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Archive for the ‘Distinguished lecturers’ Category

Sherif Sakr, Big Data Science as a Service, Tallinn, 24.10.2017 10.00

Wednesday, October 18th, 2017

Teisipäeval 24.10.2017 kell 10.00 esineb Tallinna Tehnikaülikooli ruumis ICT-507 professor Sherif Sakr loenguga “Big Data Science as a Service”.

Tuesday October 24th 2017 at 10.00 in TUT room ICT-507, Prof Sherif Sakr will give a presentation on Big Data Science as a Service.

Address: Akadeemia tee 15a, 12618, Tallinn (5th floor, rear stairs).

Everybody is welcome to participate! See below for more info on the speaker and talk.

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IEEE Computer Society Distinguished Lecturer Bernadetta Kwintiana Ane in TUT

Thursday, June 2nd, 2016

IEEE Computer Society Distinguished Lecturer Bernadetta Kwintiana Ane will give a lecture on Moday 6th of June 2016 at 11:00 in IT Maja Akadeemia tee 15A, room # ICT-507 A/B

Embedded Systems as Foundations of Cyber-Physical Systems

Abstract: Robots, intelligent buildings, implantable medical devices, cars that drive themselves or planes that automatically fly in a controlled airspace are examples of Cyber-Physical Systems (CPS). Today, CPS can be found in such diverse industries as aerospace, automotive, energy, healthcare, manufacturing, infrastructure, consumer electronics, and communications. Everyday life is becoming increasingly dependent on these systems, in some cases with dramatic improvements. CPS can be described as smart systems that encompass computational (i.e., hardware and software) and physical components, seamlessly integrated and closely interacting to sense the changing state of the real world. These systems involve a high degree of complexity at numerous spatial and temporal scales and highly networked communications integrating computational and physical components. In fact, CPS is about the intersection, not the union, of the physical and the cyber. In CPS, embedded computers and networks monitor and control the physical processes, usually with feedback loops where physical processes affect computations and vice versa. The design of such systems requires understanding the joint dynamics of computers, software, networks, and physical processes. Therefore, it is not sufficient to separately understand the physical components and the computational components. We must instead understand their interaction.

Bernadetta Kwintiana Ane is a Senior Researcher at the Institute of Computer-aided Product Development Systems, University of Stuttgart in Germany. She has 12 years teaching experiences mainly in Engineering Graphics and Design, particularly for application in the fields of Mechanical Engineering and Computer Science. Her research interest includes computer bernadettakwintianaaided geometric design (CAGD), reverse engineering, computer-aided design/manufacturing/ engineering (CAD/CAM/CAE), product design, design visualization, design automation, computer supported collaborative design, virtual reality based product design, cyber-physical design systems, and not limited to scientific data rendering and visualization for application in bioinformatics and in-silico modelling.

She has won various international research grants and has published more than 65 scientific writings in the form of books, chapters in books, journal papers, and conference papers. She is a fellow of Monbukagakusho, Japan as well as the Alexander von Humboldt Foundation and German Academic Exchange Service (DAAD), Germany. Since 2007, she played active roles as lead researcher in the international research projects in Germany as well as member in other European countries’ projects. Currently, as a Humboldtian and IEEE professional member she serves internationally as research fellow for several European research centers. She also serves as an associate editor for the Journal of Intelligent Automation and Soft-Computing (Taylor & Francis) and Journal of Applied Soft Computing (Elsevier Science), as well as grant assessor for The Czech Academy of Science, The Czech Science Foundation, and an independent expert to assist the European Commission with tasks in connection with the Framework Programme (Horizon2020) for Research and Innovation.

 

Additional information:
Urmet Jänes <urmet AT uninet.ee>

IEEE Distinguished Lecturer Prof. Hamid Krim in Tallinn and Tartu

Wednesday, May 25th, 2016

The IEEE Distinguished Lecturer of Signal Processing Society Prof. Hamid Krim is going to deliver a speech on Friday, June 10 in two places:

  • 10:00 in Tallinn University of Technology, auditorium NRG-131 (Faculty of Power Engineering building at Ehitajate tee 5), and
  • 15:30 – 17:30 in University of Tartu, auditorium (room 111) of the Computer Science Department, located at Juhan Liivi 2, 50409 Tartu.
    The event in Tartu is organized by the University of Tartu IEEE Student Branch, and sponsored by the iCV Research Group. The speech will be followed by free discussion and refreshments. Two attendants will win prizes each being worth a one-year IEEE student membership. For more information, you may contact us at ieee AT ut.ee, or visit our website http://ieee.ut.ee/ or our Facebook page https://www.facebook.com/IEEETartu/.”

