SEMINAR  

November 6, 2007 Room 1000 SEO, 2:00 pm

Nano-Engineered Materials and Applications in Life Sciences

By Dr. Shubhra Gangopadhyay,

LaPierre Chair  and Joint Professor
Department of Electrical and Computer Engineering,
Biological Engineering,and Physics
University of Missouri-Columbia

Abstract,

We are currently developing a micro system based on nano-engineered thermite materials capable of generating a large and controlled amount of energy via super-sonic pressure pulse, known as a shock wave. This shock wave can deliver different materials into single cells or tissue with extremely high precision without damaging cells/tissues. We are also preparing biocompatible nanoparticles that will permit the clustering of high doses of medical compounds, fluorescent dyes, plasmids, etc into a small compartment. Together these elements will comprise a high efficiency delivery system capable of transfecting cells or tissue with extremely high accuracy and with minimal side effects. The tunable, hand-held system will bring fundamental changes to the study and understanding of biological processes in health and disease, as well as enable novel diagnostics and interventions for treating disease. Thus, the technological advances from this study could result in a new era in the treatment and/or diagnosis of cancer, Parkinson’s disease, Alzheimer’s, spinal cord injury, thrombosis, cardiovascular diseases and host of other conditions.                              

Biography,

The Gangopadhyay Research Group is an electrical engineering and materials science research facility at the University of Missouri Columbia's College of Engineering and is associated with the International Center for Nano/Micro Systems and Nanotechnology. It is dedicated to expanding the realm of science and technology through optimization of existing techniques and exploration of new dimensions of knowledge. The group's research includes discovering, integrating, and optimizing new materials, processing methods, and characterization techniques. By promoting an interdisciplinary approach, our unique and modern research facility was designed to train, educate and prepare students to join and lead the workforce in innovative solutions to scientific challenges.

The group is headed by Dr. Shubhra Gangopadhyay, LaPierre Chair and Joint Professor, Departments of Electrical Engineering, Biological Engineering and Physics, who is an acclaimed researcher in the fields of material science and physics. The group has set up a high class research facility - the first of its kindin Missouri - with plans to upgrade and expand the facilities over the next two years.

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SEMINAR  

November 5 2007 Room 1000 SEO, 10:00 am

Dielectric Films with Metal Nanoparticles for Higk-k and Non-Volatile Memory Applications

By Dr. Shubhra Gangopadhyay,

LaPierre Chair  and Joint Professor
Department of Electrical and Computer Engineering,
Biological Engineering,and Physics
University of Missouri-Columbia

Abstract,

High-κ dielectrics have become a focal point of the complimentary metal oxide semiconductor (CMOS) front end. Controlling threshold voltages in upcoming nodes will require dielectrics which have both suitable properties on contact with silicon and a high permittivity. Our research has focused on using silver, platinum and gold nanoparticles to enhance the dielectric constant of amorphous HfO 2 and Al 2O 3. Metal nanocrystals of diameter down to 1nm are incorporated in high-K dielectrics for achieving non-volatile memories. Nanocrystal based non-volatile memories are discrete charge storage devices and are strong candidates for replacement of conventional FLASH memories.

Biography,

The Gangopadhyay Research Group is an electrical engineering and materials science research facility at the University of Missouri Columbia's College of Engineering and is associated with the International Center for Nano/Micro Systems and Nanotechnology. It is dedicated to expanding the realm of science and technology through optimization of existing techniques and exploration of new dimensions of knowledge. The group's research includes discovering, integrating, and optimizing new materials, processing methods, and characterization techniques. By promoting an interdisciplinary approach, our unique and modern research facility was designed to train, educate and prepare students to join and lead the workforce in innovative solutions to scientific challenges.

The group is headed by Dr. Shubhra Gangopadhyay, LaPierre Chair and Joint Professor, Departments of Electrical Engineering, Biological Engineering and Physics, who is an acclaimed researcher in the fields of material science and physics. The group has set up a high class research facility - the first of its kindin Missouri - with plans to upgrade and expand the facilities over the next two years.

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SEMINAR  

October 12 2007 Room 1000 SEO, 1:00 pm

Beyond Epitaxical Self-Assembled and Nanocrystal Quantum Dots: Novel Composite Nanosystems for Applications to Human Environment and Health Issues

Abstract,

Over the past two decades, advances in the synthesis and processing of vapor phase directed assembly of epitaxical semiconductor quantum nanostructures (quantum wells, dots, and wires) have led to the development of remarkable electronic and optoelectronic systems for information sensing, processing, communication, and saving energy. In parallel, advances in the solution chemistry based nanocrystals (quantum dots, rods, tetrapods, branched dendrimers) have spawned innovative applications to imaging in biology and medicine, and applications to optoelectronics and environment are being explored. Integration of these two classes of nanostructures into hybrid structures can, we suggested some time ago, potentially create novel systems having unprecedented functionalities that draw upon combining the strengths of each. In this talk I shall present some approaches to the synthesis of such hybrid structures, initial results on some conceptual issues, and the attendant materials challenges which, when overcome, could introduce a new technological paradigm for addressing societal needs in vast areas of applications ranging from solar energy conversion to detection of weak biochemical signals (such as in early detection of biohazards and disease) to probing and manipulating cell function relating to disease.

