Research & publications

A zero-shot cross-subject framework for generalizable EEG decoding on the large-scale Healthy Brain Network dataset, benchmarking a CNN baseline, a hybrid LSTM, and a Transformer-based foundation model. To adapt the Transformer for regression without catastrophic forgetting, we propose a novel progressive unfreezing strategy. The fine-tuned Transformer reaches an nRMSE of 0.9799 on unseen subjects (vs. 0.9991 for the baseline), advancing scalable, calibration-free EEG decoding for computational psychiatry and behavioral prediction.

• Brain-Computer Interfaces
• EEG
• Foundation Models

A multi-agent LLM system that resolves GitHub issues from triage through pull-request creation, combining seven layered safety controls with a baseline-aware test evaluation strategy. Work is decomposed across six specialized agents (planner, reproducer, coder, tester, failure analyst, and PR agent) coordinated by a label-based GitHub webhook state machine, with every change checked against a baseline test run before a PR is opened. Phoenix oracle-resolves 75% of a SWE-bench Lite slice with no pass-to-pass regressions, and preserves correctness on 100% of a 42-issue pilot across 14 repositories.

• Multi-Agent LLMs
• Software Engineering
• SWE-bench

A hybrid framework integrating domain-specific EEG data augmentation with a language model to improve SSVEP-based Brain-Computer Interface speller accuracy for individuals with motor disabilities. It decodes scalp-recorded EEG to identify the characters a user gazes at, tackling high EEG variability and poor generalization to unseen subjects with an end-to-end PyTorch training and evaluation pipeline.

• Brain-Computer Interfaces
• EEG
• NLP

An investigation into integrating phasor measurement with wireless power transfer systems for grid applications, supporting real-time monitoring and more reliable power-grid operation.

• Power Systems
• Phasor Measurement
• Grid