Neural Computation & Signal
Processing Lab (NCSP)
Prof.
Open Projects
Updated: Aug, 2007
Outside of Academia job opening:
(Please
contact me for more information)
1. Part time biomedical
engineer or computer science student: Good knowledge of physiology as well as
signal processing.
Below,
is a description of several projects which are open for new MSc
or PhD students. If you are interested, please contact
me regarding these projects or other projects that you would like to discuss.
Cardio/Pulmonary Functionality
Inference
The
collection of projects are aimed at advancing current state of the art in
understanding cardiac functionality and its relation to the sounds emanated
from the heart. These projects relay heavily on physiological understanding of
the cardio pulmonary system. This is provided by Prof.
Inference
of basic cardiac functionality
It is
well known that there are strong interactions between the (somatic) sensory
system of the body and its brain activity. In particular, we are interested in
the interaction of brain activity under high blood pressure and other cardiac
malfunction. We are also interested in the connection between the sensory
system and epilepsy.
First
step in this project relies on concurrent recording of EEG data and ECG data in
epileptic patients.
Students
interested in this project should gain basic knowledge in signal processing,
learning machines and physiology and be prepared to spend some of their time in
a hospital environment. All the brain
imaging related work are in conjunction with Dr.
Analysis
of Heart Sounds Via HMM
Related
work by Ray
Watrous. See also presentation by Daniel Gil at
my Advanced
Seminar, as well as background and publications of Guy Amit also in the advanced
seminar page. See also, Alex Weibel TDNN. Outline:
Follow speech recognition approach of extracting automatic features, vector
quantization, HMM, Segmentation and Clustering.
Brain Imaging
Analysis
of Brain Imaging Data in Conjunction with Cardiac Activity
It is
well known that there are strong interactions between the (somatic) sensory system
of the body and its brain activity. In particular, we are interested in the
interaction of brain activity under high blood pressure and other cardiac
malfunction. We are also interested in the connection between the sensory
system and epilepsy.
First
step in this project relies on concurrent recording of EEG data and ECG data in
epileptic patients.
Students
interested in this project should gain basic knowledge in signal processing,
learning machines and physiology and be prepared to spend some of their time in
a hospital environment. All the brain
imaging related work are in conjunction with Dr.
Analysis
of fMRI/EEG data: Emotional Effects
This
work is done in collaboration with Dr.
There
are subprojects in signal processing, machine learning and computer vision in
this subtopic.
Computational Genomics
Multi-database
mining and graph mining algorithms
Current
knowledge about genomics and proteomics is expanding rapidly with many
databases being created for special purposes. This project will draw
information from a collection of different databases, to obtain maximal amount
of knowledge of specific genes (or proteins) with respect to their effect on
specific processes. The computational questions is to determine those genes
which are optimal targets for diagnosis or therapy, namely those genes which
participate in a large number of
pathways and processes (simpler problem) and for therapy, those genes which when
affected, block a certain pathway completely, with minimal effect on other
pathways. This is an NP hard problem which requires development of novel
methods. The work will be in conjunction
with leading researches in molecular biologists and biochemistry to address
some of the most current biological research questions.
Requirements:
This project is intended for MSc Students in the
Bioinformatics program which have also good knowledge
in several database mining languages such as Python, knowledge in graph
theoretic methods and the specific use of the Graph Boost Library.
Gene
Dynamic Network Inference using Bayesian Methods
Related
work: Hartemic This project is intended for a MSc student. It intends to
continue work done by Omer Berkman on inference from a collection of “weak”
Bayesian networks. The inference is obtained on a regularitory
network from a (long) time series of Genes (or other markers) activations. In
particular, the causal regulation is sought, namely those markers which
initiate the regulation of other markers.
A similar causal effects are sought in brain imaging
inference, as we are using high resolution imaging (with EEG and MEG). See
above.
Seismic Data Analysis
Related
work: see presentation by Ido Yariv and Talmor at my Advanced
Seminar.
A
recent project was started on the infrasound properties of the mole rat and the
way it acquires information about the underground environment from infrasound.
Mathematical
Properties of the Cross-correlation Function
This
is a topic requires some knowledge in large deviation bounds, such as the Barankin bound, and the Ziv Lemple bound. Some overview of the topic appears in Judah’s thesis. The goal is to
analyze the properties of the cross correlation function from multiple sonar
returns with the purpose of devising an optimal fusion of the information that
can be extracted from each of the cross-correlations. A simple paper on this
topic is Robust
statistics from multiple pings improves noise tolerance in sonar.
Ultrasound
Image Enhancement using Multiple Pings
This
work relies on the work that we did with enhancement of Sonar images using
multiple pings and attempts to apply the same concept for medical ultrasound.
It relies on the multiple pings idea (Robust
statistics from multiple pings improves noise tolerance in sonar) and robust
motion estimation of the ultrasound sensor (Multiple ping sonar accuracy
improvement using robust motion estimation and ping fusion). The goal is to
achieve a far more accurate ultrasound with less energy for lower damage to the
fetus.
Neuronal
Optimal Coding
Related
work: Neuronal
Goals: Efficient Coding and Coincidence Detection.
A fundamental question in neural computation and computer vision is
concerned with the nature of object representations and the nature of
representations of relationship between objects. In particular, we depend on
the ability to adjust our expectations according to the past context. This
suggests that neurons should in addition to detecting features in their input representation, transmit some
information about the a-priori probability of occurrence of these features.
High
Dimensional Data Representation via Sound
Related
work: J. Berger and R. Coifman.
This
project is done in collaboration with Miri Segal (PhD
in Math and Visual & Audio Artist) and Assaf Talmudi
(PhD in Acoustics, and Musician) from the center for Digital Art in
The idea
is to provide acoustic information as an additional aid to visual information
and thus extending the number of free dimensions which can be ‘observed’
concurrently. This is important when a lot of information has to be analyzed
together, for example a radiologist that has to decide about a malignant tumor,
can get additional about a wider spectrum of the target via sound.
Computer Systems and Networks of
biomedical sensors
TinyOS and Wireless Body Sensors Network
TinyOS is an open-source
operating system designed for wireless embedded sensor networks. It
features a component-based architecture which enables rapid development.
This OS has become a standard in the recent development of a Wireless Body
Sensors Network and tmote
sky platform. We shall develop algorithms for real time analysis of ECG
using Pluto
that is based on tmote sky. This platform can
handle up to six different body sensors at a wireless range of 125m.
We
shall also develop software and algorithms to embed acoustic sensors into this
platform.
A
good place to start is a recent PhD
Thesis about Tele-Cardiology Sensor Network. Currently such networks are
heavily researched at
There
are also open projects to BioMedical
Engineering students in development of some sensors to this platform.
Blue Tooth Communication
Based on
the new CSR – BlueVoxFlash device,
http://www.csr.com/bluevoxflash/development.htm it is desired to develop a
system that can receive sensory input of one to three channels and send to the computer
for storage and analysis. Issues related to automatic gain, codec (compression)
have to be addressed.