                             

Biography,

Dr. Madhukar received his BSc (1966) and MSc (Physics, 1968) degrees respectively, from the University of Lucknow and the Indian Institute of Technology (Kanpur) in India. He received his Ph.D. in Materials Science and Physics in 1971 from the California Institute of Technology. Before coming to USC in 1976, Dr. Madhukar was a Post Doctoral Research Fellow at the Thomas J. Watson Research Center of the IBM Corporation and a Research Associate at the James Frank Institute of the University of Chicago. Dr. Madhukar was an Alfred P. Sloan Fellow (1977-81), received three NASA Certificates of Recognition (1981, 1982, 1986) for his research in Si/SiO2 interfaces and compound semiconductor MBE, Outstanding Research Award of the USC School of Engineering in 1988, and the DARPA (ETO) award for Sustained Excellence, 1997 (given to a multidisciplinary team led by Dr. Madhukar). He is the founding President of the Southern California chapter of the Materials Research Society, a member of the New York Academy of Sciences, and Fellow of the American Physical Society.

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SEMINAR  

IEEE Signal Processing Society
Department of Electrical and Computer Engineering
University of Illinois at Chicago

October 11 2007 SEO Room 1000, 1:00 pm

Iterative Image Reconstruction without the Iterations



By Prof. Charles A. Bouman
Purdue University

Abstract,

Many important medical imaging modalities such as positron emission tomography (PET), single photon emission computed tomography (SPECT), x-ray computed tomography (CT), magnetic resonance imaging (MRI), and optical tomography (OT), require the reconstruction of images from indirect and noisy measurements. Since the inception of these systems, there has been great interest in solving the associated reconstruction problems accurately and efficiently. In recent years, iterative reconstruction using regularized inversion has attracted great attention because it can produce substantially higher image quality by accounting for both the statistical nature of measurements and the characteristics of reconstructed images. For example, maximum a posteriori (MAP) reconstruction works by iteratively minimizing a cost function corresponding to the probability of the reconstruction given the measured data. Typically, the MAP reconstruction is computed using an iterative optimization method such a conjugate gradient.
 
Interestingly, when the prior model and system noise are Gaussian, the MAP reconstruction is simply a linear transformation of the measurements. However, even in this case, the MAP reconstruction is never computed using a simple matrix-vector product because the required matrix is enormous (number of voxels by the number of measurements) and is also generally dense. Consequently, both storing the required matrix, and computing the matrix-vector product is not practical.
In this talk, we introduce a novel approach to MAP reconstruction in which we directly compute the required matrix-vector product. In order to deal with such a large matrix, we introduce two new ideas. The first idea is a source-coding theory for matrix transformations. This theory is based on a distortion metric that reflects the distortions produced in the final matrix-vector product, rather than the distortions in the coded matrix itself. The resulting algorithms are shown to require orthonormal transformations of the measurement data and matrix rows before quantization and coding. The second idea is a method for storing and computing the required orthonormal transformations, which we call a sparse-matrix transform (SMT). The SMT is a generalization of the classical FFT in that it uses butterflies to compute an NxN transform; but unlike an FFT, the SMT uses the butterflies in an irregular pattern, and is numerically designed to best approximate the desired orthonormal transform.
 
We demonstrate the potential of our non-iterative MAP reconstruction scheme by showing examples of its use for OT, and MRI reconstruction. For the OT example, which is normally considered to be a very computationally intensive, the non-iterative MAP algorithm reduces both storage and computation by well over 2 orders of magnitude, as compared to traditional iterative reconstruction methods.
                             

