SIG

Virtual Seminar by Nan Cheng

Title: RingSFL: An Adaptive Split Federated Learning Towards Taming Client Heterogeneity

Date and Time:  Sept. 1, 2023, 9:00 am – 10:00 am US Eastern Time (New York Time)

Zoom Link: https://us04web.zoom.us/j/76618091026?pwd=bSR2dziIyZUS0aWF2R666BJEl4pMS5.1

Abstract:  Federated learning (FL) has gained increasing attention due to its ability to collaboratively train while protecting …

Virtual Seminar by Arup Bhuyan

Title: 5G and Future G Wireless Security

Date and Time: January 25, 2023 at 11 AM ET

Registration Process: Please register at https://albany.zoom.us/meeting/register/tJctceysqjsoHdEotovMh872sxFBObm4gOsD

Abstract: Monitoring and detecting abnormalities in the 5G and Future FG wireless networks are a necessity for their secure use. Spectrum sensing is also a key …

Virtual Seminar by Tim O’Shea

Title: Securing and Optimizing Wireless Systems with AI-Native & Data-Driven Wireless Signal Processing in the Physical Layer

Date and Time: December 13, 2022 at 10 AM ET

Registration Process: Please register at https://tinyurl.com/38s8vxuc

Abstract: This talk will provide an overview of ways in which machine learning and data-driven signal …

Virtual Seminar by Bhaskar Krishnamachari

Title: Blockchain Technology and its applications to the Internet of Things

Date and Time: November 11, 2022 at 11AM ET

Registration Process: Please register at https://tinyurl.com/y9ebze79

Abstract: Blockchain technology is bringing fundamental new capabilities pertaining to decentralized trust and enabling micropayments for data. I will present results from research …

Virtual Seminar by John M. Shea

Title: AI and Privacy in Collaborative Spectrum Sharing: Perspectives from the Spectrum Collaboration Challenge and Beyond

Date and Time: April 27, 2022 at 10AM ET

Registration Process: Please register at https://tinyurl.com/2p9fus4s

Abstract: Dynamic spectrum access has the potential to greatly improve the utilization of the radio spectrum over existing …

Virtual Seminar by Aylin Yener

Title: 6G for Information Security and Information Security for 6G

Date and Time: March 30, 2022 at 11AM ET

Registration Process: Please register at https://tinyurl.com/fh2w9meu

Abstract: 6G is envisioned as the next wireless revolution, introducing novel materials and devices, metrics and requirements, designs and applications of wireless communications, as …

Virtual Seminar by Marwan Krunz

Title: Machine Learning Classification of RF Signals over Congested and Contested Spectrum: Algorithms and Experimentation

Date and Time: February 23, 2022 at 11AM ET

Registration Process: Please register at https://tinyurl.com/zkvvsjav

Abstract: Machine learning (ML) has recently been applied for the classification of radio frequency (RF) signals. One use case …

Virtual Seminar by Danijela Cabric

Title: Open Set Wireless Transmitter Authorization: Deep Learning Approaches and Practical Considerations

Date and Time: November 19, 2021 at 11AM ET

Registration Process: Please register at https://tinyurl.com/wh89zv5w

Abstract: As the Internet of Things (IoT) continues to grow, ensuring the security of systems that rely on wireless IoT devices has …

Virtual Seminar by Walid Saad

Title: Brainstorming Generative Adversarial Networks (BGANs): Framework and Application to Wireless Networks

Date and Time: October 22, 2021 at 10AM EDT

Registration Process: Please register at https://tinyurl.com/2sn8tbwj

Abstract: Due to major communication, privacy, and scalability challenges stemming from the emergence of large-scale Internet of Things services, machine learning is …

Virtual Seminar by Ekram Hossain

Title: Federated Learning in Unreliable and Resource-Constrained Cellular Wireless Networks

Date: May 26, 2021; Time: 11AM EDT

Registration: Please register at https://albany.zoom.us/meeting/register/tJYvd-irrDMuH9ImDFQ65_9LugOGR4J-fEBg
Abstract: Federated learning is a machine learning setting where the centralized location trains a learning model by using remote devices. Federated learning algorithms cannot be employed …