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Search Results - electrical+%3e+computing+hardware
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Accurate Compute-In-Memory Accelerator With Multi-Level Analog Weight Storage (Case No. 2026-169)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a high-density, multi-level CTT-based compute-in-memory architecture that enables precise, energy-efficient analog computation directly within memory for high-performance computing. Background: Conventional digital processors for artificial intelligence...
Published: 6/3/2026
|
Updated: 6/3/2026
|
Inventor(s):
Sudhakar Pamarti
,
Mohammadreza Zeinali
,
Samyak Chakrabarty
,
Vinod Kurian Jacob
Keywords(s):
Advanced Computing / AI
,
advanced computing methods
,
AI
,
AI hardware
,
analog computing
,
Artificial Intelligence
,
artificial intelligence accelerators
,
Artificial Neural Network
,
CMOS
,
compute-in-memory
,
edge computing
,
Energy Efficiency
,
high-performance computing
,
Memory
,
parallel computing
,
Transistor
,
transistors
Category(s):
Software & Algorithms > Artificial Intelligence & Machine Learning
,
Electrical
,
Electrical > Computing Hardware
,
Electrical > Electronics & Semiconductors
,
Electrical > Electronics & Semiconductors > Circuits
,
Electrical > Electronics & Semiconductors > Memory
Calibration of Analog Multi-Bit Storage Elements Without Off-Chip Components (Case No. 2026-167)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a scalable, energy-efficient technique for high-precision threshold voltage tuning and verification in charge trap transistor arrays using low-overhead on-chip measurement. Background: Charge trap transistors (CTTs) enable non-volatile analog multi-bit...
Published: 6/3/2026
|
Updated: 6/3/2026
|
Inventor(s):
Sudhakar Pamarti
,
Mohammadreza Zeinali
Keywords(s):
analog computing
,
CMOS
,
compute-in-memory
,
Electrical
,
Electrical Engineering
,
Integrated Circuit
,
large-area arrays
,
low latency computing
,
Memory
,
Network Analysis (Electrical Circuits)
,
Neuromorphic circuits
,
programming
,
pulsed load modulation
,
scalable fabrication
,
soft electrical circuits
Category(s):
Electrical
,
Electrical > Computing Hardware
,
Energy & Environment
,
Energy & Environment > Energy Efficiency
,
Electrical > Electronics & Semiconductors > Circuits
,
Electrical > Electronics & Semiconductors
1-Micron Optical-To-Microwave Frequency Division System for Low Phase Noise Microwave Generation (Case No. 2026-042)
Summary: UCLA researchers in the Department of Electrical & Computer Engineering have designed an integrated, chip-scale architecture that generates ultra-pure, highly tunable microwave signals via microcombs. Background: Ultra-low phase noise and highly tunable microwave signals are critical for next-generation technological infrastructure....
Published: 5/29/2026
|
Updated: 5/29/2026
|
Inventor(s):
Chee Wei Wong
,
Dong IL Lee
,
Wenzheng Liu
Keywords(s):
Extremely High Frequency
,
Frequency conversion
,
frequency modulation
,
high frequency electronics
,
high-frequency signals
,
Microwave
,
Microwave Base Transceiver Station
,
Microwave Microwave Video Scaler
,
Monolithic Microwave Integrated Circuit
,
Radio Frequency
,
Radio Frequency Coil Human Factors And Ergonomics
,
Radio Frequency Sine Wave
,
radiofrequency (RF) coil
,
Radiofrequency Ablation
,
radiofrequency signaling
,
RFID (Radio Frequency Identification)
Category(s):
Electrical
,
Electrical > Signal Processing
,
Electrical > Quantum Computing
,
Electrical > Computing Hardware
,
Electrical > Electronics & Semiconductors
Superconducting Diodes for Qubit Readout (Case No. 2026-079)
Summary: UCLA researchers led by Professor Pri Narang have developed a fully superconducting, on-chip readout architecture that improves signal fidelity and limits backpropagation in quantum processors Background: Superconducting quantum processors can perform complex calculations orders of magnitude quicker than classical computers. Current superconducting...
Published: 3/3/2026
|
Updated: 2/24/2026
|
Inventor(s):
Prineha Narang
,
Arpit Arora
,
Nicolas Dirnegger
Keywords(s):
Category(s):
Electrical
,
Electrical > Quantum Computing
,
Electrical > Signal Processing
,
Electrical > Sensors
,
Electrical > Instrumentation
,
Electrical > Computing Hardware
,
Materials
,
Materials > Fabrication Technologies
,
Materials > Functional Materials
,
Materials > Semiconducting Materials
Superconducting Diodes for Qubit-Qubit Coupling (Case No. 2026-078)
Summary: UCLA researchers in the Department of Electrical Engineering have developed a superconducting diode-based nonreciprocal interconnect that enables low-loss, directional microwave signal routing between qubits, chips, and cryogenic modules while preserving quantum coherence and suppressing back-propagating noise. Background: Scalable superconducting...
