detection · segmentation · tracking · optimization · edge AI · cloud AI
I work where computer vision models meet production: architectures, custom layers and heads,
tracking pipelines, quantization, and deployment on constrained hardware.
I contribute performance improvements, bug fixes, and hardware support to widely used computer vision libraries. Recent work includes extending Hailo support across seven YOLO tasks, fixing RKNN INT8 exports that produced zero detections, making an RF-DETR DataLoader up to 1.67× faster, and reducing Hungarian matcher time by up to 77%.
| Merged PRs | |
|---|---|
| ultralytics/ultralytics | 103 |
| roboflow/rf-detr | 48 |
| roboflow/trackers | 12 |
| roboflow/supervision | 2 |
🏷️ My contributions have been credited by name in 36 upstream releases.
🟣 Ultralytics YOLO — 7 highlights
Extended Ultralytics' Hailo backend from detection-only to seven tasks across the complete
.pt → ONNX → INT8 → HEF export path.
#25254 ·
#25259 ·
#25276 ·
#25280 ·
#25283 ·
#25348
Fixed RKNN INT8 exports across detection, segmentation, pose, and OBB that produced valid files but no detections. #25524
Made channels-last the automatic default for native PyTorch inference on x86 CPUs, improving median throughput by 18.43% for YOLO26n and 14.09% for YOLO11n. #25983
Fixed dataset fraction sampling that selected images from a single class, raising YOLO11n-cls
top-1 accuracy from 9.89% to 87.64% in the validation run.
#25968
Restored ByteTrack's low-confidence recovery step, which was unreachable under the default configuration and discarded detections in the 0.1–0.25 confidence range. #25034
Removed per-object GPU stalls from result processing, making Results.plot() 7.55× faster and
cutting segmentation-validator synchronizations from 876 to 2.
#25230 ·
#25853
Found train/test contamination affecting 27.9% of KITTI depth training images; validation found no statistically significant accuracy impact. #25650
🟠 RF-DETR — 6 highlights
Reduced the DataLoader handoff from 114 objects to 9 per batch, improving throughput by up to 1.67× and preventing file-descriptor crashes at high worker counts. #1399
Rewrote the evaluation confidence sweep from O(T·N) to O(N log N), making it 7.1–7.8× faster at
COCO scale with identical macro_f1 results.
#1339
Reduced Hungarian matcher time and peak CUDA memory by up to 77% by padding to the largest target count in each batch instead of the total number of targets. #1297
Corrected the encoder mask-loss computation across all released segmentation models and added
the missing tests for SegmentationHead.
#1331
Aligned ONNX/TFLite decoding with PyTorch, restoring 30 detections dropped across 26 of 200 COCO validation images. #1320
Preserved callback state after resuming training, preventing diverged runs from overwriting good checkpoints with NaN weights. #1318
🔵 Trackers — 4 highlights
Fixed a float-equality bug that degraded steady-frame-rate tracking by as much as 4.86 HOTA and 236 extra ID switches on DanceTrack. #531
Fixed the CLI, demo, and benchmark paths silently assuming 30 fps—a default that was wrong for every SportsMOT and DanceTrack sequence supported by the benchmark. #569
Fixed OC-SORT omitting low-confidence inputs from its return value, restoring one output row per detection. #566
Reduced a Kalman filter noise-calculation hot path by 64.93% while preserving bit-identical output. #572
Frameworks & runtimes
Models & methods YOLO (v8 / 11 / 26) · RF-DETR · DINOv2 · SAM · deformable DETR · Kalman filtering and multi-object tracking
Silicon & platforms Hailo · MemryX MXA · RKNN · Cloud TPU · Google Cloud



