Fall 2022 Seminars

Speaker: Sarika Khushalani Solanki

Date: August 22, 2022

Time: 5:00 PM - 6:00 PM

Place: AERB 135

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: August 29th, 2022

Time: 5:00 PM - 6:00 PM

Place: AERB 135

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: Sara Tehranipoor

Date: Monday, October 10, 2022

Time: 5:00 PM

Place: AERB 135

Abstract:Hardware security refers to the protection of physical devices from vulnerabilities and harm. A strong hardware security foundation is a great essential for realizing secure systems. Additionally, the demand for hardware security research and innovation is increasing with growing security needs in digital hardware devices. The hardware layer of devices is often directly exposed to physical attacks, which manipulate hardware or software function by physical means and pose many challenges/vulnerabilities. One potential approach to making such physical attacks more difficult is to apply hardware security primitives modules (e.g. PUFs and TRNGs) throughout the design process. Another approach is to increase the security of circuit netlists using hardware obfuscation and logic locking. In addition, applying machine learning methods to explore hardware vulnerabilities/threats are another promising methodology. In this talk, first, I will present a number of new hardware security primitives architectures that can help the use of unique characteristics of hardware to design lightweight and effective solutions for establishing security and trust in embedded systems. Second, I will present novel techniques of logic locking followed by attacks and defenses against these methods. Thirdly, I will discuss the use of machine learning techniques for exploring the vulnerabilities of secured designs and propose countermeasures.

Bio:Sara Tehranipoor is currently an Assistant Professor of the Lane Department of Computer Science and Electrical Engineering at the West Virginia University. Previously, she was an Assistant Professor of Electrical and Computer Engineering department at the Santa Clara University. She received her Ph.D. in Electrical and Computer Engineering from the University of Connecticut, in 2017. She obtained her MS and BS degree in Computer Hardware Engineering from Iran in 2013 and 2011, respectively. Sara and her research team work on a variety of hardware security from hardware foundation to applied Machine Learning in hardware security. Topics include hardware security primitives, AI in hardware security, side-channel analysis and hardware obfuscation. Sara is the leading author/co-author of 40+ peer-reviewed conference proceedings, journal articles, and book chapters as well as mentoring 40+ graduate and undergraduate students for their research thesis and senior design projects. She has served in the organizing and technical program committee members of many IEEE/ACM conferences such as ISQED, GLSVLSI, DAC, ICCAD, DATE, CODES+ISSS, ISVLSI, VDEC, etc. She is actively involved in Women in Engineering related conferences/workshops/committees as a chair, co-chair, and session chair. She is the Silicon Valley Cybersecurity Conference 2020 Women/Minority in Cybersecurity (WMiCS) session chair. Dr. Tehranipoor received the “Best Technical Paper Award” in the 30th International Conference on VLSI Design (VLSID) and 16th International Conference on Embedded Systems in 2017. She is currently serving as an associate editor for IEEE Consumer Electronics Magazine (ICEM), and section editor of the Discover Internet of Things (DIoT) Journal.

Speaker: Scott Zemerick

Date: Monday, October 17, 2022

Time: 5:00 PM

Place: AERB 135.

Abstract:Software-only-Simulation Test Beds (SoST) are beginning to become more popular among aircraft, spacecraft, and smallsat embedded system developers due to the high cost of duplicating hardware test beds. Traditionally, large Department of Defense and NASA projects will duplicate rooms of expensive “one-off” engineering test units (ETUs) for unit testing and integration testing prior to operational deployment. The problems with this approach are many; most notably hardware is limited which creates a “scarce resource” problem that causes testing, specifically software (integration) testing, to suffer. SoSTs provide a software-only, or virtual test bed, that creates a “digital-twin” that contains software models of the ETUs, and often includes modeled components such as flight computers, busses (e.g., MIL-STD-1553, SPI, I2C), compact PCI (cPCI) backplane cards, sensors, and actuators. The ultimate goal of a SoST is for it to have the capability of running the native system compiled-binary on its native CPU architecture (e.g., PowerPC, LEON3/4, ARM) on a standard X86 personal computer/laptop without needing to recompile for X86. This methodology maintains the “Test-As-You-Fly” approach and is a powerful capability when used in tandem with ETU test beds.

