0368-5141--01 Semester I/II

Monday 16-17.30 Schreiber 309

Prof. Nathan Intrator

___________________________________________________________________________________________________

Seminar Overview

The seminar time will be used for a meeting of my lab students or prospective students who are interested in the field.

We shall have formal presentations as well as informal discussions.

Current applications include:

Brain Imaging: EEG, fMRI – Epilepsy detection, network discovery, brain state interpretation

Biomedical Signal Processing: Cardiac functionality interpretation

Earthquake Detection

Financial Markets Anomaly Detection

Presentations should emphasize the machine learning, robust statistics and robust modeling in their work.

Nathan’s office hours: Schreiber 221, x7598, Wednesday 4-5 (please set up by email)

NCSP Past seminars 2004-5 Sem I 2004-5 Sem II 2006-7 Brain Imaging 2007-8 2008-9 2009-10

Other relevant seminars: Eshel Ben Yaakov Eytan Ruppin Ron Shamir Hezy Yeshurun

Seminar Forum: http://groups.google.com/group/ncsp-cs-tau (please register, future announcments will be made through here)

Planned Presentations

Date	Title	Speaker
Nov 27	Short spotlight presentations by all participants
Dec 5	Band-limited Granger Causality of Human ECoG	Shahar Jamshy
Jan 2	Feature Extraction Methods for Structural and Functional Medical Imaging	Shahar Jamshy
Jan 9	Overview of NIPS workshop on Causality and Connectivity in Neuroscience (Written summary of both workshops)	Shahar Jamshy
Jan 16	Summary of NIPS workshop on Machine Learning and Interpretation in Neuro-Imaging	Ilana Podlipsky
Jan 23	Robust estimation in the presence of outliers: a machine learning approach	Saha Aparstin

Participating Students

Name	Area of Interest	Degree	Supervisor
Zack Dvey-Aharon	Neuroscience	Ph.D.	Nathan Intrator
Shahar Jamshy	Machine Learning, Connectivity, and Causality for Neuroimaging	Ph.D.	Nathan Intrator & Talma Hendler
Yehudit Hasson	Neuroscience	Ph.D.	Nathan Intrator
Chen Levi	MRS and MRI of the Central Nervous System and Image processing	M.Sc.	Yoram Cohen
Jonathan Herzig	Machine learning analysis on biological signals, Heart sounds	M.Sc.	Nathan Intrator
Sasha Aparstin	Sonar, Signal Processing, Machine Learning, Fusion of experts	Ph.D.	Nathan Intrator
Omer Meir	Sonar	M.Sc.	Nathan Intrator

General instructions for seminar presenters

The presentation should have an introductory component that can enable all students understand the background of the seminar. They should then have a methodological component which explains at least a single method that can be used in a variety of applications. Finally, there should be some application results which demonstrate the usefulness of the proposed methods.

In contrast, a review presentation should describe several computational methods which are aimed at addressing a specific problem, together with a clear background of that problem. Preferably some comparison between the methods should be provided.

Abstract of the presentation should be sent to me up to three days before the presentation and a slides up to a day before the presentation.

Relevant Reading Material

Sound analysis

Auditory display of hyperspectral colon tissue images

Singing the Mind Listening

Sound features

Chris Raphael Rhythm changes

Biomedical signals and sensors

Robust measurement of Carotid Heart sound delay

Heart Mechanical and Electrical System

Segmentation of EKG signals

EKG Overview