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Oklahoma State University

ECE Seminars

 

Present and Future Challenges of Data Storage Channels

Date: 
Wednesday, November 16, 2016 - 12:30pm to 1:30pm
Location: 
ATRC 102

Food provided at 12 P.M. - 12:30 P.M.
Food reservation can be made at the ES202 front desk one week prior to each seminar.


Dr. J.R. CruzDr. J.R. Cruz - Director and Tilley Chair Professor, School of Electrical and Computer Engineering, University of Oklahoma

J. R. Cruz (S’75-M’79-SM’85-F’01) received his undergraduate degree in electrical engineering from the University of Porto, Portugal, and the M.S. and Ph.D. degrees from the University of Houston, TX, USA, while holding a Fulbright Fellowship. He was with Computer Sciences Corporation at the NASA Johnson Space Center, and Motorola Research, prior to joining The University of Oklahoma, where he is currently a Professor, Director of the School of Electrical and Computer Engineering, and the holder of the Tilley Chair in Electrical Engineering. His research interests are in communications signal processing, particularly equalization, detection and coding techniques, with applications to digital data storage and transmission. He is a member of the Board of Governors and a Past President of the IEEE Vehicular Technology Society, and a recipient of its Outstanding Service and Stuart Meyer Memorial Awards. He is a former Editor-in-Chief of the IEEE Transactions on Vehicular Technology and currently serves as an Editor for the IEEE Transactions on Magnetics. He is a Fellow of the Radio Club of America, the recipient of the Armstrong Medal in 2014 and the IEEE Third-Millennium Medal in 2000. He was a Distinguished Lecturer for the IEEE Communications Society and the co-recipient of the Best Paper Prize in Signal Processing and Coding for Data Storage at the 2007 IEEE International Conference on Communications.

Seminar Abstract

Data storage plays a large role in our lives and drives an industry with annual sales approaching $30B. To be useful, data storage devices must be able to reliably read back the same data that was originally written. However, the underlying communication channels in these systems are inherently unreliable, often very unreliable, and behave in complex ways unlike simpler communications channels often found in transmission systems. Understanding the behavior of these complex channels is necessary in order to design reliable data storage systems that can overcome these challenges. In this lecture, we first discuss the magnetic recording channel for high-density hard-disk drives and our development of a state-the-art channel model. We also discuss NAND-flash solid-state drive channels as well as future non-volatile memories such as spin-torque transfer random access memory (STT-RAM), and explore how all these channels pose special problems for reliable storage system design.

Full color flyer (pdf)

Engineers Help Unravel the Mysteries of the Brain

Date: 
Tuesday, October 11, 2016 - 12:30pm to 1:30pm
Location: 
ATRC 102

Food provided at 12 P.M. - 12:30 P.M.
Food reservation can be made at the ES202 front desk one week prior to each seminar.


Dr. Scott T. ActonDr. Scott T. Acton - Professor of Electrical & Computer Engineering and of Biomedical Engineering, University of Virginia

Professor Acton’s laboratory at UVA is called VIVA - Virginia Image and Video Analysis. They specialize in biomedical image analysis problems. The research emphasis of VIVA is video tracking and segmentation. Professor Acton has over 275 publications in the image analysis area including the books Biomedical Image Analysis: Tracking and Biomedical Image Analysis: Segmentation. Professor Acton has been at the University of Virginia since 2000. Before that time, he was on the faculty at Oklahoma State University (1994-2000). He’s worked in industry for AT&T, Motorola and the Mitre Corporation. He is editor-in-chief of the IEEE Transactions on Image Processing.

Seminar Abstract

This talk highlights the intersection of engineering and neuroscience. The scientific community is attempting to map the structure and connectivity of neurons in organisms such as Drosophila – the fruit fly. To accomplish such an atlas, automated image analysis is required and stands as a major roadblock to success. The talk addresses recent progress in the segmentation and tracing of individual neurons.  Graph theoretic and diffusion-based methods are discussed along with results. Also, the comparison and matching of neurons is described. This last portion of the research addresses the open question: can we quantify morphological change in neurons?

Full color flyer (pdf)

Technology, Computer Architecture and Memory

Date: 
Thursday, September 29, 2016 - 12:30pm to 1:30pm
Location: 
ATRC 102

Food provided at 12 P.M. - 12:30 P.M.
Food reservation can be made at the ES202 front desk one week prior to each seminar.


