Drausin Wulsin
wulsin[at]seas.upenn.edu
[About]
I am a fourth year PhD student in
Bioengineering at the University of Pennsylvania in the Translational
Neuroengineering Lab with my advisor, Brian
Litt. I
graduated from Yale in 2007 with a B.S. with honors in
Biomedical Engineering. In my free time, I enjoy reading, sailing,
ultimate, and brewing beer.
[Interests]
My research focuses on intelligently processing large
amounts of clinical data using machine learning and statistical
modeling techniques. I am currently using nonparametric Bayesian models like
hierarchical Dirichlet processes (HDP), HDP-hidden markov models, and
beta processes to build large-scale models of seizures across many
patients. This work aims to intelligently compare and analyse seizures and other epileptic events within a patient and between patients. In previous work, I have used models like Restricted
Boltzmann Machines and Deep Belief Nets to learn clinical EEG
waveforms and then do pattern recognition and anomaly detection on
them.
[Refereed Publications]
Drausin Wulsin, Emily Fox, Brian Litt. Parsing Epileptic Events Using a Markov Switching Process for Correlated Time Series. International Conference on Machine Learning (ICML) 2013 [paper pdf, supp mat pdf]
Drausin Wulsin, Shane Jensen, Brian Litt. A Hierarchical Dirichlet Process Model with Multiple Levels of Clustering for Human EEG Seizure Modeling. International Conference on Machine Learning (ICML) 2012 [paper pdf, supp mat pdf]
D Wulsin, J Gupta, R Mani, J Blanco, B Litt. Modeling
electroencephalography waveforms with semi-supervised deep belief nets:
faster classification and anomaly measurement. Journal of Neural
Engineering 8 (3), 2011 [pdf]
J Viventi, ... D Wulsin, et al. Flexible, Foldable, Actively
Multiplexed, High-Density Surface Electrode Arrays for Mapping Brain
Activity in vivo with Single Trial Resolution. Nature
Neuroscience, 14 (12): 1599-1605, 2011
D Wulsin and B Litt. An Unsupervised Method for Identifying Regions
that Initiate Seizures on Intracranial EEG. Proceedings of the IEEE
Engineering in Medicine and Biology Conference (EMBC), 2011 [pdf]
A Pearce, D Wulsin, B Litt, J Blanco. Does the Morphology of
High-Frequency(100-500 Hz) Brain Oscillations Change During Epileptic
Seizures? Proceedings of the IEEE Asilomar Conference on Signals,
Systems, and Computers, 2011 (in press)
D Wulsin, J Blanco, R Mani, BLitt. Semi-Supervised Anomaly
Detection of EEG Waveforms Using Deep Belief Nets. Proceedings of the
International Conference on Machine Learning and Applications
(ICMLA) 2010 [pdf]
T Kyriakides, D Wulsin, E A Skokos, P Fleckman, A Pirron, J M
Shipley, R M Senior, P Borstein. Mice that lack matrix
metelloproteinase-9 display delayed wound healing associated with delayed
reepitheliazation and disordered collagen fibrillogenesis. Matrix
Biology 28 (2):65-73, 2009 [pdf]
[Code]
For simplicity, I have posted below code I think
others might find most useful, but if you would like to see code from any of
my publications, let me know. Of course, if you find bugs/errors or have
general suggestions, please let me know.
MLC-HDP Library (Matlab)
MLC-HDP_v1.0.zip
- OOP implementation of the multilevel clustering hierarchical Dirichlet process (MLC-HDP)
- OOP implementation of the multilevel clustering hierarchical Dirichlet process (MLC-HDP)
Deep Learning Object Oriented Library (Matlab)
DBNToolbox_v1.0.zip
- OOP implementatations of Restricted Boltzmann Machines (RBMs) and Deep Belief Nets
- OOP implementatations of Restricted Boltzmann Machines (RBMs) and Deep Belief Nets
[Data]
Most of my datasets are too large to post here, but if
you're interested in them, send me an email.