Postdoc & Research Collaboration Fit

I am looking for postdoctoral and research scientist opportunities where robust perception, multimodal learning, spatiotemporal modeling, and reliable AI are central.

Best-Fit Research Areas

  • Computer vision for UAV-based perception
  • Multi-object tracking and temporal reasoning
  • Multimodal sensing, MultiLiDAR perception, and sensor fusion
  • Remote sensing / GeoAI under domain shift
  • Biomedical imaging / radiogenomics
  • Reliable AI and uncertainty-aware evaluation

Why I Am a Good Fit

  • Publications in UAV detection and tracking (journal + conference track record)
  • Dissertation focus on robust UAV perception and temporal modeling
  • Hands-on experience with datasets, modeling, evaluation, and end-to-end pipelines
  • Strong PyTorch/OpenCV/Linux/GPU implementation background
  • Teaching and mentoring experience in data- and systems-oriented courses

Possible Collaboration Directions

Robust UAV Perception Under Weak Signals

Tiny target detection, weak evidence integration, and robust scene understanding under motion and clutter.

Formation-Aware Swarm Tracking

Temporal association and conservative recovery strategies for dense multi-UAV settings.

Calibration-Free / Uncertainty-Aware Fusion

Reliable multimodal integration under noisy, sparse, and partially missing sensor streams.

MultiLiDAR UAV Sensing

Point-cloud accumulation, candidate clustering, and reliability-aware fusion for sparse heterogeneous LiDAR streams.

Domain-Generalized GeoAI for Climate/Agriculture

SAR-optical-weather modeling for robust generalization across geographies and seasons.

Reliable MRI / Radiogenomic AI

Translational multimodal biomedical modeling with reliability and generalization focus.