Dr. Mark D HillDr. Mark D Hill - Gene M. Amdahl and John P. Morgridge Professor of Computer Sciences, University of Wisconsin- Madison

Professor Hill is a senior computer architect at Wisconsin interested in parallel-computer system design, memory system design, and computer simulation. He developed the 3C cache miss taxonomy (compulsory, capacity, and conflict) and co-developed “sequential consistency for data-race free” that serves as a foundation of the C++ and Java memory models. He is a fellow of IEEE and the ACM, co-inventor on 35 patents, and taught more than 1000 students with 40 Ph.D. progeny so far. Hill has a PhD in computer science from the University of California, Berkeley and currently serves as Vice Chair of the Computer Community Consortium.

Seminar Abstract

First, this talk will discuss how challenges to Moore’s Law will open up new directions for computer systems, including architecture as infrastructure, energy first, impact of emerging technologies, and cross-layer opportunities. Second, the talk will delve into examples of cross-layer research driven by changes in memory due to the million-fold memory capacity growth, the introduction of general-purpose graphics processing unit computing, and non-volatile memory’s fusing of memory and storage. While computing gets the glory, remember that it is vast memory that makes most interesting computation possible!

Full color flyer (pdf)

Next Generation Engineering Education

Date: 
Monday, April 4, 2016 - 12:30pm to 1:30pm
Location: 
102 ATRC

Food provided at 12 P.M. - 12:30 P.M.
Food reservation can be made at the ES202 front desk one week prior to each seminar.


Dr. Robert G. OlsenDr. Robert G. Olsen - Professor at the School of Electrical Engineering
and Computer Science at Washington State University

Olsen received his B.A. degree in electrical engineering from Rutgers University, New Brunswick, NJ in 1968 and the M.S. and Ph.D. degrees in electrical engineering from the University of Colorado, Boulder, CO in 1970 and 1974 respectively. For the latter two degrees, his area of specialization was electromagnetic theory. He was the associate dean for undergraduate programs of the Voiland College of Engineering and Architecture from 2003-20013.

His research interests span all aspects of electromagnetics issues in power transmission and has resulted in approximately 85 publications in refereed journals and approximately 150 conference publications/presentations. He is also one of the authors of the AC Transmission Line Reference Book – 200 kV and Above which is published by the Electric Power Research Institute (EPRI) and the author of the recently published two volume book, High Voltage Overhead Transmission Line Electromagnetics.

Seminar abstract

There are a number of important issues to be faced when contemplating undergraduate engineering education for the next generation. Retention is a major concern given the historically low retention rate in engineering programs due to the relative lack of control over the first two years of the students’ education. This issue will be addressed in addition to the more recent problem of generally reduced student readiness for the engineering curriculum. The discussion will include challenges faced in both recruiting and retaining underrepresented minorities and women.  Engineering programs are evolving and are expected to change to emphasize learning more than teaching and to include more “experience enhanced education.” Infused within all segments of the seminar will be the roles played by NSF funding and assessment to enhance programs. If undergraduate programs are to grow, the resources (human, facility and financial) must be made available either by increased efficiency or additions to existing resources. An issue of great importance, given their many responsibilities, is that faculty workload related to the undergraduate program must be set at a ‘reasonable” level.

Full color flyer (pdf)

Phase Sensitive X-ray Imaging for Cancer Diagnosis

Date: 
Tuesday, March 22, 2016 - 12:30pm to 1:30pm
Location: 
102 ATRC

Food provided at 12 P.M. - 12:30 P.M.
Food reservation can be made at the ES202 front desk one week prior to each seminar.


Dr. Hong LiuDr. Hong Liu - Charles and Jean Smith Chair in Biomedical
Engineering, George Lynn Cross Professor of Electrical and Computer
Engineering, Director of Advanced Medical Imaging Core Facility at
University of Oklahoma

Liu is a leading researcher in medical imaging. His current research projects include phase sensitive x-ray imaging for breast cancer diagnosis and optical and fluorescent imaging for clinical genetic diagnosis. He has published 270 scientific papers, book chapters and patents.

Dr. Liu received his college education in mechanical engineering and master training in applied physics, both in Beijing, China. He received a Ph.D. degree in biomedical engineering from Worcester Polytechnic Institute in Massachusetts. Liu was on faculty at the University of Virginia and Johns Hopkins University.  He joined the faculty of the University of Oklahoma in 2000.

Seminar abstract

Radiography is one of the important imaging techniques in medicine. Conventional radiography is principally based on x-ray tissue attenuations. However, x-ray contrast can also be obtained from phasechanges.  Several advanced methods are currently under investigation to image phase variations. Among them, the in-line phase sensitive x-ray imaging technique has demonstrated its clinical potential, as it can be implemented with polychromatic sources. The in-line phase-sensitive x-ray imaging measures the Laplacian of phase, leading to improved feature visualizations through edge enhancement. Furthermore, the technique allows the retrieval of tissue’s phase map, potentially enables quantitative tumor characterization. In this presentation, the basic principles of medical x-ray imaging will be introduced. The development of innovative phase-sensitive x-ray imaging prototypes; as well its clinical applications in breast cancer diagnosis will be discussed.

