Area of research
Electrical and Electronic Engineering · Artificial Intelligence
Research interest
Research interests include Ferroelectric and Negative Capacitance Devices, Advanced Memory and Neural Computing, Neural Networks and Reservoir Computing, and Parallel Computing and Optimization Techniques.
PhotoHDC: An Electro-Photonic Accelerator for Hyperdimensional Computing
Debias Once for All: A Data-Centric Strategy for Fair Machine Learning
Contextual Fusion Strategies for Multimodal GNN-Based Reasoning: Performance and Computational Trade-Offs
Opto-Aligner: Optical Near-Sensor Architecture for Accelerating DNA Pre-Alignment Filtering
HEAL: Brain-Inspired
<u>H</u>
yperdimensional
<u>E</u>
fficient
<u>A</u>
ctive
<u>L</u>
earning
Vision language model for interpretable and fine-grained detection of safety compliance in diverse workplaces
A Homogeneous FeFET-Based Time-Domain Compute-in-Memory Fabric for Matrix-Vector Multiplication and Associative Search
TaskCLIP: Extend Large Vision-Language Model for Task Oriented Object Detection
A Scalable 2T-1FeFET-Based Content Addressable Memory Design for Energy Efficient Data Search
Neuro-Photonix: Enabling Near-Sensor Neuro-Symbolic AI Computing on Silicon Photonics Substrate
CyberRL: Brain-Inspired Reinforcement Learning for Efficient Network Intrusion Detection
Tri-HD: Energy-Efficient On-Chip Learning With In-Memory Hyperdimensional Computing
Enabling Efficient and Interpretable Cybersecurity Reasoning Through Hyperdimensional Computing
White Admitted by Stanford, Black Got Rejections: Exploring Racial Stereotypes in Text-to-Image Generation from a College Admissions Lens
TriageHD: A Hyper-Dimensional Learning-to-Rank Framework for Dynamic Micro-Segmentation in Zero-Trust Network Security
Hyperdimensional Intelligent Sensing for Efficient Real-Time Audio Processing on Extreme Edge
Event-Driven Spatiotemporal Processing-In-Sensor with Phase Change Memory-based Optical Acceleration
Cognitive map formation under uncertainty via local prediction learning
LVLM_CSP: Accelerating Large Vision Language Models via Clustering, Scattering, and Pruning for Reasoning Segmentation
Configurable hyperdimensional graph representation
Robust Reasoning and Learning with Brain-Inspired Representations under Hardware-Induced Nonlinearities
DynHD: Hyperdimensional Computing Approach for Efficient Radar Spectrum Classification
Lightator: An Optical Near-Sensor Accelerator with Compressive Acquisition Enabling Versatile Image Processing
HyperSense: Hyperdimensional Intelligent Sensing for Energy‐Efficient Sparse Data Processing
Deep random forest with ferroelectric analog content addressable memory.
Advancing Hyperdimensional Computing Based on Trainable Encoding and Adaptive Training for Efficient and Accurate Learning
In-Memory Acceleration of Hyperdimensional Genome Matching on Unreliable Emerging Technologies
Intelligent Sensing Framework: Near-Sensor Machine Learning for Efficient Data Transmission
Efficient Exploration in Edge-Friendly Hyperdimensional Reinforcement Learning
Hyperdimensional Brain-Inspired Learning for Phoneme Recognition With Large-Scale Inferior Colliculus Neural Activities.
CPS: Small: Advanced Hyperdimensional and Symbolic Knowledge Transfer for Cyber-Physical Systems
UKRI/BBSRC-NSF/BIO: Interpretable and Noise-Robust Machine Learning for Neurophysiology
CPS: Small: Brain-Inspired Memorization and Attention for Intelligent Sensing
Neurally-Inspired Integration of Communication and Cognitive Computation in Hyperspace
Hyperdimensional Neural Computation for Real-Time Cognitive Learning