Prof. Megumi Kaneko and Prof. Bruno Clerckx
Tuesday, October 27, 2020, 15:45
- 17:15
KAUST
Contact Person
First Speaker: Megumi Kaneko, National Institute of Informatics, Japan. Talk Title: Resource Allocation in NOMA-Based Fog Radio Access Networks. In this talk, I will first describe the potential benefits offered by the integration of NOMA in an FRAN architecture for achieving the specific objectives of use cases envisioned in B5G, in terms of throughput, latency, reliability and energy efficiency. Second Speaker: Bruno Clerckx, Imperial College London, United Kingdom. Talk Title: Rate-Splitting Multiple Access and its Applications to Cloud-Enabled Platforms. This talk argues that to efficiently cope with the high throughput, reliability, heterogeneity of Quality-of-Service (QoS), and massive connectivity requirements of future multi-antenna wireless networks, multiple access and multiuser communication system design need to depart from the two extreme interference management strategies, namely fully treat interference as noise (as commonly used in 5G, MU-MIMO, CoMP, Massive MIMO, millimetre wave MIMO) and fully decode interference (as in NOMA).
Thursday, November 21, 2019, 12:00
- 13:00
Building 9, Level 2, Hall 1, Room 2322
I will present an overview of our activities around estimation problems for partial and fractional differential equations. I will present the methods and the algorithms we develop for the state, source and parameters estimation and illustrate the results with some simulations and real applications.
Prof. David L. Donoho, Department of Statistics, Stanford University
Tuesday, November 12, 2019, 15:00
- 16:00
Building 19, MOSTI Auditorium
Contact Person
We consider the problem of recovering a low-rank signal matrix in the presence of a general, unknown additive noise; more specifically, noise where the eigenvalues of the sample covariance matrix have a general bulk distribution. We assume given an upper bound for the rank of the assumed orthogonally invariant signal, and develop a selector for hard thresholding of singular values, which adapts to the unknown correlation structure of the noise.
Prof. David L. Donoho, Department of Statistics, Stanford University
Tuesday, November 12, 2019, 12:00
- 13:00
Building 9, Level 2, Hall 2, Room 2325
Contact Person
A variety of intriguing patterns in eigenvalues were observed and speculated about in ML conference papers. We describe the work of Vardan Papyan showing that the traditional subdisciplines, properly deployed, can offer insights about these objects that ML researchers had.
Christian Claudel, Assistant Professor, Architectural and Environmental Engineering at UT-Austin
Wednesday, September 04, 2019, 10:00
- 11:00
Building 5, Level 5, Room 5209
Flash floods are one of the most common natural disasters worldwide, causing thousands of casualties every year. The emergence of Unmanned Aerial Vehicles (UAVs) gives the possibility to monitor these events over large geographical areas. In this talk, we focus on the problem of trajectory planning for a swarm of unmanned aerial vehicles sensing flooding conditions.
Thursday, April 18, 2019, 12:00
- 13:00
B9 L2 Hall 1
We will present some new methods for source and parameters estimation for partial and fractional differential equations and illustrate the results with some simulations and real applications.
Monday, April 01, 2019, 08:00
- 18:00
Conference Center Building 19 Level 3 Hall 1
The Conference is inspired by the surging interest in smart cities and smart environmental systems worldwide. The ever-increasing capabilities of sensing, communications, and computation will be key enablers of future destinations that are designed for livability, efficiency, and affordability, all the while ensuring sustainability and environmental stewardship. The conference will feature research presentations on smart solutions for energy, transportation, urban planning, and monitoring, as well as the supporting foundational areas of networks and communications; signal processing and big data; high performance computing; and cyberphysical systems.