Speaker: Sarika Khushalani Solanki
Date: January 8, 2024
Time: 5:00 PM - 6:00 PM
Place: ESB G102
Abstract: Introduce the graduate seminar series and welcome students.
Speaker Bio: Biography: Sarika Khushalani Solanki received B.E. and M.E. degrees from India in 1998 and 2000 respectively. She received Ph.D. in Electrical and Computer Engineering from Mississippi State University, USA in 2006. She is currently an Associate Professor in Lane Department of Computer Science and Electrical Engineering at West Virginia University, Morgantown, WV, since August 2009. Prior to that, she worked for Open Systems International Inc, Minneapolis, MN as a Senior Engineer for three years. She has served as reviewer in National Science Foundation and Department of Energy and is past president of IEEE Distribution Systems Analysis Subcommittee and IEEE Career Promotion and Workforce Development Subcommittee and is editor of Transactions in Smart Grid. She is a recipient of Honda Fellowship award and NSF Career Award. Her research interests are Smart Grid, Power Distribution System, computer applications in power system analysis and power system control.
Speaker: Martin Dunlap
Date: January 22nd, 2024
Time: 5:00 PM - 6:00 PM
Place: ESB G102
Abstract: He will introduce the services and resources available through the WVU Libraries. These library resources may be critical to your graduate research.
Speaker Bio: He joined WVU in 1998 and has spent 10+ years working in the swamps of Florida as an environmental consultant. Since then he has worked in libraries first in Cleveland, Ohio and then here at WVU in various capacities. He recently got promoted to be the Engineering Librarian at WVU.
Speaker: WVU IT
Date: NA
Time: NA
Place: At your desk
Abstract: There is an online plagiarism tutorial at https://wvu.qualtrics.com/jfe/form/SV_6W3rGjsAaEenYgd
Here are the steps:
View videos.
Take a self-test.
Repeat steps for each module.
Take the Plagiarism Avoidance Test.
How do you progress through this tutorial?
View videos or read material in a module. Take a self-test after reading and viewing materials in a module. This self-test is for practice and taking it will open the next module. Repeat steps for each module, five modules in all. After viewing / reading the material in each module and taking the self-tests, take the Plagiarism Avoidance Test.
Speaker: David Bader
Date: Monday, February 5, 2024
Time: 5:00 PM
Place: Zoom-https://wvu.zoom.us/j/9188836315
Abstract:Data science aims to solve grand global challenges such as: detecting and preventing disease in human populations; revealing community structure in large social networks; protecting our elections from cyber-threats, and improving the resilience of the electric power grid. Unlike traditional applications in computational science and engineering, solving these social problems at scale often raises new challenges because of the sparsity and lack of locality in the data, the need for research on scalable algorithms and architectures, and development of frameworks for solving these real-world problems on high performance computers, and for improved models that capture the noise and bias inherent in the torrential data streams. In this talk, Bader will discuss the opportunities and challenges in massive data science for applications in social sciences, physical sciences, and engineering.
Bio:David A. Bader is a Distinguished Professor and founder of the Department of Data Science and inaugural Director of the Institute for Data Science at New Jersey Institute of Technology. Prior to this, he served as founding Professor and Chair of the School of Computational Science and Engineering, College of Computing, at Georgia Institute of Technology. Dr. Bader is a Fellow of the IEEE, ACM, AAAS, and SIAM; a recipient of the IEEE Sidney Fernbach Award; and the 2022 Innovation Hall of Fame inductee of the University of Maryland’s A. James Clark School of Engineering. He advises the White House, most recently on the National Strategic Computing Initiative (NSCI) and Future Advanced Computing Ecosystem (FACE). Bader is a leading expert in solving global grand challenges in science, engineering, computing, and data science. His interests are at the intersection of high-performance computing and real-world applications, including cybersecurity, massive-scale analytics, and computational genomics, and he has co-authored over 300 scholarly papers and has best paper awards from ISC, IEEE HPEC, and IEEE/ACM SC. Dr. Bader has served as a lead scientist in several DARPA programs including High Productivity Computing Systems (HPCS) with IBM, Ubiquitous High Performance Computing (UHPC) with NVIDIA, Anomaly Detection at Multiple Scales (ADAMS), Power Efficiency Revolution For Embedded Computing Technologies (PERFECT), Hierarchical Identify Verify Exploit (HIVE), and Software-Defined Hardware (SDH). Recently, Bader received an NVIDIA AI Lab (NVAIL) award, and a Facebook Research AI Hardware/Software Co-Design award. Dr. Bader is Editor-in-Chief of the ACM Transactions on Parallel Computing, and General Co-Chair of IPDPS 2021, and previously served as Editor-in-Chief of the IEEE Transactions on Parallel and Distributed Systems. He serves on the leadership team of Northeast Big Data Innovation Hub as the inaugural chair of the Seed Fund Steering Committee. ROI-NJ recognized Bader as a technology influencer on its 2021 inaugural and 2022 lists. In 2012, Bader was the inaugural recipient of University of Maryland’s Electrical and Computer Engineering Distinguished Alumni Award. In 2014, Bader received the Outstanding Senior Faculty Research Award from Georgia Tech. Bader is a member of Tau Beta Pi (National Engineering Honor Society), Eta Kappa Nu (Electrical Engineering Honor Society), and Omicron Delta Kappa (National Leadership Honor Society). Bader has also served as Director of the Sony-Toshiba-IBM Center of Competence for the Cell Broadband Engine Processor and Director of an NVIDIA GPU Center of Excellence. In 1998, Bader built the first Linux supercomputer that led to a high-performance computing (HPC) revolution, and Hyperion Research estimates that the total economic value of Linux supercomputing pioneered by Bader has been over $100 trillion over the past 25 years. Bader is a cofounder of the Graph500 List for benchmarking “Big Data” computing platforms. He is recognized as a “RockStar” of High Performance Computing by InsideHPC and as HPCwire’s People to Watch in 2012 and 2014.
