BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Northeastern University College of Engineering - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Northeastern University College of Engineering
X-ORIGINAL-URL:https://coe.northeastern.edu
X-WR-CALDESC:Events for Northeastern University College of Engineering
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20220313T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20221106T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20230312T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20231105T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20240310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20241103T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230808T100000
DTEND;TZID=America/New_York:20230808T110000
DTSTAMP:20260507T202450
CREATED:20230721T142808Z
LAST-MODIFIED:20230721T142808Z
UID:37565-1691488800-1691492400@coe.northeastern.edu
SUMMARY:Yukui Luo's PhD Dissertation Defense
DESCRIPTION:Title:\nSecuring FPGA as a Shared Cloud-Computing Resource: Threats and Mitigations \nCommittee Members:\nProf. Xiaolin Xu (Advisor)\nProf. Yunsi Fei\nProf. Xue Lin \nAbstract:\nWith the widespread adoption of cloud computing\, the demand for programmable hardware acceleration devices\, such as field-programmable gate arrays (FPGA)\, has increased. These devices benefit the growth of efficient hardware accelerators\, making cloud computing possible for a wide range of research and commercial projects\, including genetic engineering\, intensive online secure trading\, the Artificial Intelligence (AI) interface\, etc. To further improve the performance of FPGA-enabled cloud computing\, one promising technology is to virtualize the hardware resources of an FPGA device\, which allows multiple users to share the same FPGA. This solution can provide on-demand FPGA instances\, significantly improving the hardware utilization and energy efficiency of the cloud FPGA. However\, due to the hardware reconfigurability of FPGA\, current virtualization technologies used for multi-tenant CPU and GPU instances are incompatible with multi-tenant FPGA. \nWe aim to enhance the security of multi-tenant FPGA by defining the threat model and evaluating security concerns from the perspectives of confidentiality\, data integrity\, and availability. As part of this goal\, we constructed multi-tenant FPGA prototypes and demonstrated potential attacks. These attacks serve as preliminary steps toward developing a secure multi-tenant FPGA virtualization system. This system involves hardware and software co-design\, which extends the multi-tenant isolation from software to hardware\, ultimately resulting in a secure FPGA shared cloud computing service.
URL:https://coe.northeastern.edu/event/yukui-luos-phd-dissertation-defense/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230808T103000
DTEND;TZID=America/New_York:20230808T113000
DTSTAMP:20260507T202450
CREATED:20230802T192515Z
LAST-MODIFIED:20230802T192515Z
UID:37694-1691490600-1691494200@coe.northeastern.edu
SUMMARY:Dinesh Murugan MS Thesis Defense
DESCRIPTION:Title: Advances in Modelling\, Control\, and Perception for Soft Robotics and Autonomous Vehicle Systems \nLocation on Campus: Snell Room \nCommittee Members:\nAdvisor: Prof. Milad Siami\nProf. Bahram Shafai\nProf. Rozhin Hajian – University of Massachusetts\, Lowell \nAbstract:\nIn this research project\, we investigate the distributed consensus and vehicle platoons control problem. We first investigate the performance deterioration of commensurate fractional-order consensus networks under exogenous stochastic disturbances. We formulate fractional-order differential equations for the network dynamics using Caputo derivatives and the Laplace transform\, and employ the H_2 norm of the dynamical system as a performance measure. By developing a graph-theoretic methodology\, we relate the structural specifications of the underlying graphs to the performance measure and explicitly quantify fundamental limits on the best achievable levels of performance in fractional-order consensus networks. We also establish new connections between the sparsity of the network and the performance measure\, characterizing fundamental tradeoffs that reveal the interplay between the two. Finally\, we provide numerical illustrations to verify our theoretical results\, which could help in the design of robust fractional-order control systems in the presence of disturbances. \nAdditionally\, the study examines the real-time application of the theoretical advancements on Quanser’s Qcars\, a scaled model vehicle used for academic purposes. The findings are highly relevant to the design and implementation of large-scale consensus networks and autonomous vehicle platoons\, as they emphasize the importance of balancing network density and update cycle speed for optimal performance. \nTo extend the research’s findings to viscoelastic based networks\, the interaction between agents is modeled as a fractional-order system.
URL:https://coe.northeastern.edu/event/dinesh-murugan-ms-thesis-defense/
END:VEVENT
END:VCALENDAR