Published: 3/3/2026
|
Updated: 2/24/2026
|
Inventor(s):
Prineha Narang
,
Nicolas Dirnegger
,
Arpit Arora
Keywords(s):
Communication & Networking
,
cryogenic cooling
,
device architectures
,
Diode
,
Electrical Impedance
,
entanglement
,
Microwave
,
Network On A Chip
,
quantum communication
,
Quantum Computer
,
quantum network
,
quantum processing
,
quantum processor
,
scalable communication
,
transmission enhancement
Category(s):
Electrical
,
Electrical > Quantum Computing
,
Electrical > Computing Hardware
,
Energy & Environment > Energy Transmission
,
Electrical > Signal Processing
Through-Glass Vias (TGVS) Thermal Management for Advanced 3DIC Packaging (Case No. 2026-156)
Summary: UCLA researchers in the Department of Mechanical and Aerospace Engineering have developed a novel approach to enhance the thermal performance of through-glass vias for advanced semiconductor packaging. Background: Advanced semiconductor systems rely on 3D integrated circuits (3DICs) to meet rising demands for higher performance, reduced...
Published: 3/5/2026
|
Updated: 2/20/2026
|
Inventor(s):
Tiwei Wei
,
Ye Yang
Keywords(s):
3D integrated circuits (3DIC)
,
advanced semiconductor packaging
,
artificial intelligence accelerators
,
copper electroplating
,
cubic-octahedral diamond
,
diamond composites
,
diamond metallization
,
Doping (Semiconductor)
,
Electronics & Semiconductors
,
ferromagnetic semiconductor
,
functional/composite materials
,
glass interposers
,
heat dissipation
,
high-performance computing
,
Microelectronics Semiconductor Device Fabrication
,
microfabrication
,
Organic Semiconductor
,
physical vapor deposition (PVD)
,
real-time thermal management
,
Semiconductor
,
semiconductor chip foundries
,
Semiconductor Device
,
Semiconductor Device Fabrication
,
Semiconductor Ohmic Contact
,
Semiconductor Risk Assessment
,
Semiconductor Sapphire
,
Semiconductors
,
silicon interposers
,
thermal bottleneck
,
thermal management
,
thermal management systems
,
through-glass vias (TGVs)
,
zzsemiconducting materials
Category(s):
Chemical
,
Chemical > Industrial & Bulk Chemicals
,
Chemical > Synthesis
,
Chemical > Chemical Processing & Manufacturing
,
Electrical
,
Electrical > Computing Hardware
,
Electrical > Electronics & Semiconductors
,
Materials
,
Materials > Metals
,
Materials > Semiconducting Materials
,
Materials > Functional Materials
,
Materials > Fabrication Technologies
,
Materials > Composite Materials
,
Software & Algorithms > Communication & Networking
Multi-Level Scheduling and Partitioning of Reconfigurable Processor Arrays (Case No. 2026-011) Circular Elevator Style Network-on-Chip (Case No. 2026-012) and Pattern Compilation for Runtime Reconfigurable Arrays (Case No. 2026-013)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a high-speed runtime reconfigurable processor array (RTRA) that enables on-chip scheduling and rapid multi-program execution with unprecedented energy and area efficiency for dynamic computing workloads. Background: Dynamic digital signal processing...
Published: 12/11/2025
|
Updated: 12/11/2025
|
Inventor(s):
Dejan Markovic
,
Hong Seok Lee
,
Chenkai Ling
Keywords(s):
computational efficiency
,
computational efficiency and analysis
,
edge computing
,
energy-efficient
,
Hardware
,
high speed
,
large-area arrays
,
low latency computing
,
low-power architecture
,
Microarray
,
Microprocessor
,
processor design
,
programming
,
scalable manufacturing
,
System On A Chip
Category(s):
Electrical > Signal Processing
,
Electrical
,
Electrical > Electronics & Semiconductors
,
Software & Algorithms
,
Electrical > Computing Hardware
CDMA MIMO Readout Networks for Semiconductor-Based Compact 2-Dimensional Qubit Array (Case No. 2025-153)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a novel CDMA-MIMO qubit readout network that enables scalable, high-fidelity measurement of two-dimensional semiconductor qubit arrays for fault-tolerant quantum computing. Background: Qubit arrays form the foundation of complex quantum computations...
