Self-Awareness in Cyber-Physical Systems 2024

DATE: February 22-23, 2024
LOCATION: San Diego State University (SDSU)
Inspired by biological examples, self-awareness has become a hot research topic in a variety of disciplines and its applicability has been explored in various application domains. The main purpose of this workshop is to strengthen and extend the community and to try to develop a shared and communal understanding of the main concepts underlying self-awareness with respect to CPS.

Hardware for ML and ML for Hardware

DATE/TIME: Monday, April 1st, 11:00am
SPEAKER: Prof. Aman Arora, Arizona State University
This talk delves into the exciting intersection of hardware design and machine learning, showcasing how these fields are mutually benefiting each other. The presentation will feature cutting-edge research projects that exemplify this dynamic.

Fairness-Aware learning over Graphs

DATE/TIME: Tuesday, April 2nd, 12:00pm
SPEAKER: Oyku Deniz Kose
While graph-based ML models nicely integrate the nodal data with the connectivity, they also inherit potential unfairness. Using such ML models may therefore result in inevitable unfair results in various decision- and policy-making in the related applications. While fairness and explainability have attracted increasing attention in responsible ML, they are mostly under-explored in the graph domain.

Towards Self-Sustainable Wearable IoT Devices for Reliable Mobile Health Applications

DATE/TIME: Thursday, April 25th, 10:00am
SPEAKER: Prof. Ganapati Bhat, Washington State University
Wearable internet of things (IoT) devices are the next big evolution in computing systems. Wearable sensors and IoT devices, along with smart home technologies, have the potential to transform healthcare by enabling cost-effective, reliable, continuous, and data-driven monitoring of users in a free-living environment. Despite the impressive potential of wearable technology, widespread adoption of wearable devices has been limited due to several technology and adaptation challenges.

Agile Hardware Specialization

DATE/TIME: Wednesday, May 1st, 11:00am
SPEAKER: Prof. Yun Eric Liang, Peking University
As Moore’s law is approaching to the end, designing specialized hardware accelerator along with the software that map the applications onto the specialized hardware is a promising solution. However, the hardware is very difficult to design and optimize due to the low-level programming and huge design space.

Dissecting the Software Supply Chain of Modern Industrial Control Systems

DATE/TIME: Thursday, May 23rd, 10:00am
SPEAKER: Prof. Michail (Mihalis) Maniatakos, NYU Abu Dhabi
In this seminar, we will shed light to the security landscape of modern ICS, dissecting firmware from the dominant vendors and motivating the need of employing appropriate vulnerability assessment tools.

Deep Latent Variable Modeling of Physiological Signals

DATE/TIME: Friday, May 24th, 9:30 am
SPEAKER: PhD Candidate Khuong An Vo
A deep latent variable model is a powerful tool for modeling complex distributions. These models assume that underlying structures, but unobserved, are present within the data. In this dissertation, we explore high-dimensional problems related to physiological monitoring using latent variable models.