Research
My past research focuses on brain-computer interfaces (BCIs) with wide of applications below.
Area 1: Robust adaptive control algorithms for treating brain diseases. [Supported by Pilot Award]
- Designing and Validating of a Robust and Adaptive Neuromodulation Algorithm for Closed-Loop Control of Brain States. (Controller.png)
- Robust Adaptive Deep Brain Stimulation Control of Non-Stationary Cortex-Basal Ganglia-Thalamus Network Models in Parkinson's Disease (PD.png)
- Predictive Neuromodulation of Cingulo-Frontal Neural Dynamics in Major Depressive Disorder using a Brain-Computer Interface System: A Simulation Study (MDD.png)
Area 2: Toward consistent neural decoding
- Model-Agnostic Meta-Learning Framework for EEG-Based Emotion Recognition (MAML.png)
- SPINT: Spatial Permutation-Invariant Neural Transformer for Consistent Intracortical Motor Decoding (SPINT.png)
- Emotion Recognition from EEG Network Connectivity Using Low-Dimensional Discriminant Analysis on Riemannian Manifolds (Riemannian.png)
Area 3: Trajectory planning for ingelligent robots
- Cross-Embodiment Robotic Manipulation Synthesis via Guided Demonstrations through CycleVAE and Human Behavior Transformer (Cross-embodiment.png)
- APEX: Ambidextrous Dual-Arm Robotic Manipulation Using Collision-Free Generative Diffusion Model (Apex.png)
- A Unified Control Framework using Diffusion Variational Autoencoder for Intercepting Flying Objects with Obstacle Avoidance (Unified.png)
- RETRO: Reactive Trajectory Optimization for Real-Time Robot Motion Planning in Dynamic Environments (Retro.png)
Area 4: Toward future hardware integreated intracranial brain-computer interfaces
- Toward Lightweight and Fast Inference Neural Decoder Design using Quantization Aware Training: A Simulation Study (Lightweight.png)
- A Co-Design of Hardware and Software Systems for Future Integrated Brain-Computer Interfaces (Co-deisgn.png)