Prof. Ameer Abdelhadi

Professor of Computing, McMaster University
Talk Title: Customized Computer Architecture for Deep Learning and Neurotechnology 

Bio: Ameer M. S. Abdelhadi is an assistant professor of Computer Engineering in the Department of Electrical and Computer Engineering at McMaster University. He obtained his PhD in Computer Engineering from the University of British Columbia in 2016. Prior to joining McMaster, Dr. Abdelhadi held various academic positions as a research fellow and lecturer at the University of Toronto, Imperial College London, and Simon Fraser University. Before pursuing his graduate studies, he held multiple design and research positions in the semiconductor industry. Dr. Abdelhadi’s research interests span multiple areas, including application-specific custom-tailored computer architecture and hardware acceleration, hardware-efficient deep learning, neurotechnology, reconfigurable computing, and asynchronous circuits.
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Summary:

Commodity computing often fails to meet the stringent requirements of emerging compute- and memory-
intensive applications, particularly those constrained by latency, form-factor, and energy—especially when
deployed on portable and wearable devices. The success of such systems hinges upon real-time processing,
energy eƯiciency, and adaptability to user needs. Existing solutions are often post-hoc, resulting in limited
portability and energy eƯiciency. For such systems to become practical, highly optimized algorithms,
innovative computing paradigms, and customized hardware are essential to enable portable, scalable,
adaptable, real-time, and power-eƯicient processing.
Two decades ago, the semiconductors technology faced a power wall due to the demise of Dennard scaling,
which ended the golden era where increasing frequency could improve performance while reducing voltage
maintained power consumption. Instead, massively parallel architectures emerged, driven by the continuity
of Moore's Law, which predicted the availability of densely packed, cheaper transistors.
A prime example of this paradigm shift is the field of deep learning. Although the foundational concepts of
deep learning have been known for decades, their practical application was impeded by the limited
capabilities of commodity hardware. The introduction of general-purpose GPUs, with their massive spatially
parallel processing capabilities, revolutionized deep learning by enabling the eƯicient training and inference
of complex models. However, as deep learning algorithms become more sophisticated and demanding, and
as workloads continue to expand, even the most advanced GPUs are reaching their limits. This necessitates
the adoption of custom accelerators specifically designed for deep learning tasks, particularly for portable applications, where GPUs fail in energy eƯiciency.
This talk will delve into two critical domains where custom acceleration is indispensable: deep learning and neurotechnology. We will overview these fields and their potential applications and focus on the integral role
that custom computer architecture has to play for these areas to flourish. By examining case studies, we will explore how custom-tailored hardware solutions have unlocked unprecedented performance and energy eƯiciency, advancing the capabilities of both fields.
In neurotechnology, after taking a mile-high view of a brain-machine interface system, we will then highlight the unique challenges and solutions that have emerged in creating hardware to meet the stringent requirements of neural data processing. In deep learning, we will discuss our current hardware-accelerated deep learning techniques for reducing computation, data traƯic, and memory footprint. We conclude with a review of future research directions for custom-tailored computer architecture and its applications.
Join us to explore how the intersection of customized computer architecture and application-specific demands is shaping the future of computing, unlocking new potentials and enabling groundbreaking advancements in deep learning and neurotechnology

        Prof. Raed Mesleh 

Professor of Computing, Princess Sumaya University for Technology
Talk Title: Elevating Connectivity: UAVs, IoT, and 5G in Moving Cells and Remote Sensing
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Raed Mesleh is currently on an unpaid leave at Princess Sumaya University for Technology (PSUT) where he serves as the Dean of Scientific Research and Higher Education. He is also a professor in the Communication Engineering
department at King Abdullah II School of Engineering. He is a tenured faculty member in the Electrical Engineering Department at the German Jordanian University (GJU) and served as the Dean and the Vice Dean of the school of Electrical Engineering and Information Technology for about six years. He received his PhD in 2007 from Jacobs University in Bremen, Germany, and was a postdoctoral fellow at Jacobs University from 2007 to 2010. He was with
the Electrical Engineering Department at University of Tabuk in Saudi Arabia from 2010 to 2015, where he held the positions of department chair and the director of research excellence and intellectual property units at the deanship of scientific research. He has been a visiting scholar at Boston University, The University of Edinburgh, and HerriotWatt University. 

Summary:
In an era marked by rapid technological advancement, Unmanned Aerial Vehicles (UAVs) are
emerging as a transformative force, particularly in the context of moving cells and remote sensing
applications. UAV communication and their role in IoT (Internet of Things) are poised to
revolutionize our interactions with the environment.
UAVs offer unparalleled potential in a wide array of applications. In the realm of IoT, they enable
seamless connectivity by facilitating data exchange between various IoT devices. This
connectivity extends beyond smart homes, reaching precision agriculture, where UAVs play a
pivotal role in optimizing crop yields and resource utilization. Additionally, in the domain of
remote sensing, UAVs are invaluable tools for collecting high-resolution data in remote or
inaccessible areas.
To fully unlock the capabilities of UAVs in IoT and remote sensing, robust wireless connectivity
is essential. This is where 5G technology, the fifth generation of wireless communication, steps in
as a vital enabler. With its exceptional speed, ultra-low latency, and the ability to support a massive
number of device connections, 5G is poised to connect not only UAVs but also a myriad of IoT
devices, ranging from autonomous vehicles to healthcare wearables.
As we embark on this UAV-driven future, it is imperative to confront the opportunities and challenges that lie ahead. Addressing security and privacy concerns in UAV communication, ensuring equitable access to 5G technology, and fostering collaboration among academia, industry,
and policymakers will be pivotal in harnessing the transformative power of UAVs, IoT, and 5G.
The digital revolution is in full swing, and UAVs, in partnership with 5G, are at the forefront.
Together, they are shaping a world where connectivity is ubiquitous, intelligence is embedded, and the possibilities are limitless. It's a future that holds immense promise and one that we should eagerly embrace and actively participate in.