Speaker: Dr. John Libert
Date: Monday, March 4, 2024
Time: 5:00 PM
Place: Zoom-https://wvu.zoom.us/j/9188836315
Abstract: : Contactless acquisition of fingerprints presents a fundamental departure from legacy capture technologies. The friction ridge surface that comprises a fingerprint is a three-dimensional topography superimposed upon a three-dimensional curved surface of a finger presenting many challenges in both acquisition as well as interoperability with legacy contact collected imagery. In this presentation we will discuss NIST’s work in the area of standardizing this nascent technology, and the challenges in doing so.
Bio: John Libert has worked at NIST for over twenty-four years, variously engaged in developing measurements by which to assess video quality, performance of electronic flat panel displays, and biometric image quality. His current primary focus is development of metrics, protocols, and standard test artifacts for the evaluation of contactless fingerprint acquisition devices and their interoperability with legacy contact devices.
Speaker: Yenumula Reddy
Date: Monday, March 25, 2024
Time: 5:00 PM
Place: ESB G102
Abstract: The term “Artificial Intelligence” was coined by John McCarthy in 1956 to attract more attention to the planned Computer Science Conference at Dartmouth. Ever since, the society expected some day machines will do the manual labor and thinking for us and we will live in a society of leisure surrounded by unlimited number of “Machine-Servants.” Even after 68 years, we have not realized that Utopian Society. We may be closer than ever, but we are not there, and may be never. If we examine the history of science and technology, we will realize mere invention of a technology will not automatically improve the society. Machines that can do what we do have to do must be invented before the promise of the inventions could be fully realized. Invention of steam engine did not automatically benefit farmers until machines like tractor and harvester were developed. Invention of electricity automatically impact the society until the lightbulb, motors, etc. were developed. Recent developments in Generative AI and the possibility of developing the Artificially General Intelligence (AGI) has led to wild speculations the future of the society. In this talk I will discuss the concept of Knowledge Advantage and how it could be exploited by Knowledge Workers using Personal Knowledge Advantage Machines that are within reach.
Bio: Ramana Reddy is a professor of Computer Science at West Virginia University (WVU). He created the first AI Lab in 1981 which gave rise to two successful start-up companies acquired by Fortune 100 companies. His team at the AI Lab and later at the DARPA funded Concurrent Engineering Research Center (CERC) demonstrated how AI could be used in designing complex industrial products. Later, under the DARPA Dual Use Technology Initiative, in collaboration with the National Library of Medicine, CERC demonstrated the first Web-Based Electronic Medical Record – even before Web Browsers were commonplace. Professor Reddy is now focused on creating a framework for building Knowledge Advantage Machines. He is also involved in realizing Healthy Longevity through exploitation of Robotics and Knowledge Advantage.
Speaker: Piotr Wojciechowski
Date: Monday, April 1, 2024
Time: 5:00 PM
Place: https://wvu.zoom.us/j/9188836315
Abstract: The database migration problem entails the movement of data between different databases. Such migration is often necessary due to database software updates or from changes to hardware, project standards, and other business factors. This is a pervasive issue in cloud computing clusters, where a pay-per-use infrastructure and unpredictable workloads necessitate frequent allocation and movement of data. Thus, there is a pressing need for efficient procedures to minimize the resource overhead involved in data migration. This interest has also been fueled in recent years by the massive generation of data in what is now being called the Big Data age. Consequently, there has been a proliferation of resource-intensive data centers and the adoption of cloud computing and storage as a service in order to manage said data.
Bio: Piotr Wojciechowski is an Assistant Professor in the Lane Department of Computer Science and Electrical Engineering at West Virginia University. Dr. Wojciechowski earned a PhD in Computer Science from West Virginia University in 2019. Dr. Wojciechowski’s research is concerned with the application of concepts from theoretical computer science in artificial intelligence and data science. Problems in both of these fields arise in practical situations. Thus, modeling such problems using constraints and networks is a crucial step towards generating efficient algorithms for these problems and problems in related fields.