ผู้เขียน: Marian Verhelst

สนับสนุน
Laura Isabel Galindez Olascoaga obtained her M.Sc. degree in Systems and Control from the Technical University of Eindhoven, The Netherlands, in 2015 and her Ph.D. degree in Electrical Engineering from KU Leuven, Belgium, in 2020.   During the winter of 2018, she was a visiting scholar at the Statistical and Relational Artificial Intelligence (Star AI) lab of UCLA. She is currently a postdoctoral researcher at the Berkeley Wireless Research Center (BWRC) in UC Berkeley, where she investigates how to exploit the paradigm of Hyperdimensional Computing in applications that require intelligent feedback loops. Wannes Meert received his degrees of Master of Electrotechnical Engineering, Micro-electronics (2005), Master of Artificial Intelligence (2006) and Ph.D. in Computer Science (2011) from KU Leuven. He is a research manager in the DTAI section at KU Leuven. His work is focused on applying machine learning, artificial intelligence and anomaly detection technology to industrial application domains. Marian Verhelst is an associate professor at the MICAS laboratories of the EE Department of KU Leuven. Her research focuses on embedded machine learning, hardware accelerators, HW-algorithm co-design and low-power edge processing. Before that, she received a Ph D from KU Leuven in 2008, was a visiting scholar at the BWRC of UC Berkeley in the summer of 2005, and worked as a research scientist at Intel Labs, Hillsboro OR from 2008 till 2011. Marian is a member of the DATE and ISSCC executive committees, is TPC co-chair of AICAS2020 and tiny ML2020, and TPC member DATE and ESSCIRC. Marian is an SSCS Distinguished Lecturer, was a member of the Young Academy of Belgium, an associate editor for TVLSI, TCAS-II and JSSC and a member of the STEM advisory committee to the Flemish Government. Marian currently holds a prestigious ERC Starting Grant from the European Union and was the laureate of the Royal Academy of Belgium in 2016.​




6 หนังสืออิเล็กทรอนิกส์โดย Marian Verhelst

Venkata Rajesh Pamula & Chris Van Hoof: Analog-and-Algorithm-Assisted Ultra-low Power Biosignal Acquisition Systems
This book discusses the design and implementation aspects of ultra-low power biosignal acquisition platforms that exploit analog-assisted and algorithmic approaches for power savings.The authors desc …
PDF
อังกฤษ
€96.29
Bert Moons & Daniel Bankman: Embedded Deep Learning
This book covers algorithmic and hardware implementation techniques to enable embedded deep learning. The authors describe synergetic design approaches on the application-, algorithmic-, computer arc …
PDF
อังกฤษ
€96.29
Marian Verhelst & Wim Dehaene: Energy Scalable Radio Design
Smart energy management, both at design time and at run time, is indispensable in modern radios. It requires a careful trade-off between the system’s performance, and its power consumption. Moreover, …
PDF
อังกฤษ
€149.79
Laura Isabel Galindez Olascoaga & Wannes Meert: Hardware-Aware Probabilistic Machine Learning Models
This book proposes probabilistic machine learning models that represent the hardware properties of the device hosting them. These models can be used to evaluate the impact that a specific device conf …
PDF
อังกฤษ
€64.19
Nimish Shah & Wannes Meert: Efficient Execution of Irregular Dataflow Graphs
This book focuses on the acceleration of emerging irregular sparse workloads, posed by novel artificial intelligent (AI) models and sparse linear algebra. Specifically, the book outlines several co-o …
PDF
อังกฤษ
€85.59
Vikram Jain & Marian Verhelst: Towards Heterogeneous Multi-core Systems-on-Chip for Edge Machine Learning
This book explores and motivates the need for building homogeneous and heterogeneous multi-core systems for machine learning to enable flexibility and energy-efficiency. Coverage focuses on a key asp …
PDF
อังกฤษ
€117.69