Title: Convexity, Sparsity, Nullity and all that….

Abstract: High dimensional data exhibit distinct properties compared to its low dimensional counterpart; this causes a common performance decrease and a formidable computational cost increase of traditional approaches. Novel methodologies are therefore needed to characterize data in high dimensional spaces. Considering the parsimonious degrees of freedom of high dimensional data compared to its dimensionality, we study the union-of-subspaces (UoS) model, as a generalization of the linear subspace model. The UoS model preserves the simplicity of the linear subspace model, and enjoys the additional ability to address nonlinear data. We show a sufficient condition to use l1 minimization to reveal the underlying UoS structure, and further propose a bi-sparsity model (RoSure) as an effective algorithm, to recover the given data characterized by the UoS model from errors/corruptions. As an interesting twist on the related problem of Dictionary Learning Problem, we discuss the sparse null space problem (SNS). Based on linear equality constraint, it first appeared in 1986 and has since inspired results, such as sparse basis pursuit, we investigate its relation to the analysis dictionary learning problem, and show that the SNS problem plays a central role, and may naturally be exploited to solve dictionary learning problems. Substantiating examples are provided, and the application and performance of these approaches are demonstrated on a wide range of problems, such as face clustering and video segmentation.

HamidKrimBiography: Hamid Krim received his BSc. MSc. and Ph.D. in Electrical Engineering. He was a Member of Technical Staff at AT&T Bell Labs, where he has conducted R&D in the areas of telephony and digital communication systems/subsystems. Following an NSF postdoctoral fellowship at Foreign Centers of Excellence, LSS/University of Orsay, Paris, France, he joined the Laboratory for Information and Decision Systems, MIT, Cambridge, MA as a Research Scientist and where he was performing and supervising research. He is presently Professor of Electrical Engineering in the ECE Department, North Carolina State University, Raleigh, leading the Vision, Information and Statistical Signal Theories and Applications group. His research interests are in statistical signal and image analysis and mathematical modeling with a keen emphasis on applied problems in classification and recognition using geometric and topological tools. He has served and is currently serving on the IEEE editorial board of SP, and the TCs of SPTM and Big Data Initiative, as well as an AE of the new IEEE Transactions on SP on Information Processing on Networks, and of the IEEE SP Magazine. He is also one of the 2015-2016 Distinguished Lecturers of the IEEE SP Society.

 

Additional information:
Morteza Daneshmand, e-mail: mortezad AT ut.ee

Distinguished Lecturer event by Prof. Simon Deleonibus “More Moore and More than Moore meeting for 3D”

Tuesday, December 15th, 2015

IEEE Electron Devices Society: Distinguished Lecturer event :

More Moore and More than Moore meeting for 3DSimon d pic

by Prof. Simon Deleonibus
Chief Scientist/Directeur Scientifique, CEA, LETI, MINATEC Campus, Grenoble, France
Visiting Professor at Tokyo Institute of Technology, Tokyo, Japan
Visiting Professor at National Chiao Tung University, Hsinchu, Taiwan

December the 18-th, 2015, 12:00-13:50,
room U03-302 in Tallinn University of Technology (TUT), Ehitajate str 5

in co-operation with IEEE Estonian Section and TUT (Thomas Johann Seebeck Department of Electronics, ICT doctoral school)
Information about event and optional registration (latest 18.12, 9:30) is here.