Bio: Dr. Scott Zemerick is a distinguished Chief Engineer and Program Manager with TMC Technologies, an innovative engineering and software development small business located in West Virginia. Dr. Zemerick has over twenty years of experience performing embedded systems R&D and commercial product-development-prototyping with successful product-to-market strategies. Scott is now a dedicated space enthusiast with interests in space exploration (public and private), scientific space research, and the search for life in the universe. At TMC, Dr. Zemerick is a contractor Lead of the Jon McBride Software Test and Research (JSTAR) laboratory at the NASA IV&V Facility in Fairmont, WV. Through this work, Scott has performed modeling and simulation on numerous NASA missions, such as the Space Launch System (SLS), James Webb Space Telescope (JWST), Deep Space Climate Observatory (DSCOVR), Psyche, Europa Clipper, and the Artemis missions (Orion and Gateway). These efforts are utilized for performing advanced Verification and Validation of missions’ flight software to ensure mission success. Dr. Zemerick was one of the Principal Investigators of WV’s First Spacecraft, Simulation-To- Flight-1 (STF-1), which is a SmallSat still operating on-orbit after 1300+ days. The highly successful STF-1 spacecraft led to the open-source software invention NASA Operational Simulator for SmallSats (NOS3), which was awarded Runner Up in the prestigious NASA Software of the Year Award 2019. Also in 2019, Dr. Zemerick was presented the NASA IV&V Engineer of the Year Award by NASA Director Jim Bridenstine, NASA IV&V Director Greg Blaney, and GSFC Deputy Directory George Morrow. Scott was born in the coalfields of WV and graduated magna cum laude from West Virginia University’s College of Engineering and Mineral Resources with a B.S. Computer Engineering, M.S. Electrical Engineering, and PhD Computer Engineering degrees. Dr. Zemerick is also an Adjunct Assistant Professor at West Virginia University with research focusing on spacecraft modeling, simulation, and flight software. Scott resides in WV with his wife, Cindy, of 18 years, and daughters Kayleigh and Sarah.

Speaker: Nima Karimian

Date: Thursday, October 20, 2022

Time: 5:00 PM

Place: AERB 120.

Abstract:The need for accurate and unclonable identity recognition methods has become an issue of increasing urgency, affecting security across the government, public, and private sectors. Biometrics authentication can pave the way for future safety and functioning. Nevertheless, they suffer from limitations associated with various attacks, e.g., spoofing attacks, template theft, illegal system access, etc. To address these weaknesses and mitigate public concern over privacy violations, it is imperative to make privacy protection a priority in developing the next-generation biometric authentication systems, which exploits continuous human-user authentication. This talk reviews the lessons learned by the community for spoofing detection using liveness detection and introduces promising new directions inspired by hardware security domain to protect biometric templates.

Bio:Nima Karimian is an Assistant Professor with the Lane Computer Science and Electrical Engineering Department at the West Virginia University. He is also director of Biometric Security Lab at WVU. His research covers the domain of security from biometric to hardware. He is pioneer of Biometrics Enabled Hardware Security field. Dr. Karimian has served on the technical program committees of leading events such as IJCB, HOST, BTAS, ISQED. He is currently serving as an associate editor for the Discover Internet of Things (DIoT) Journal. His research has also been recognized with best paper awards from venues, such as International Joint Conference on Biometrics (IJCB) for the IAPR TC4 Best Student Paper Award, the Best Technical Paper Award at 30th International Conference on VLSI Design (VLSID), and the Best Poster Award from FICS Research Conference on Cybersecurity. Dr. Karimian also received Faculty Excellence in Scholarship Award from SJSU in 2021.

Speaker: Mario Szegedy

Date: Monday, October 24, 2022

Time: 5:00 PM

Place: Online via Zoom. Please register here to get the attendance instructions.

