I am an IST Plus Fellow based in Gašper Tkačik's group at the Institute of Science and Technology Austria. Thanks for visiting my webpage!


Our paper: "Efficient and adaptive sensory codes" is now out in Nature Neuroscience

Our paper: "Statistical analysis and optimality of neural systems" is now out in Neuron

New preprint: "Attentional dynamics of efficient codes" is available on bioRxiv.

We are organizing the Inferring and testing optimality in perception and neurons workshop at the Bernstein Conference 2020. The event will be held online on Sept 29th 2020.

We have two posters at Cosyne 2020 in Denver:

"Top-down attention as efficient perceptual inference"

with Gašper Tkačik

"Hierarchical inference guides perceptual decision-making

in a dynamic environment" with Julie Charlton, Yoon Bai,

Ann Hermundstad and Robbe Goris

Our paper: "Ecological origins of perceptual grouping principles in the auditory system" is now out in PNAS.

New preprint: "Efficient and adaptive sensory codes" is available on bioRxiv.

We have a poster at Cosyne 2019 in Lisbon:
"Speed-information-task performance trade-offs in efficient sensory adaptation"

Our paper: "Adaptive coding for dynamic sensory inference" is now out in eLife

We have two posters at Cosyne 2018 in Denver:

"Co-occurrence statistics of natural sound features

predict perceptual grouping" with Josh McDermott

"Sensory codes for optimizing tradeoffs between task

performance, adaptation speed and resource use"

with Ann Hermundstad

Our paper: "Learning mid-level auditory codes from natural sound statistics" is out in Neural Computation

I'm organizing the Natural Scene Statistics and Sensory Representations workshop at the Bernstein Conference in Berlin on 21st Sept 2016

Education and working experience:



2018 - to date, IST Plus Fellow, Institute of Science and Technology Austria, Klosterneuburg, Austria



2015 - 2018, Postdoctoral Associate, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, USA



2011 - 2015, PhD in Computer Science, Max-Planck Institute for Mathematics in the Sciences, Leipzig, Germany



2009 - 2011, Research Assistant in Bioinformatics, Department of Molecular Neuropharmacology, Institute of Pharmacology, Polish Academy of Sciences, Kraków, Poland



2005 - 2010 MSc in Computer Science, Jagiellonian University, Kraków, Poland

An important property separating living systems from inorganic matter is the ability to build and maintain internal models of the world. In order to achieve that, organisms extract regularities present in environments in which they evolved and developed.


The brain seems to be a prominent example of a system employing such a strategy. It has been demonstrated that numerous properties of perception and sensation can be explained as an adaptation to the natural environment.


In my work I follow these lines of thought. I analyze the statistical structure of natural stimuli, develop optimal processing strategies which might be approximated by biological systems and verify theoretical predictions through experimental data analysis. I hope that this approach will bring us towards identifying general principles which govern information processing in Nature.

Preprints and manuscripts under review:



Mlynarski W., Tkacik G., "Attentional dynamics of efficient codes", bioRxiv preprint, (preprint link)



Journal Papers:



Mlynarski W.*, Hermundstad A.*, "Efficient and adaptive sensory codes", Nature Neuroscience, 2021, (link)


Mlynarski W.*, Hledik M.*, Sokolowski T., Tkacik G. "Statistical analysis and optimality of neural systems", Neuron, 2021, (link, press release)


Mlynarski W., McDermott J.H., "Ecological origins of perceptual grouping principles in the auditory system", Proceedings of the National Academy of Sciences, 2019 (link)


Mlynarski W.*, Hermundstad A.*, "Adaptive coding for dynamic sensory inference", eLife, 2018 (link, press release)


Mlynarski W., McDermott J.H., "Learning mid-level auditory codes from natural sound statistics", Neural Computation, 2018 (link)


Mlynarski W. "The opponent channel population code of sound location is an efficient representation of natural stereo sounds", PLOS Computational Biology, 2015 (link)


Mlynarski W., Jost J. "Statistics of natural binaural sounds", PLOS One, 2014 (link)


Mlynarski W, "Efficient coding of spectrotemporal binaural sounds leads to emergence of the auditory space representation", Frontiers in Computational Neuroscience, 2014 (link)


Mlynarski W., Freigang C., Bennemann J., Stoehr M. and Ruebsamen R.. "Position of acoustic stimulus modulates visual alpha activity", NeuroReport, 2014 (link)


Korostynski M., Piechota M., Dzbek J., Mlynarski W., Szklarczyk K., Ziolkowska B. and Przewlocki R. "Novel drug-regulated transcriptional networks in brain reveal pharmacological properties of psychotropic drugs", BMC Genomics, 2013 (link)




Conference Papers and Technical Reports:



Mlynarski W., McDermott J. H. "Natural sound statistics predict auditory grouping principles", CCN 2018, Philadelphia, USA, Proceedings  


Mlynarski W., "Sparse, complex-valued representations of natural sounds learned with phase and amplitude continuity priors", arXiv:1312.4695 [cs.LG]


Mlynarski W., "Learning binaural spectrogram features for azimuthal speaker localization", Interspeech 2013, Lyon, France

Email: wiktor.mlynarski (at) ist (dot) ac (dot) at

       wiktor.mlynarski (at) gmail (dot) com



Address: Am Campus 1, 3400 Klosterneuburg, Austria



Google Scholar: link



Twitter: @samplingRage