IEEE distinguished lecturer Prof. Maria Sabrina Greco “Advanced Techniques of Radar Detection in Non-Gaussian Background”

Thursday, September 3rd, 2015

On Wednesday, 16th September 2015 at 14:00, Tallinn University of Technology, room NRG-226
IEEE distinguished lecturer Prof. Maria Sabrina Greco from University of Pisa

Marina_Sabrina

Abstract

After a brief introduction dedicated to modern statistical and spectral modeling and analysis of high-resolution sea and ground clutter, the lecture will focus on coherent radar detection in non-Gaussian background. Optimum and sub-optimum detectors are derived and their performance analysed against a non-Gaussian background. Different interpretations of the various detectors are provided that highlight the relationships and the differences among them. Moreover, some discussion is dedicated to how to make adaptive the detectors, by incorporating a proper estimate of the disturbance covariance matrix, in order to guarantee the CFAR behaviour of the detector. Results with simulated and real recorded data will be shown.

Prof. Visa Koivunen lecture: “Robust Estimators for Complex-Valued Multichannel Data”

Wednesday, March 25th, 2015

On Wednesday, 8th April 2015 14:00 at Tallinn University of Technology, room U02-102
IEEE Distinguished lecturer Prof. Visa Koivunen

Robust Estimators for Complex-Valued Multichannel Data

Prof. Visa Koivunen is the Full Professor of Signal Processing in Aalto University, Finland, since 1999. He holds the Academy Professor position. He was a Principal Investigator in SMARAD Center of Excellence in Research in 2002-2013. He was also Adjunct Full Professor, University of Pennsylvania, USA (2003-2006); Visiting Fellow, Princeton University, NJ, USA (2007, 2013-2014); and part-time Visiting Fellow, Nokia Research Center (2006-2012). His research interest include statistical, communications, sensor array and multichannel signal processing. He has published about 350 papers in international scientific conferences and journals. He co-authored the papers receiving the best paper award in IEEE PIMRC 2005, EUSIPCO’2006, EUCAP 2006 and COCORA 2012. He has been awarded the IEEE Signal Processing Society best paper award for the year 2007. He is the recipient of 2015 EURASIP Technical Achievement Award.

Lecture of Dr. R. V. Joshi “Climbing the VLSI Power Wall for nm Era”

Sunday, October 5th, 2014

In Thursday, Oct. 9 at 12:00 in U03-103 (Tallinn University of Technology) will a lecture from BEC2014 invited speaker R. V. Joshi: “Climbing the VLSI Power Wall for nm Era“.

Dr. R.V. Joshi (Bio) is also Distinguished Lecturer for IEEE CAS and EDS society.

Abstract:
Low Power, and energy efficiency are key themes which is pushing system, software and hardware design. In order to achieve low power system, circuit and technology co-design is essential. This talk focuses on related technology and important circuit techniques for nanoscale era.
Achieving low power and high performance simultaneously is always difficult. Technology has seen major shifts from bulk to SOI and then to non-planar devices such as FinFET/Trigates.
As the technology pushes towards sub-65nm era, process variability and geometric variation in devices can cause variation in power. The reliability also plays an important role in the power-performance envelope. This talk also reviews the methodology to capture such effects and describes all the power components. All the key areas of low power optimization such as reduction in active power, leakage power, and short circuit power are covered. Usage of clock gating, power gating, longer channel, multi-Vt design, stacking, header-footer device techniques, resonant clocking and other methods are described for logic and memory.

Finally the talk summarizes key challenges in achieving low power.

Distinguished lecturer V. John Mathews on May 2-nd 2014 in TUT

Monday, April 7th, 2014

On Friday May 2-nd 2014 14:00 in Tallinn University of Technology, room #: II-102

Equalization and Adaptation of Nonlinear Systems

V John Mathews
Department of Electrical & Computer Engineering
University of Utah
Salt Lake City, UT 84112

Abstract

This talk provides a tutorial introduction to nonlinear signal processing with emphasis on equalization of nonlinear distortions in practical problems and adaptation of nonlinear system models. In the first part of the talk, we will discuss efficient approaches to inversion and equalization of a broad class of nonlinear systems. We will start by looking at exact inverses of nonlinear systems, but stable implementations of such systems may not exist. We will then describe approximate equalizer architectures that are systolic and operate in a stable manner. Examples of applying the equalizers in audio applications will also be shown. The second part of the talk will overview adaptive algorithms for identifying linear-in-the parameters nonlinear systems. Among the approaches discussed will be a method whose computational complexity involves a single multiplication and two additions per input sample, regardless of the complexity of the model.

Prof. V.John Mathews biography