PLENARY SPEAKERS

Society’s Grand Challenges & the “Glocal” Opportunities for Digital & Computing Innovation

Abstract

Society’s grand challenges are multi-dimensional, complex and evolving. Global and local (“glocal”) efforts to address these and the UN’s Sustainable Development Goals (SDGs) also have to deal with disruptions caused by “chronic stressors” and/or “shocks” or extreme events, natural and/or human-caused. Significant advances in Information and Communication Technologies (ICT), data science, engineering and allied fields underpinned the rapid development of society in the last century, and these are expected to play even more important roles in addressing humanity’s grand challenges. As ICT solutions become even more ubiquitous and embedded in our everyday lives, however, important environmental, socio-cultural, ethical and legal issues have come into sharper focus. This presentation outlines some of the ICT sector’s opportunities and challenges to address society’s challenges while minimising its potentially adverse impacts. In the context of a developing country like the Philippines, we explore what these global challenges and opportunities might mean to local capabilities and actions and how local know-how and capabilities can potentially meet the needs of, and opportunities in, global markets. The key concepts are illustrated by examples in selected domains and industry sectors, including disaster and crisis management, built environment and infrastructure, transport, freight and logistics, and energy and urban systems. Congress participants and attendees will have the opportunity to engage with these issues and add to the knowledge base on how to bridge the technology and innovation gaps – from global to local and vice versa – transform lives and/or industries, and contribute towards a more sustainable and resilient future.

A scholar and scientist of global standing, he received the prestigious James Croes Medal from the American Society of Civil Engineers (ASCE), amongst other awards, and has a publications record ranked in the top 1% amongst Civil Engineering researchers worldwide (based on the Stanford-Elsevier composite citation index). Greg has previously worked at the University of California in Berkeley and the Australian national science agency, the CSIRO. He is an expert consultant to – and research collaborator with – industry, government and international institutions such as IEA and UN agencies. He received his PhD and 2 MSc degrees at Virginia Polytechnic Institute and State University (Virginia Tech) in the US, and executive leadership and management training at the Australian Institute of Company Directors and the MIT Sloan Executive Education. (Further details at: https://www.linkedin.com/in/foliente/ )

Rethinking Algorithm Design in the Post-Moore Era

Abstract

For years, we designed algorithms with the expectation that newer hardware will bring performance improvement because of Moore's Law. However, with the end of Moore's law and Dennard scaling, these expectations will no longer hold. The computing community, hence, need a paradigm shift from its "bigger (data and models) is better" mentality to something more sustainable. Computing power has always been a major bottleneck in AI and continues to increase exponentially each year and throwing more compute leads to higher cost, (i.e., millions of dollars for training AI models) and a higher carbon footprint. This is in contrast with the human brain which contains billions of neurons but requires much smaller space and energy to operate.  As we reach the end of Moore's law, we need to rethink how we design algorithms for the current hardware architectures as well influence the design of future computer architectures. This talk will discuss improvements we can do to redesign our algorithms to be more efficient. We will discuss how we can shift our algorithm design paradigm to address the memory-bandwidth bottleneck, reduce the dark silicon problem, design efficient AI models, examine the limitations of our current hardware (i.e., CPU, GPU, and TPU), and design algorithms for hardware accelerators.

Biography

Ann Franchesca Laguna is an assistant professor at De La Salle University. She received her Ph.D. in Computer Science and Engineering in at the University of Notre Dame, USA in 2022 under the Fulbright Scholarship. She received her MS degree in Electrical Engineering in 2014 under the Engineering Research and Development (ERDT) Scholarship of the Philippine Department of Science and Technology (DOST) and a BS degree in Computer Engineering from the University of the Philippines – Diliman, in 2012. She is a recipient of Outstanding Research Assistant at the Department of Computer Science and Engineering at the University of Notre Dame and has been nominated for the best paper award at DATE 2021.  She is currently the managing editor of ACM Transactions on Design Automation of Electronic Systems (TODAES). Her research interests are in hardware-software co-design of machine learning, bioinformatics, and digital signal processing applications.

Mga Mata Mula Sa Kalawakan: The ASTI-ALaM Project and The Connections of Space Science and Deep Learning 

Abstract

ASTI-ALaM is a DOST project with the goal of utilizing readily available satellite imagery in artificial intelligence- (AI-) and machine learning- (ML-) based applications for environmental monitoring, resource assessment, etc. This talk will feature the various disciplines and specializations necessary for the fruition of the project’s goals, as well as discuss how space science and technology in integrated into use cases involving deep learning.

Biography

A licensed geodetic engineer who can write scholarly papers and short stories, an employee of various academic science projects, and an artist currently involved in two comics projects - one personal and the other science-inspired..