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.
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.
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.
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.
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.
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.
Name: Joann Chen Chair: Prof. Zhou Li Date: May 28, 2024 Time: 11:00 AM Location: EH 5204 Committee: Prof. Yanning Shen, Prof. Gene Tsudik Title: Differential Privacy for Non-standard Settings Abstract: […]
Name: Trier Mortlock Chair: Prof. Mohammad Al Faruque Date: May 31, 2024 Time: 2 PM Location: ISEB 1200 Committee: Prof. Faryar Jabbari, Prof. Pramod Khargonekar Title: Multi-Sensor Data Fusion and […]
Name: Amir Hosein Afandizadeh Zargari Chair: Prof. Fadi Kurdahi Date: June 5, 2024 Time: 11 AM Location: EH 3206 Committee: Prof. Peter Tseng, Prof. Amir Rahmani Title: Advanced Machine Learning […]
Name: Bo Tsai Chair: Prof. Kwei-Jay Lin Date: June 6, 2024 Time: 8:30 AM Location: Virtual/Zoom Committee: Prof. Rainer Doemer, Prof. Yasser Shoukry Title: Object-Oriented Visual Localization in Urban Mobile-Edge […]
Name: Mohanad Odema Chair: Prof. Mohammad Abdullah Al Faruque Date: August 9, 2024 Time: 2:30 PM Location: EH 2430 Committee: Prof. Marco Levorato, Prof. Hyouk Jun Kwon Title: Hardware/Software Co-design […]
DATE/TIME: Thursday, October 17th, 3:00pm
SPEAKER: Nika Mansouri Ghiasi, ETH Zürich
The exponential growth of genomic data poses unprecedented challenges in genomics and metagenomic applications. These applications suffer from significant data movement overheads from the storage system. To fundamentally address these overheads, we make a case for storage-centric computing.