Biography,

Charles A. Bouman received a B.S.E.E. degree from the University of Pennsylvania in 1981 and a MS degree from the University of California at Berkeley in 1982. From 1982 to 1985, he
was a full staff member at MIT Lincoln Laboratory and in 1989 he received a Ph.D. in electrical engineering from Princeton University. In 1989, he joined the faculty of Purdue University where he holds the rank of Professor with a primary appointment in the School of Electrical and Computer Engineering and a secondary appointment in the School of Biomedical Engineering. Professor Bouman's research focuses on the use of statistical image models, multiscale techniques, and fast algorithms in applications including medical and electronic imaging. Professor Bouman is a Fellow of the IEEE, a Fellow of the American Institute for Medical and Biological Engineering (AIMBE), a Fellow of the society for Imaging Science and Technology (IS&T), a member of the SPIE professional society, a recipient of IS&T’s Raymond C. Bowman Award for outstanding contributions to digital imaging education and research, and a University Faculty Scholar of Purdue University. He is currently the Editor-in-Chief for the IEEE Transactions on Image Processing, secretary of the IEEE Biomedical Image and Signal Processing Technical Committee, and a member of the Steering Committee for the IEEE Transactions on Medical Imaging. He has been an associate editor for the IEEE Transactions on Image Processing and the IEEE Transactions on Pattern Analysis and Machine Intelligence. He has also been Co-Chair of the 2006 SPIE/IS&T Symposium on Electronic Imaging, Co-Chair of the SPIE/IS&T conferences on Visual Communications and Image Processing 2000 (VCIP), a Vice President of Publications and a member of the Board of Directors for the IS&T Society, and he is the founder and co-chair of the SPIE/IS&T conference on Computational Imaging.
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SEMINAR  

IEEE Signal Processing Society
Department of Electrical and Computer Engineering
University of Illinois at Chicago

Thursday, September 27, 2007
1:00 p.m., 1325 SEO

Genomic Network Tomography




By Prof. Robert Nowak
University of Wisconsin – Madison

Abstract,

Living organisms use protein signaling networks to communicate information about the extracellular environment from the cell wall to the nucleus, leading to changes in gene expression that enable the organism to adapt and survive in diverse environments.  Unfortunately, no high-throughput measurement technology exists for directly elucidating the structure of signaling networks.  In this talk I will discuss recent work on inferring the structure of signaling networks from co-occurrence data: observations that indicate which proteins (nodes) are involved in a signaling pathway without revealing their order within the pathway (edges).  We call this proble m since it bears a strong resemblance, both physically and mathematically, to tomographic imaging and related network tomography problems.  Without any order information, every permutation of the proteins in a pathway potentially leads to a different feasible network, resulting in combinatorial explosion of the feasible set.  However, the physical principles underlying cellular signaling networks suggest that not all feasible solutions are equally likely. Proteins that co-occur in many pathways are probably more closely connected.  Building on this intuition, we model co- occurrence data as randomly shuffled samples of a random walk on the network.  Based on this model, we derive a polynomial-time Monte Carlo EM algorithm for network inference, and, using novel concentration inequalities for importance sampling estimators, we prove that the algorithm converges to a maximum likelihood solution with very high probability.

Biography,

Robert Nowak received the B.S. (with highest distinction), M.S., and Ph.D. degrees in electrical engineering from the University of Wisconsin-Madison in 1990, 1992, and 1995, respectively.  He was a Postdoctoral Fellow at Rice University in 1995-1996, an Assistant Professor at Michigan State University from 1996-1999, held Assistant and Associate Professor positions at Rice University from 1999-2003, and was a Visiting Professor at INRIA in 2001. Dr. Nowak is now the McFarland-Bascom Professor of Engineering at the University of Wisconsin-Madison.  He has served as an Associate Editor for the IEEE Transactions on Image Processing, and is currently an Associate Editor for the ACM Transactions on Sensor Networks and the Secretary of the SIAM Activity Group on Imaging Science. He has also served as a Technical Program Chair for the IEEE Statistical Signal Processing Workshop and the IEEE/ACM International Symposium on Information Processing in Sensor Networks. Dr. Nowak received the General Electric Genius of Invention Award in 1993, the National Science Foundation CAREER Award in 1997, the Army Research Office Young Investigator Program Award in 1999, the Office of Naval Research Young Investigator Program Award in 2000, and IEEE Signal Processing Society Young Author Best Paper Award in 2000.  His research interests include statistical signal processing, machine learning, imaging and network science, and applications in communications, bio/medical imaging, and genomics.

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SEMINAR  

10:30AM to 12PM, Thursday September 13, 2007

Engineering Research Facilities (ERF), Room 1043

One Dimensional Nanostructures and their Applications

By Meyya Meyyappan ,

NASA Ames Research Center
Moffett Field, CA 94035
m.meyyappan@nasa.gov

Abstract,

The ability to grow carbon nanotubes and a variety of semiconductor, oxide
and other inorganic materials in the form of nanowires with controlled
properties and vertical orientation(if desired) provides an avenue for
applications in logic, memory, data storage, sensors, photovoltaics,
displays,  and others. Growth of these  materials, characterization and
application development will be discussed in detail.

