SegAgent-AI
Dockerized AI platform for industrial defect segmentation, severity analysis, HTML reporting, and cloud deployment.
FastAPI · Streamlit · PyTorch · Docker · AzureCurriculum Vitae
AI Researcher & Machine Learning Engineer
Ph.D. candidate specializing in computer vision, deep learning, explainable AI, medical imaging, industrial inspection, and time-series forecasting for practical AI systems.
Industry-Focused Profile
I build intelligent, interpretable, and efficient AI systems that combine deep learning, computer vision, time-series forecasting, and signal processing to transform data into practical insight and deployable workflows.
My work connects research-oriented model development with engineering implementation, including segmentation networks, Transformer-based architectures, explainability pipelines, API deployment, Dockerized applications, and reproducible AI systems.
Career Direction
Target Roles
Computer Vision Engineer
Machine Learning Engineer
Deep Learning Engineer
Data Scientist
AI Research Scientist
Medical AI Researcher
Applied AI Engineer
Technical Strengths
Technical Skill Matrix
Computer Vision
Segmentation, medical imaging, surface defect inspection, crack detection, wildfire segmentation, object tracking.
OpenCVmmsegmentationTorchVisionGrad-CAM
Deep Learning
CNNs, UNet, UNet++, DeepLabV3+, SegFormer, Vision Transformer, Swin Transformer, CNN–Transformer hybrids, Mamba.
PyTorchTensorFlowKerasHuggingFace
Forecasting & Data Science
LSTM, GRU, FEDformer, Informer, CEEMDAN, environmental forecasting, PM2.5, hydrology, model evaluation.
pandasscikit-learnXGBoostOptuna
Deployment & Engineering
FastAPI, Flask, MySQL, JSON APIs, shell scripting, scheduled automation, Docker, Linux, Git, CUDA workflows.
FastAPIDockerMySQLLinux
Applied Work
Featured Engineering Projects
Brief CV-style highlights. Full project details, images, and repositories are available on the Projects page.
LACTNet Surface Defect Segmentation
Label-Aware CNN–Transformer architecture for pixel-level industrial defect segmentation and inspection workflows.
CNN · Swin Transformer · Segmentation · XAIETT & Carina Segmentation
UNet-based segmentation system for chest radiographs and automated airway placement assessment.
PyTorch · UNet · Chest X-ray · Medical ImagingCropNet Forecasting System
End-to-end evapotranspiration and rainfall forecasting pipeline with automated APIs, MySQL storage, and scheduled updates.
LSTM · Flask · MySQL · API · AutomationExperience
Professional Timeline
2022–Present
Ph.D. Researcher / Research Assistant
Explainable AI Lab, National Yunlin University of Science and Technology, Taiwan
- Designed CNN–Transformer architectures for industrial defect segmentation and visual inspection.
- Developed medical imaging, explainable AI, and systematic review research in deep learning and Transformers.
- Published first-author work in applied AI, computer vision, forecasting, and signal analysis journals.
2021–2022
Machine Learning Engineer
University of Hawaii / CropNet Project · Remote
- Built forecasting pipelines for evapotranspiration and rainfall prediction over 1-, 3-, and 7-day horizons.
- Integrated API extraction, MySQL storage, LSTM forecasting models, and Flask JSON endpoints.
2024
Signal Processing Developer
statigen.ai · USA / Remote
- Built a machine learning pipeline for multi-level blood concentration classification from sensor signals.
- Implemented preprocessing, feature extraction, visualization, classification, Optuna optimization, and reporting.
2019–2022
AI/ML Developer and Course Instructor
Clocklearn / Shahroud University of Medical Sciences
- Designed and recorded a Persian-language machine learning course from preprocessing to neural networks.
- Developed healthcare-oriented AI prototypes using ultrasound signals, HOG features, and supervised classifiers.
Education
Education
Ph.D. in Information Management
National Yunlin University of Science and Technology, Taiwan · Expected Sep. 2026
GPA: 4.00/4.00 · Research focus: computer vision, defect segmentation, CNN–Transformer architectures, and explainable AI.M.Sc. in Artificial Intelligence
Shahrood University of Technology, Iran · 2013–2016
GPA: 4.00/4.00 · Ranked 2nd in Artificial Intelligence cohort.B.Sc. in Software Engineering
Shahrood University of Technology, Iran · 2008–2012
Ranked 2nd in Software Engineering cohort.Recognition
Honors
- University scholarship for outstanding doctoral students — YunTech.
- NSTC doctoral research award.
- Ranked 2nd in M.Sc. Artificial Intelligence cohort.
- Ranked 2nd in B.Sc. Software Engineering cohort.
Research Credibility
Research Impact
800+Google Scholar Citations
12h-index
13i10-index
19+Publications
Learning & Certifications
Selected Certificates
Generative AI Engineering with LLMs
Computer Vision Specialization
Transformer Models and BERT
Introduction to Large Language Models
Machine Learning — Stanford / DeepLearning.AI
Developing AI Applications with Python and Flask
Getting Started with Git and GitHub
Python for Data Science, AI & Development
View Credentials Gallery
Download the complete CV
The PDF version includes the full publication list, references, certificates, and detailed academic service.