• Jun.

• 18

• 2026

IEEE Talk: Underwater Wireless Communication Systems and Networks: A Survey, Future Directions, and Novel Proposals

2026-06-18T14:00:00.000Z, 2026-06-18T14:00:00.000Z – 2026-06-18T15:00:00.000Z
Walter Light Hall, Room 314, Queen's University

Hosted by Kingston Section Chapter, C16/COM19
Co-hosted by Kingston Section; Newfoundland Labrador Sect Chap, C16/COM19/CAS04;

Title:
Underwater Wireless Communication Systems and Networks: A Survey, Future Directions, and Novel Proposals
Speaker:
Abdallah S. Ghazy
Bio:
Abdallah Ghazy received the B.Sc. degree in Electrical Engineering from Al-Azhar University, Cairo, Egypt, in 2007, the M.Sc. degree from the Egypt-Japan University of Science and Technology (E-JUST), Alexandria, Egypt, in 2016, and the Ph.D. degree in Electrical and Computer Engineering from McMaster University, ON, Canada, in 2021. From 2008 to 2017, he worked in the telecommunications industry with Sina Technology, Cairo, Egypt, where he contributed to the design, deployment, and operation of telecommunication systems and networks. Alongside his industrial experience, he served as a Teaching Assistant at both Al-Azhar University and McMaster University between 2012 and 2021, supporting courses and laboratory activities in communications, signal processing, and networking systems. Between 2021 and 2025, he was a Research Fellow with École de technologie supérieure (ÉTS), Montréal, Canada, where he conducted advanced research on Space and Defence technologies. Since December 2025, he has been a Research Associate with Calian Group Ltd., Ottawa, Canada, contributing to research and development activities in advanced Space and Defence technologies. His research has contributed to emerging communication paradigms spanning RF, optical, acoustic, underwater, and satellite communication systems, with an emphasis on heterogeneous networking, intelligent protocol design, signal processing, machine learning, and communication security. His work also explores AI-assisted optimization techniques for future resilient and adaptive communication infrastructures.
Abstract:
Underwater wireless sensor networks (UWSNs) have gained increasing attention for civil and defense applications, but underwater environments present major challenges such as dynamic channels, localization difficulties, high delays, limited bandwidth, energy constraints, interference, and strong noise. This work presents a comprehensive survey of UWSN protocols across the physical, MAC, and routing layers, including existing network stacks, underwater modems, and security threats, with emphasis on the Smart Adaptive Long- and Short-range Acoustic (SALSA) stack. The survey also discusses emerging technologies in machine learning and cybersecurity for intelligent, adaptive, and secure underwater communication systems, highlighting their potential in channel estimation, routing optimization, anomaly detection, intrusion prevention, and autonomous network management. Based on the identified research gaps, two main contributions are proposed. First, Developed-SALSA (D-SALSA) stack protocols are introduced to improve adaptability, energy efficiency, throughput, and communication reliability. Second, a heterogeneous underwater architecture combining acoustic and optical communication technologies is presented to support high-rate and large-scale data transmission. Finally, future research directions and open challenges related to AI-assisted networking, cross-layer optimization, and resilient cybersecurity frameworks are discussed.

Save to calendar:

• iCal
• Save to Outlook (vCal)

• Jul.

• 03

• 2026

IEEE WIE Panel Discussion : From Blueprints to Startups - Engineers as Emerging Founders in the Startup Ecosystem

2026-07-03T18:30:00.000Z, 2026-07-03T18:30:00.000Z – 2026-07-03T19:30:00.000Z
, Room EN 3075, Faculty of Engineering and Applied Science

Hosted by Newfoundland-Labrador Section Affinity Group, WIE
Co-hosted by Newfoundland-Labrador Section;

From Blueprints to Startups: Engineers as Emerging Founders in the Startup Ecosystem

As part of the IEEE WIE Day 2026 celebrations, IEEE Women in Engineering (WIE) Newfoundland and Labrador, together with the Memorial Centre for Entrepreneurship (MCE), invites you to an engaging panel discussion on innovation, entrepreneurship, and leadership in STEM.

Hear from entrepreneurs, startup leaders, innovation mentors, and academic experts as they share their experiences in transforming ideas into impactful ventures. The discussion will explore innovation, entrepreneurship, mentorship, startup development, and the opportunities and challenges involved in building successful ventures.

Whether you are a student, researcher, early-career professional, or aspiring entrepreneur, this event offers valuable insights while celebrating the contributions of women in STEM innovation and entrepreneurship.

A networking session with refreshments will follow the panel discussion.

Registration is required. Please scan the QR code on the event flyer to register. Seating is limited, and registrations will be accepted on a first-come, first-served basis.

 

Save to calendar:

• iCal
• Save to Outlook (vCal)

• Jul.

• 14

• 2026

IEEE OES-GRSS-APS Invited Talk 2 (14 July 2026)

2026-07-14T17:30:00.000Z, 2026-07-14T17:30:00.000Z – 2026-07-14T18:30:00.000Z
CSF, Room 1203,

Hosted by Newfoundland-Labrador Sect Jt.Chap,OE22/GRS29/AP03

IEEE OES-GRSS-APS Invited Technical Talk 2

Speaker: Dr. Kegen Yu

Title：Monitoring Ocean States with Spaceborne GNSS Reflectometry

Abstract: Global Satellite Navigation System Reflectometry (GNSS-R) is an emerging remote sensing technology that is increasingly widely used in Earth observation, environmental parameter retrieval, and monitoring of marine and terrestrial disasters. This talk primarily discusses the use of spaceborne GNSS-R technology for monitoring ocean conditions, selecting three ocean parameters—sea surface wind speed and direction, and sea surface wave height—as retrieval targets. It focuses on studying how to construct ocean parameter retrieval models using machine learning algorithms under the condition of sufficient observational data samples. Model training primarily utilizes GNSS-R observation data from China's Fengyun-3E and the U.S. CYGNSS satellites, along with several ocean parameter product datasets as reference data. Through extensive experimental data processing, the model's performance was validated, demonstrating that spaceborne GNSS-R technology can be applied to monitor ocean conditions and serve as an effective supplement to existing ocean monitoring techniques.

Time: 3pm-4pm NST, 14 July, 2026

Location: CSF-1203, Memorial University

Save to calendar:

• iCal
• Save to Outlook (vCal)