                              Biography

Meyya Meyyappan is Chief Scientist for Exploration at the Center for
Nanotechnology, NASA Ames Research Center in Moffett Field, CA.  Until
June 2006, he served as the Director of the Center for Nanotechnology as
well as Senior Scientist. He holds an Adjunct Professor position at the
Arizona State University.  He is a founding member of the Interagency
Working Group on Nanotechnology(IWGN) established by the Office of
Science and Technology Policy(OSTP).  The IWGN is responsible for
putting together the National Nanotechnology Initiative.

Dr. Meyyappan is a Fellow of the Institute of Electrical and Electronics
Engineers(IEEE), the Electrochemical Society(ECS), American Vacuum
Society(AVS)and the California Council of Science and Technology.  In
addition, he is a member of the American Society of Mechanical
Engineers(ASME), Materials Research Society, and American Institute of
Chemical Engineers.  He is the IEEE Distinguished Lecturer on
Nanotechnology and ASME's Distinguished Lecturer on
Nanotechnology(2004-2006).  He is currently the President of the IEEE's
Nanotechnology Council(2006-2007).

For his work and leadership in nanotechnology, he has received numerous
awards: NASA's Outstanding Leadership Medal;  Arthur Flemming Award by the
Arthur Flemming Foundation and George Washington University; President's
Meritorious Award; IEEE Judith Resnick Award; and Engineer of the Year
award by the San Francisco section of the
AIAA(American Institute of Aeronautics and Astronautics) for his
contributions to nanotechnology education and training.  Dr. Meyyappan has
authored or co-authored over 150 articles in peer reviewed publications
and made over 200 Invited/Keynote/Plenary Talks in nanotechnology subjects
across the world.

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SEMINAR  

2 pm, Thursday September 20, 2007

Science and Engineering Office Building(SEO), Room 1000

DNA: Not Merely the Secret of Life

Prof. Nadrian C. Seeman , Margaret and Herman Sokol Chair in Chemistry, Department of Chemistry, New York University, New York, NY 10003, USA, ned.seeman@nyu.edu, 212-998-8395 (t), 212-260-7905 (f).

Structural DNA nanotechnology uses reciprocal exchange between DNA double helices to produce branched DNA motifs. We combine branched motifs to produce specific structures, using sticky-ended cohesion. We have used this approach to make DNA stick-polyhedra, a variety of 2D DNA crystalline arrays, and some 3D arrays. We have used the 2D arrays to organize metallic nanoparticles and other functional species, such as DNAzymes. We have built a variety of DNA nanotubes, which can assemble directly, or from paired halves.

We have also built a number of sequence-dependent nanomechanical devices, such as a bipedal walker and a machine that translates DNA sequences into assembly instructions. The walker traverses a sidewalk in either direction as a consequence of the addition and removal of specific strands. The translation machine is based on a device that rotates one end relative to another by a half-turn; this device is also driven in a sequence-specific fashion by the addition and removal of specific strands. We have incorporated this device into a cassette that includes a domain to insert it into a 2D periodic array, along with a robotic arm that is reoriented by the motion of the device. By using atomic force microscopy, we are able to demonstrate that the device is active when it is inserted into the array, thereby laying the basis for a DNA-based nanorobotics.

This research has been supported by grants from the NIGMS, NSF, ARO, DOE and the W.M. Keck Foundatiion.

Host: Michael Stroscio, (312) 413-5968, Stroscio@uic.edu

A selected paper recommended by Mike Stroscio: N.C. Seeman. Nanotechnology and the Double Helix, Scientific American., 290, (6) 64-75 (2004).

Honors and Awards:

NATO Advanced Study Fellow, 1970
Damon Runyon Fellow, 1972-1973
NIH Postdoctoral Fellow, 1973-1976
Sidhu Award, 1974
Basil O'Connor Fellow, 1978-1981
NIH Research Career Development Award, 1982-1987
Science and Technology Award from Popular Science Magazine, 1993
Feynman Prize in Nanotechnology, 1995
Emerging Technology Award from Discover Magazine, 1997
Honorary Professor, Universidad Peruana Cayetano Heredia, 1998
Elected Fellow of the American Association for the Advancement of Science, 1998
Margaret and Herman Sokol Faculty Award in the Sciences, 1999
Margaret and Herman Sokol Chair in Chemistry, 2001-
Tulip Award in DNA-Based Computation, 2004.
Elected Fellow of the Royal Society of Chemistry, 2005.
MERIT award from the National Institute of General Medical Sciences, 2005.
Nano50 Award from Nanotech Briefs, 2005.
Biotechnology Award from World Technology Network, 2005.

Founding President, International Society for Nanoscale Science, Computation and Engineering

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