Hi, I enjoy working on computational tools to advance behavioral neuroscience research.

Some things I've worked on: ORCiD

Neural signal analysis

• eeg-feat-ext
  High-throughput pipeline for extracting cycle-level theta waveform features from human iEEG, built to support a waveform-shape control analysis which revealed HPC phase-amplitude coupling as a biomarker for memory.

Behavioral data disovery / visual

• behavioral-data-discovery
  A visualization for open-field behavior, with filtering and directional trajectory views. This analysis was complemented by OpenCV-based neural image processing CaImAn to investigate place cell encoding in rats.

Recent open-source work (in progress)

• movement Issue #873 Proposed 4 collective behavior metrics (polarization, milling, group spread, leadership) + 2 supporting pairwise metrics (egocentric angle, radial/tangent velocity) for multi-animal tracking analysis.

• movement Draft PR #875 Added compute_polarization() for collective behavior analysis, supporting both orientation polarization from body-axis keypoints and heading polarization from displacement vectors.

• movement Draft PR #945 Added a skeleton-agnostic anterior/posterior body-axis inference pipeline that uses geometry and motion to validate user-specified body-axis keypoint pairs and suggest better posterior → anterior pairs when needed.

• movement PR #948 Extended vector.py utilities to support 3D coordinate transforms (Cartesian, cylindrical, spherical), enabling future 3D polarization analysis.

Focus

• Neuronal encoding ⇄ decoding
• Signal processing · Time-series analysis · Statistical learning · Pattern recognition