Professional profile
MD Rafiul Islam
Machine Learning Engineer
- Specialty
- CV & Edge AI
- Location
- Dhaka, Bangladesh
- Focus
- Production systems
- Status
- Available
RI · ML · 2026PORTFOLIO
Available for AI/ML & Computer Vision opportunities
Hello, I’m
MD Rafiul Islam
Machine Learning Engineer — Computer Vision & Edge AI
I engineer production video analytics, OCR, safety, and inspection systems—connecting rigorous model development with reliable real-time deployment at the edge.
- 28
- CV/ML works
- 11
- Industry deployments
- 3
- Research papers
PythonPyTorchYOLOOpenCVTensorRTNVIDIA JetsonFastAPIDocker
MD Rafiul IslamMachine Learning EngineerDhaka, Bangladesh About
Engineering reliable vision systems for the real world
I’m a Machine Learning Engineer specializing in production Computer Vision and Edge AI. I build systems for safety, logistics, manufacturing, banking surveillance, and retail—from data and model development to tracking, decision logic, APIs, and dependable edge deployment.
Alongside industry delivery, I conduct peer-reviewed research in computational healthcare. That research discipline strengthens how I evaluate models, communicate uncertainty, and design trustworthy systems.
- 28
- CV/ML works
- 11
- Industry deployments
- 3
- Research papers
- CV + Edge AI
- Engineering focus
Projects
Featured projects
Industry engineering, internal R&D, and research in computer vision and machine learning
IndustryKDS Logistics Ltd.
Track My Container: ISO 6346 Container Recognition
Edge computer vision pipeline for reading ISO 6346 container numbers from reach stackers and side lifters using fisheye correction, YOLO-OBB detection, crop pairing, PaddleOCR, prefix correction, and check-digit validation.
- Python
- YOLO11 OBB
- PaddleOCR
- OpenCV
- NVIDIA Jetson
- +3 more
IndustryBAT Bangladesh
BAT AI Leaf SOP Checker
Multiprocess RTSP analytics system that checks six leaf-buying SOP stages: bale opening, barcode scan, moisture inspection, layer-by-layer inspection, weighing step-back, and unwanted activities.
- Python
- YOLO11
- OpenCV
- RTSP
- Multiprocessing
- +2 more
IndustryUnilever Bangladesh Ltd.
Argus Automata: Industrial Safety Video Analytics
Multi-module safety platform covering vehicle overspeed estimation, PPE compliance, forklift-worker collision risk, restricted-area intrusion, unsafe behavior, and perimeter throwing detection.
- Python
- YOLO11
- OpenCV
- Homography
- SQLite
- +2 more
IndustryNew Asia Ltd.
Bangla ANPR & Vehicle Verification
Track-centric Bangla automatic number-plate recognition using YOLO-OBB detection, vehicle association, per-track crop queues, PaddleOCR, district and category validation, confidence voting, deduplication, and API delivery.
- Python
- YOLO11 OBB
- PaddleOCR
- ByteTrack
- OpenCV
- +1 more
Experience
Production engineering & applied research
End-to-end ownership across model development, deployment, and evaluation
Machine Learning Engineer
Bondstein Technologies Ltd.Build and deploy production computer vision systems for enterprise safety, security, logistics, retail, and manufacturing workflows. Own the lifecycle from dataset and model development through RTSP processing, tracking and temporal rules, evidence generation, API integration, and NVIDIA Jetson or GPU deployment. Representative work includes ISO 6346 container-code OCR, Bangla ANPR, factory SOP and PPE monitoring, multi-camera banking surveillance, retail analytics, and industrial visual inspection.
PythonYOLO11YOLO-OBBPaddleOCROpenCVBoT-SORTByteTrackInsightFaceFAISSTensorRTNVIDIA JetsonFastAPIDockerSQLite
Technical capabilities
Production-focused AI stack
Tools and methods used across industry engineering, R&D, and research
Computer Vision
YOLO11YOLO-OBBYOLOEOpenCVObject DetectionInstance SegmentationPose EstimationPaddleOCRBangla ANPRInsightFaceFAISSByteTrackBoT-SORTMediaPipeDepth-Anything-V2
Video Analytics & Reliability
Multi-camera RTSPROI & Line-Crossing LogicTemporal VotingState MachinesEMA & HysteresisSession DeduplicationEvidence GenerationSQLite WAL QueuesRetryable SendersCamera Health & Tamper Signals
Edge AI & Deployment
NVIDIA JetsonTensorRTONNXFP16/INT8 OptimizationCUDAGStreamerDockerLinuxMulti-GPU InferenceMultiprocessingThreaded PipelinesPerformance Profiling
Deep Learning & Research
PyTorchTensorFlowCNNsVision TransformersDenseNetGRUTransfer Learningwav2vec 2.0WavLMWhisperSubject-independent EvaluationGrad-CAMLIMESHAP
Publications
Research papers
Peer-reviewed research and preprints in machine learning and AI
Journal of Voice — peer-reviewed article, accepted 8 October 2024 • 2024
Mental Health Diagnosis From Voice Data Using Convolutional Neural Networks and Vision Transformers
A hybrid CNN–Vision Transformer approach for classifying Bengali voice samples into stable and unstable mental-health categories using spectrogram representations. The study reports approximately 91% accuracy and ROC-AUC of about 0.97, with a focus on ethical data collection and research evaluation rather than clinical validation.
arXiv preprint arXiv:2501.18161 • 2025
Using Computer Vision for Skin Disease Diagnosis in Bangladesh: Enhancing Interpretability and Transparency in Deep Learning Models for Skin Cancer Classification
A skin-lesion classification study using HAM10000, a custom deep convolutional network, and established transfer-learning baselines. The work emphasizes interpretable decision support and the Bangladesh healthcare context. This item is a preprint and is presented separately from the peer-reviewed journal article.
Contact
Let’s connect
Open to opportunities, collaborations, and interesting conversations