Abstract:Quantum communication networks combine several quantum computers to enable them to solve interesting tasks from cryptography, communication complexity, distributed computing etc. Building a large-scale quantum communication network is a daunting task that will take many years, but networks with a few small quantum computers are under construction and may start to appear in the next few years. These networks are either based on channels that physically communicate quantum states, or rely on classical communication in tandem with shared entanglement, or a combination of both. Communication over classical channels cannot increase entanglement, so in the absence of quantum channels we have to rely on prior entangled states. In this work we study n-party resource states from which LOCC protocols can create EPR-pairs between any k disjoint pairs of parties. We give constructions of such states where k is not too far from the optimal n/2 while the individual parties need to hold only a constant number of qubits. In the special case when each party holds only one qubit, we describe a family of n-qubit states with k proportional to log n, based on Reed-Muller codes. We also show, that if k=n/2,then the parties must have at least Omega(loglog n) qubits each. Joint with Sergey Bravyi, Yash Sharma and Ronald de Wolf.

Bio:Mario Szegedy is a Hungarian-born computer scientist, professor of computer science at Rutgers University. He received his Ph.D. in computer science from the University of Chicago.Szegedy's research areas include complexity theory, combinatorics and quantum computing. He was awarded the Gödel Prize twice in 2001 and 2005 for his work on probabilistically checkable proofs and on the space complexity of approximating the frequency moments in streamed data.

Speaker: Luyi Wang

Date: Monday, November 7, 2022

Time: 5:00 PM

Place: Online via Zoom. Please register here to get the attendance instructions.

Abstract:With the development of Machine learning and deep learning, machine learning engineer, software engineer or data scientist can be confusing terms for many students in seeking their future career. In this talk, we will cover the life of a data scientist from an industry perspective, also share some excited development and research topics.

Bio:Luyi Wang is an American computer scientist and technology entrepreneur focusing Artificial Intelligence. He specialized in recommendation system and user-behavior based AI technology. In his past experience, he was employed by two biggest phone manufacturer, Samsung and Futurewei , and one Cloud Infrastructure company, VMware. During his work time in Samsung and Futurewei, he focused on building recommendation services using Machine Learning and AI. The recommendation system he designed and built provides services running on billions of devices and consumed by millions of end users. Starting from last year, Luyi started to apply AI technology on the cryptography and database domain.

Speaker: Chen Chen

Date: Monday, November 14, 2022

Time: 5:00 PM

Place: Online via Zoom. Please register here to get the attendance instructions.

Abstract:Video-analytics-as-a-service enables a wide range of real-world applications, e.g., video surveillance, smart shopping systems like Amazon Go, elderly person monitoring systems. A key concern in such services is the privacy of the videos being analyzed, as analyzing such information-rich video data may reveal personal information like an individual’s daily routine, home location, gender, race, clothes, etc. Therefore, there is a pressing need for solutions to privacy-preserving video analysis. In this talk, we will present our recent work on a novel self-supervised privacy-preserving action recognition framework. It removes privacy information from input video in a self-supervised manner without requiring privacy labels. Extensive experiments show that our framework achieves competitive performance compared to the supervised baseline for the known action privacy attributes. We also showed that our method achieves better generalization to novel action-privacy attributes compared to the supervised baseline.

Bio:Dr. Chen Chen is an Assistant Professor at the Center for Research in Computer Vision at the University of Central Florida. He received his Ph.D. in Electrical Engineering from the University of Texas at Dallas in 2016, receiving the David Daniel Fellowship (Best Doctoral Dissertation Award). He was an Assistant Professor at the Department of Electrical and Computer Engineering at the University of North Carolina at Charlotte from 2018 to 2021. His research interests include computer vision, efficient deep learning, and federated learning. He has been actively involved in several NSF and industry sponsored research projects, focusing on efficient resource-aware machine vision algorithms and systems development for large-scale camera networks, and federated learning for internet of things. He is an Associate Editor of IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), Journal of Real-Time Image Processing, and IEEE Journal on Miniaturization for Air and Space Systems. He also served as an area chair for several conferences such as ECCV’2022, CVPR’2022, ACM-MM 2019-2022, ICME 2021 and 2022. His recent paper on mitigating the effects of data heterogeneity on federated learning was nominated for the Best Paper Award at CVPR 2022. According to Google Scholar, he has 10K+ citations and an h-index of 51.