Full color flyer (pdf)

CEAT Research Seminar Series

Date: 
Friday, February 26, 2016 - 12:30pm to 1:30pm
Location: 
103 ATRC

Systems Analysis of the Interactions between Food, Energy, and Water systems - David Lampert, Ph.D., Asst. Prof. CIVE

Optimizations of Memory-based Elementary Functions within Computing - James E. Stine, Jr., Ph.D., Prof. ECE

See flyer for full details.

Mixed-signal MEMS for Sensing Instrument and Biomedical Applications

Date: 
Thursday, February 18, 2016 - 3:30pm to 4:30pm
Location: 
101 ATRC

Refreshments and discussion following

Presenter:  Dongning Zhao

Abstract:  In recent years, there has been an increasing demand for state-of-the-art MEMS technology development to address the basic and most important issues for humans: energy, environment, and health. By combining fundamental principles in mechanical engineering, semiconductor fabrication technology, low-noise low-power analog circuitry in MEMS development, a variety of new products have been created to increase the quality of people's lives and improve the efficiency of product manufacturing processes. This talk will discuss on mixed-signal, low-offset interface circuit for MEMS applications. Specially, I will discuss the research and development of a low-noise CMOS Interface for inertial measurement unit (IMU) - micro-g accelerometer featuring high sensitivity and large dynamic range. Also I will discuss the development of a portable multi-channel MEMS ultrasound sensor array for 3-dimensional high-resolution medical imaging applications. The talk will conclude with a brief discussion on future research such as MEMS applications for portable electronics and energy harvesting for IoT / bio-medical sensors.

Dongning Zhao received his BS and MS in Electrical Engineering from the University of Nebraska - Lincoln in 2001 and 2003, respectively. He received his PhD degree in Electrical and Computer Engineering from the Georgia Institute of Technology in 2009. His doctoral dissertation was focused on CMOS low-noise interface circuits design for MEMS accelerometer. From 2011 to 2014, he was with the Institute of Microelectronics (IME) Singapore, as a Scientist, where he worked on the research and development of low-power CMOS analog/power IC system for ultrasound bio-medical imaging applications. Presently he is working on battery power management in the electric charging pile system for green electric cars. His research interests and areas are CMOS analog/power/biomedical IC and system design for MEMS sensors and implantable/wearable medical devices.

Open to the Public

Energy-Efficient Interfaces for World-to-Cloud Computing

Date: 
Monday, February 15, 2016 - 3:00pm to 4:00pm
Location: 
102 ATRC

Refreshments and discussion following

Presenter:  Vanessa Chen

Abstract:  Our world is rapidly moving towards a wireless future where everything will stay connected largely through the internet, and we have come to rely on smart devices for sensing, communication, and computing.

This presentation will demonstrate how rethinking the fundamental nature of circuits and systems leads to dramatically more energy efficient and more robust solutions. To reduce power consumption for ubiquitous sensing, machine learning is applied to the system-driven design for bio-information acquisition. Only the critical information is acquired in the sensor array, and the system could identify the bio-information correctly with more than 10 times power reduction in the interface circuits. The other approach to achieve better energy efficiency is to enhance the design with algorithms. A time- interleaved analog-to-digital converter, which needs a large comparator array to work in parallel to resolve data at 20GS/s, will be discussed. A low-frequency clock is used to synchronize the high-throughput data, and the randomness of process mismatch is exploited to compensate for the clock misalignment. The algorithm breaks the tradeoff between speed and power, and allows the system to be calibrated in the background as a self-healing system. This work achieves the best reported power efficiency for the gigahertz analog-to-digital converters.

Vanessa Chen received her Ph.D. degree in Electrical and Computer Engineering from Carnegie Mellon University, Pittsburgh, in 2013. From 2010 to 2013, at Carnegie Mellon, she focused her research on self-healing systems and high-speed ADC designs, and held a research internship position at IBM T. J. Watson Research Center, Yorktown Heights, in 2012. Her work has appeared in top academic conferences and has been featured as highlights in the IEEE International Solid-State Circuit Conference (ISSCC). She was the recipient of the IBM Ph.D. Fellowship in 2012 and Analog Devices Outstanding Student Designer  Award  in  2013.  Prior  to  that,  she  received  her  B.S.  and  M.S.  degrees  in Electrical Engineering from National Tsing Hua University, Taiwan, in 2003 and 2005, respectively. In 2005, she joined Realtek Semiconductor working on analog front-end circuits of xDSL chipsets. She is currently with Qualcomm working on low-power data- acquisition systems for mobile devices. Her research interests focuses on energy-efficient analog-digital interface designs for ubiquitous sensing and communication systems.

