I am a postdoctoral researcher working in the Computational Audition Lab at Brain and Cognitive Sciences Department at MIT. I am also a member of the Center for Brains Minds and Machines. Thanks for visiting my webpage!



NEWS:

We will be presenting two posters at Cosyne:

"Adaptive Compression of Statistically Homogenous Sensory

Signals" with Josh McDermott


"Statistical Inference under Resource Constraints in

Dynamic Environments" with Ann Hermundstad



New preprint: "Learning mid-level auditory codes from natural sound statistics" is available on arXiv

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:

 

 

2015 - to date, 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. In particular, I study the auditory system through the lens of stimulus statistics by constructing statistical models of natural sounds and perceptual mechanisms. I hope that this approach will bring us towards identifying general principles which govern information processing in biological systems.

Journal Papers:

 

 

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 Preprints:

 

 

Mlynarski W., McDermott J.H., "Learning mid-level auditory codes from natural sound statistics", arXiv:1701.07138
[q-bio.NC]

 

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: mlynar (at) mit (dot) edu


       wiktor.mlynarski (at) gmail (dot) com

 

 

Office Phone: 617 324 7270

 

 

Mailing Address: 77 Massachusetts Avenue, 46-4078, Cambridge, MA 02139

 

 

Physical Address: 43 Vassar Street, Office 46-4078