. 🧵(1/6)
doi.org/10.1162/QSS....
@tklebel.bsky.social and I tried to make our introduction as accessible as possible. We illustrate the theory by three case studies based on a simulated model of Open Science. 🧵(1/6)
January 27, 2026 at 10:24 AM
📣 Our introduction to structural causal models in science studies is now published:
doi.org/10.1162/QSS....
@tklebel.bsky.social and I tried to make our introduction as accessible as possible. We illustrate the theory by three case studies based on a simulated model of Open Science. 🧵(1/6)
doi.org/10.1162/QSS....
@tklebel.bsky.social and I tried to make our introduction as accessible as possible. We illustrate the theory by three case studies based on a simulated model of Open Science. 🧵(1/6)
my only speculation was that it was really old japanese, but google lens confirms it's some random chinese :-)
January 23, 2026 at 11:28 AM
my only speculation was that it was really old japanese, but google lens confirms it's some random chinese :-)