Published: 12/12/2025
|
Updated: 12/10/2025
|
Inventor(s):
Mau-Chung Chang
,
Jhih-Wei Chen
Keywords(s):
computational efficiency
,
computational efficiency and analysis
,
Electrical
,
Electrical Engineering
,
Electronics & Semiconductors
,
large-area arrays
,
quantum communication
,
Quantum Computer
,
quantum error correction (QEC)
,
quantum network
,
quantum processing
,
quantum processor
,
Semiconductor
,
Semiconductor Device
,
Semiconductors
Category(s):
Electrical
,
Electrical > Computing Hardware
,
Electrical > Electronics & Semiconductors
,
Electrical > Quantum Computing
,
Software & Algorithms > Communication & Networking
,
Software & Algorithms
Monitoring Structural Health Using Diffractive Optical Processors (Case No. 2025-201)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a novel structural health monitoring system that is highly accurate and cost effective, addressing limitations in current infrastructure and civil health monitoring and a rise in public safety concerns. Background: The need for structural health monitoring...
Published: 12/5/2025
|
Updated: 12/5/2025
|
Inventor(s):
Aydogan Ozcan
,
Ertugrul Taciroglu
,
Yuntian Wang
,
Yuhang Li
Keywords(s):
3D structures
,
Adaptive Optics
,
AI-generated images and content
,
all-optical diffractive computing
,
all-optical transformation
,
analog computing
,
analog optical computing
,
Analogue Electronics
,
Artifical Intelligence (Machine Learning, Data Mining)
,
Artificial Intelligence
,
artificial intelligence algorithms
,
artificial intelligence augmentation
,
artificial intelligence/machine learning models
,
artificial-intelligent materials
,
civil engineering
,
civil infrastructure
,
civil monitoring
,
computational imaging
,
computational imaging task
,
Construction
,
deep diffractive network
,
Diffraction
,
diffractive design
,
diffractive image reconstruction
,
diffractive network
,
diffractive processor
,
diffractive surface
,
digital image reconstruction
,
electromagnetic spectrum
,
Electro-Optics
,
Image Analysis
,
Image Processing
,
Image Resolution
,
image restoration
,
image signal processing
,
Imaging
,
Infrastructure
,
Lens (Optics)
,
linear optics
,
Nanostructure
,
optical processor
,
optically-guided structural monitoring
,
Optics
,
passive light-matter interactions
,
security imaging
,
Signal Reconstruction
,
Structural health monitoring
,
structural health monitoring (SHM)
,
structure monitoring
,
Structures
Category(s):
Electrical
,
Electrical > Signal Processing
,
Electrical > Imaging
,
Materials
,
Materials > Construction Materials
,
Electrical > Visual Computing
,
Electrical > Computing Hardware
,
Electrical > Instrumentation
,
Energy & Environment
,
Energy & Environment > Energy Efficiency
,
Software & Algorithms
,
Software & Algorithms > Artificial Intelligence & Machine Learning
,
Software & Algorithms > Image Processing
,
Software & Algorithms > Programs
Prototype Software for Neuron-Centric Memory Architecture in AI (Case Nos. 2025-327/328)
Summary: Researchers at UCLA’s Department of Integrative Biology & Physiology and Neurobiology have pioneered the first prototype of a novel, neuron-centric AI architecture featuring intracellular memory and adaptive computation capabilities, designed to enhance deep learning performance and efficiency. Background: Deep learning leverages...
Published: 12/10/2025
|
Updated: 10/23/2025
|
Inventor(s):
Alain Glanzman
,
David Glanzman
Keywords(s):
Artifical Intelligence (Machine Learning, Data Mining)
,
Artificial Intelligence
,
artificial intelligence algorithms
,
artificial intelligence augmentation
,
artificial intelligence/machine learning models
,
artificial intelligence-generated content
,
Artificial Neural Network
,
Artificial Neural Network Artificial Neuron
,
artificial-intelligent materials
,
generative artificial intelligence
,
Medical artificial intelligence (AI)
,
Neuron
,
neurons
,
Software
,
Software & Algorithms
,
Software Development Tools
,
Software-enabled learning
Category(s):
Software & Algorithms
,
Software & Algorithms > AI Algorithms
,
Software & Algorithms > Artificial Intelligence & Machine Learning
,
Electrical
,
Electrical > Computing Hardware
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