Privacy-Preserving Data Analytics for Big Data Applications

Date: 
Wednesday, February 10, 2016 - 3:00pm to 4:00pm
Location: 
103 ATRC

Refreshments and discussion following.  Public is welcome.

Speaker:  Yanming Gong

Abstract:  Big data has driven innovation, productivity, efficiency, and growth in many domains, creating enormous benefits for the global economy. However, with massive data and advanced data analytical techniques, far more information can be inferred than most people have anticipated at the time of data collection/publication. Traditional privacy-preserving techniques are either insufficient against such new privacy attacks or preventing reasonable data usage. We need a secure and privacy-preserving solution which allows people to learn information as it was intended and stops people from learning information in ways it was not.

 In this talk, I will first describe privacy challenges in current big data applications , and then focus on protecting the privacy of biomedical "big" data in healthcare systems. Our work attempts to design a practical, secure, and privacy-preserving framework for utilizing healthcare data which are distributed among multiple parties. Our framework is general and can be used for multiple learning algorithms. Moreover, I will briefly introduce my work on  security and privacy in other big data applications such as mobile computing and smart metering.

Yanmin Gong received the B.Eng. degree in electronics and information engineering from Huazhong University of Science and Technology, China, and the M.S. degree in electrical engineering from Tsinghua University, China, in 2009 and 2012, respectively. She is currently a PhD candidate in electrical and computer engineering at the University of Florida. Her current research interests focus on security and privacy in big data with applications in healthcare, mobile computing, and cyber-physical systems.

Random Subcarrier Allocation in OFDM-Based Cognitive Radio Networks

Date: 
Monday, February 8, 2016 - 3:00pm to 4:00pm
Location: 
103 ATRC

Refreshments and discussion following.  Open to the public.

SPEAKER:  Dr. Sabit Ekin

ABSTRACT:   Advances in communications technologies entail demands for higher data rates. One of the popular solutions to fulfill this requirement was to allocate additional bandwidth, which unfortunately is not anymore viable due to spectrum scarcity. In addition, spectrum measurements around the globe have revealed the fact that the available spectrum is under-utilized. One of the most remarkable solutions to cope with the under-utilization of radio-frequency spectrum is the concept of cognitive radio (CR) with spectrum sharing features, also referred to as spectrum sharing systems.

This work investigates the performance of an orthogonal frequency-division multiplexing (OFDM)-based CR spectrum sharing communication system that assumes random allocation and absence of the primary user’s (PU) channel occupation information, i.e., no spectrum sensing is employed to acquire information about the availability of unused subcarriers or the PU's activity. Due to the lack of information about PUs' activities, the secondary user (SU) randomly allocates the subcarriers of the primary network and collide with the PUs' subcarriers with a certain probability. The average capacity of SU with subcarrier collisions is employed as performance measure to investigate the proposed random allocation scheme for both general and Rayleigh channel fading models. In the presence of multiple SUs, the multiuser diversity gain of SUs is also investigated. The main benefit of proposed random subcarrier utilization is to uniformly distribute the amount of SUs' interference among the PUs' subcarriers, also termed as interference spreading. The analysis and performance of such a communication set-up provides useful insights and can be utilized as a valid benchmark for performance comparison studies in CR spectrum sharing systems that assume the availability of spectrum sensing information. Further, the complexity of the proposed random access method with respect to the methods based on spectrum sensing is much lower due to the elimination of spectrum sensing mechanism and minimal cooperation between primary and secondary base stations.

Sabit Ekin received his B.Sc. degree in the Department of Electrical and Electronics Engineering from Eskisehir Osmangazi University in Eskisehir, Turkey, in 2006, the M.Sc. degree from the Department of Electrical Engineering from New Mexico Tech, Socorro, NM, in 2008, and the Ph.D. degree from the Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX in 2012.

He was working as a visiting research assistant in Electrical and Computer Engineering Program at Texas A&M University at Qatar (2008–2009). During the summer of 2012, he worked with the Femto-cell interference management team in the Corporate R&D at New Jersey Research Center, Qualcomm Inc. After his Ph.D. study, he joined in Qualcomm Technologies Inc., San Diego, CA, where his is currently working as a senior modem system engineer at the Department of Qualcomm Mobile Computing. His research interests are in the areas of design and performance analysis of communications systems, particularly interference management and statistical modeling of interference in next-generation wireless and cognitive radio networks.