What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Electrical engineering
- Neuroscience
Kwabena Boahen mostly deals with Neuromorphic engineering, Subthreshold conduction, Electronic circuit, CMOS and Neuroscience.
His Neuromorphic engineering study contributes to a more complete understanding of Artificial intelligence.
His biological study spans a wide range of topics, including Electronic engineering, Circuit design and Very-large-scale integration.
His work carried out in the field of Electronic engineering brings together such families of science as Analogue electronics, Transistor, Computer hardware and Tree network.
His Very-large-scale integration study combines topics in areas such as Range, Ranging and Computational model.
His CMOS research incorporates elements of Pixel and Dynamic range.
His most cited work include:
- Neuromorphic Silicon Neuron Circuits (1070 citations)
- Neurogrid: A Mixed-Analog-Digital Multichip System for Large-Scale Neural Simulations (636 citations)
- Point-to-point connectivity between neuromorphic chips using address events (533 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Neuromorphic engineering, Electronic engineering, Neuroscience, Artificial intelligence and CMOS.
Neuromorphic engineering is a subfield of Artificial neural network that he tackles.
The Electronic engineering study combines topics in areas such as Analogue electronics, Electronic circuit, Computer hardware and Chip.
His work on Excitatory postsynaptic potential, Ganglion and Retinal ganglion as part of his general Neuroscience study is frequently connected to Chemistry and Population, thereby bridging the divide between different branches of science.
His research in CMOS tackles topics such as Dynamic range which are related to areas like Bandwidth.
His work deals with themes such as Transistor and Simulation, which intersect with Very-large-scale integration.
He most often published in these fields:
- Neuromorphic engineering (36.00%)
- Electronic engineering (25.60%)
- Neuroscience (22.40%)
What were the highlights of his more recent work (between 2013-2021)?
- Neuromorphic engineering (36.00%)
- Neuroscience (22.40%)
- Mathematical optimization (3.20%)
In recent papers he was focusing on the following fields of study:
Kwabena Boahen focuses on Neuromorphic engineering, Neuroscience, Mathematical optimization, Function and Analogue electronics.
Kwabena Boahen interconnects Dynamical systems theory, Control theory, Electronic circuit, Synapse and Electronic engineering in the investigation of issues within Neuromorphic engineering.
In Electronic circuit, Kwabena Boahen works on issues like Spiking neural network, which are connected to Tree, Computer hardware and Tree network.
Borrowing concepts from Physical neural network, Kwabena Boahen weaves in ideas under Electronic engineering.
His study on Cognition, Neocortex and Cortical map is often connected to Chemistry and Ventral cochlear nucleus as part of broader study in Neuroscience.
His Analogue electronics study incorporates themes from Digital electronics, Neurogrid, Artificial neural network, Very-large-scale integration and Computation.
Between 2013 and 2021, his most popular works were:
- Neurogrid: A Mixed-Analog-Digital Multichip System for Large-Scale Neural Simulations (636 citations)
- Selective modulation of cortical state during spatial attention (109 citations)
- Braindrop: A Mixed-Signal Neuromorphic Architecture With a Dynamical Systems-Based Programming Model (66 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Electrical engineering
- Neuroscience
Kwabena Boahen spends much of his time researching Neuromorphic engineering, Analogue electronics, Dynamical systems theory, Artificial neural network and Digital electronics.
His Neuromorphic engineering research includes elements of Tracking error, Control theory, Trajectory, Control theory and Robot.
His Analogue electronics research is multidisciplinary, relying on both Electronic engineering, Very-large-scale integration, Tree network and Computation.
His Dynamical systems theory study combines topics from a wide range of disciplines, such as Feature, Theoretical computer science, Silicon, Biological system and Neural engineering.
The various areas that Kwabena Boahen examines in his Artificial neural network study include Convolution, Mixed-signal integrated circuit and Computational science.
His Digital electronics research is multidisciplinary, incorporating perspectives in TrueNorth, Computer hardware and Neurogrid.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
