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The Department of Electrical Engineering and Computer Science at the University of Wyoming is offering the EECS Colloquium series as a service to all who are interested in Electrical Engineering and Computer Science. Most seminars in Fall 2024 are scheduled for Monday 3:10PM -- 4:00PM in EERB 251. For help finding the locations of our seminar meetings, consult the on-line UWyo campus map. For questions about this page or to schedule talks, please contact Diksha Shukla: dshukla@uwyo.edu. Here is a list of seminar schedules. Previous EECS Colloquium Speakers. |
EECS Colloquium Schedule, Fall 2024
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EECS Colloquium What the Philosophy of Computing is About Speaker: Dr. Robin Hill, University of Wyoming, Laramie, WY When: 3:10PM ~ 4:00PM, Monday, October 14, 2024 Abstract: Does Nature use data? Can virtue epistemology mitigate information disorder? What would truly objective Web search look like? These are questions in the philosophy of computing; others abound, across the standard subjects of computing and the prominent inquiries of philosophy. To investigate these questions is to integrate the technical with the interpretive, yielding a deeper understanding of our products and activities. Bio: Dr. Hill is a lecturer in Electrical Engineering and Computer Science, and affiliate faculty member in both Philosophy and the Wyoming Institute for Humanities Research, at the University of Wyoming. Her research interest is the philosophy of computer science, on which she writes a blog for the online Communications of the ACM. Her teaching experience includes over 30 years of logic, computer science, and information systems courses for the University of Wyoming, University of Maryland University College (European Division), State University of New York at Binghamton, Metropolitan State College, and others. She holds a Ph.D., two Master's degrees, and a B.A. in Philosophy. |
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EECS Colloquium Unlocking VR Security: Identifying Vulnerabilities and Fortifying with Behavioral Biometrics Speaker: Sindhu Reddy Kalathur Gopal, CS Ph.D. Candidate, SSL Research Lab, EECS, University of Wyoming When: 3:10PM ~ 4:00PM, Monday, October 21, 2024 Abstract: Virtual Reality (VR) technology has become pervasive across various industries leading to a significant increase in the collection and storage of user-specific data on VR devices. Despite having well-documented vulnerabilities, current VR devices rely on conventional knowledge-based authentication methods such as passwords, pins, and graphical lock patterns for user identity verification. In particular, the existing knowledge-based authentication systems are shown to be more susceptible to vision-based attacks (e.g., Hidden Reality attacks presented in the literature) in immersive environments. To mitigate such security threats, we propose a novel user authentication system that authenticates users based on intrinsic hand movement signatures while they type on their VR screen. The system relies on hand movements encompassing innate hand gestures as users navigate to type characters and click on the virtual screen, captured by IMU sensors. The experiment results indicate the robustness and potential of our user verification system as a secure authentication solution tailored for the virtual reality environment. Bio: Sindhu Reddy is Computer Science PhD candidate in the EECS department at the University of Wyoming. Her research focuses on both offensive and defensive analysis of wearable devices. She is interested in analyzing side channels to uncover security vulnerabilities in smart wearables and in designing user-friendly, lightweight, and cost-efficient authentication system(s) using behavioral biometrics. |
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EECS Colloquium Tripolar Concentric Ring Electrodes (TCREs) for Bidirectional Brain Communication Speaker: Dr. Walter Besio, Professor, Department of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI When: 3:10PM ~ 4:00PM, Monday, October 28, 2024 Abstract: Electroencephalography (EEG) is an essential component in the evaluation of epilepsy, the most common serious brain disorder worldwide. Misdiagnosis of epilepsy is very common and occurs in up to 50% of the patients. Artifact contamination seriously hinders the effectiveness of EEG and is a root cause of misdiagnosis. Dr. Besio has been developing a tripolar concentric ring electrode (TCRE) sensor and a t-Interface that registers tripolar EEG (tEEG, nano-volt signals) and emulated EEG (eEEG) from the same sensors concurrently. tEEG resolves the fundamental drawbacks of conventional EEG, providing significant improvement in signal fidelity, spatial resolution, and registering of higher frequency brain activities, where conventional EEG is lacking. The fundamental principles of the TCRE and t-Interface automatically cancel artifacts, such as from muscles, which are orders of magnitude larger than scalp-recorded brain signals. Dr. Besio will provide examples for comparison between tEEG and EEG for epilepsy and brain computer interfacing. Further, about 12 in 100 people worldwide, or 800 million, are suffering from neurological disorders such as epilepsy, chronic pain, Parkinson’s, etc. Around 450 million people worldwide are affected by psychiatric disorders. Despite decades of research, new drugs, and advances in surgical therapy, up to 30% of the patients with epilepsy or psychiatric disorders do not respond to medical treatment or suffer from its severe side effects. Dr. Besio has also been developing transcranial focal electrical stimulation (TFS), applied through CREs, and will show how TFS prevents epilepsy, stops seizures, alters neurotransmitters and genes, as well as enhances anti-seizure drugs. More Information: http://egr.uri.edu/neurorehabilitationlab/ and https://cremedical.com/ Contact: besio@uri.edu and walt@cremedical.com Bio: Dr. Besio is a Professor in the Department of Electrical, Computer, and Biomedical Engineering and Interdisciplinary Neuroscience Program at the University of Rhode Island (URI). Dr. Besio received his M.S. and Ph.D. degrees in biomedical engineering from the University of Miami and a B.S. in electrical engineering from the University of Central Florida. Prior to joining academia, Dr. Besio worked 12+ years in the biomedical device and electronics industries. Dr. Besio specializes in research to develop innovative biomedical instrumentation for diagnosis and therapies for enhancing the lives of persons with neurological disease and disability. This work involves unique patented concentric electrodes for neuromodulation and brain computer interfacing (bidirectional). Dr. Besio is a co-founder of the URI Graduate Interdisciplinary Neuroscience Program that has since spawned the Ryan Institute for Neuroscience and an undergraduate program. He is an Institute for Electrical and Electronics Engineers (IEEE) Senior Member, IEEE Engineering in Medicine and Biology Society (EMBS) (representative to TBioCAS and BioCAS, Faculty Advisor URI Student Chapter, past Vice President of Finance, past North American Administrative Committee Member, past Wearable Biomedical Sensors and Systems Technical Committee Chair, past EMBS Sensors Council representative, and past Chair Providence Chapter), and an active member of the American Epilepsy Society (Technical Committee and Fellows Mentor). Dr. Besio has also developed intellectual property that forms the basis for his medical device startup company CREmedical Corporation. Dr. Besio is passionate about moving his research beyond the laboratory to help relieve disease, disability, pain, and suffering. |
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EECS Colloquium Modeling and Reasoning about Cyber-Physical Systems Resiliency Speaker: Dr. Indrakshi Ray, Colorado State University, Fort Collins, CO. When: 3:10PM ~ 4:00PM, Monday, November 11, 2024 Abstract: Operation efficiency in cyber physical system (CPS) has been significantly improved by digitalization of industrial control systems (ICS). However, digitalization exposes ICS to cyber attacks. We discuss how to model and reason about cyber-resiliency using existing tools and technologies. We use Coloured Petri Nets (CPN) for formal representation – CPN is supported by automated tools for analysis and it has been used for verification of real-world systems. We use Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, and Elevation of Privilege (STRIDE) for evaluating the threats in the ICS architecture. We use Microsoft Threat Modeling Tool (MTMT) for ICS threat modeling that classifies the threats into the categories defined in STRIDE. Threat models are also converted into CPN models. The CPN models of the ICS architecture and the threat model are then composed. The methodology then verifies the resulting CPN. This verification explores the system states where the ICS cannot resist the attacks. The methodology is applied to a wind farm system comprising many distributed subsystems connected via various networks. The result shows that the methodology is practical for the ICS verification and assets criticality assessment, providing recommended mitigations to construct a robust ICS. Bio: Indrakshi Ray is a Professor in the Computer Science Department at Colorado State University. She is the Director of Colorado Center for Cyber Security at Colorado State University. She is also the Site Director of NSF IUCRC Center for Cyber Security Analytics and Automation. She has been a visiting faculty at Air Force Research Laboratory, Naval Research Laboratory, and at INRIA, Rocquencourt, France. She obtained her Ph.D. in Information Technology from George Mason University. Dr. Ray's research interests include software assurance, data analytics and security. She has published over two hundred and fifty technical papers in refereed journals and conference proceedings with the support from agencies including Air Force Research Laboratory, Air Force Office of Scientific Research, National Institute of Health, National Institute of Standards and Technology, National Science Foundation, the United States Department of Agriculture, and industries from the US, Norway, and Japan. Dr. Ray is on the editorial board of International Journal of Information Security, Computer Standards and Interfaces, and Associate Editor of IEEE Security & Privacy. Dr. Ray is associated with the program committees of various conferences including ACM CCS, ACM CODASPY, ACM SACMAT, DBSec, EDBT, ESORICS, ICDE, VLDB, and WWW. She is a senior member of the IEEE and a senior member of the ACM. She was awarded Professor Laureate from the College of Natural Sciences at Colorado State University. |
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EECS Colloquium An Analysis of Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs): Advancements, Architectures, and Applications Speaker: Mohamad Zamini, Ph.D. Candidate, SSL Research Lab, EECS, University of Wyoming. When: 3:10PM ~ 4:00PM, Monday, November 18, 2024 Abstract: Large Language Models (LLMs) have transformed the landscape of language understanding and generation, providing significant breakthroughs in natural language processing, reasoning, and personalized interaction. As multimodal capabilities emerge, Multimodal Large Language Models (MLLMs) extend these advancements by integrating text with additional modalities, such as vision and audio, to facilitate more holistic understanding and versatile interaction across varied input types. This presentation presents a comparative analysis of LLMs and MLLMs, examining their architectures, core components, and the latest advancements driving each model type. We assess key applications, performance benchmarks, and limitations, highlighting how multimodality enhances model interpretability and cross-modal reasoning. Through this comparative framework, we provide insights into the strengths and challenges of each model, setting the stage for future research directions in multimodal interactions, cross-modal embedding frameworks, and the design of increasingly interactive and intelligent AI systems. Bio: Mohamad is a PhD candidate in Computer Science, specializing in multimodal large language models (MLLMs) with a focus on advancing reasoning capabilities and improving model performance. His research integrates foundational principles in artificial intelligence with cutting-edge methods in multimodality to push the boundaries of model interpretability and cross-modal interactions. Previously, he worked at Numenta Inc. during an internship, contributing to research on foundational models, where he gained valuable experience in scalable model architectures and sparse attention mechanisms in LLMs. |
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EECS Colloquium TBA Speaker: Dr. Ruben Gamboa, University of Wyoming, Laramie, WY. When: 3:10PM ~ 4:00PM, Monday, November 25, 2024 Abstract: TBA Bio: TBA |
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EECS Colloquium TBA Speaker: Dr. Rob Sumners, Advanced Micro Devices (AMD), Fort Collins, CO. When: 3:10PM ~ 4:00PM, Monday, December 02, 2024 Abstract: TBA Bio: TBA |
