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I design and ship end-to-end AI solutions β from problem definition and research to a working, optimized system running under real-world constraints. Ω
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π About Β· π Highlights Β· π§ Skill Atlas Β· π οΈ Tech Stack Β· π Snake Β· π§ 3D View Β· π Skylines Β· π Featured Work Β· π§ Strengths Β· π Stats Β· π Recent Β· π¦ Releases Β· π― Pinned Β· π Guestbook
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class ParsaKarkooti:
role = "AI Engineer"
focus = ["Computer Vision", "Deep Learning", "Video Intelligence"]
domains = ["Industrial AI", "Video Analytics", "Recommender Systems", "Multimodal AI"]
education = "B.Sc. Computer Engineering β Razi University, Kermanshah"
approach = "understand the problem β research the method β build it β make it fast"
open_to = ["AI Engineering roles", "Research collaboration", "Open source"]- π§ I work at the intersection of research and production: reading the papers, then making the thing actually run.
- π Built real systems for industrial visual inspection, real-time multi-stream video intelligence, recommendation, and multimodal search.
- β‘ Strong on the unglamorous parts β modular pipelines, VRAM-safe inference, hardware-aware deployment, real evaluation metrics.
- π― Currently publishing my project portfolio here, one carefully documented repository at a time.
π Every year since I joined β straight from GitHub, refreshed daily
Lifetime totals since 2024 Β· rebuilt daily at 03:00 UTC
gitGraph
commit id: "quiet"
branch code-context-engine
commit id: "09-22 Β· +6"
commit id: "09-23 Β· +6"
commit id: "09-25 Β· +6"
commit id: "code-context-engine Β· 19 commits this week"
checkout main
branch portfolio
commit id: "09-22 Β· +4"
commit id: "09-23 Β· +4"
commit id: "09-25 Β· +4"
commit id: "portfolio Β· 12 commits this week"
checkout main
branch ParsaVictor-github-io
commit id: "09-22 Β· +4"
commit id: "09-23 Β· +4"
commit id: "09-25 Β· +4"
commit id: "ParsaVictor-github-io Β· 11 commits this week"
checkout main
branch neuromesh
commit id: "09-22 Β· +1"
commit id: "09-23 Β· +1"
commit id: "09-25 Β· +1"
commit id: "neuromesh Β· 2 commits this week"
checkout main
commit id: "today"
An anatomical map of how my technical mind is organised β 200 paths of real neuroanatomy, recoloured to the profile palette and pulsing like a living brain.
Deep Learning
Computer Vision
Machine Learning & Data
Deployment & Practices
Built from my real contribution calendar β every tower is a day, its height is that day's commit count. Rebuilt daily by Actions.
Another angle β the same year as a solid block
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Print it β the same graph as a real 3D-printable model, built with GitHub's official gh extension install github/gh-skyline
gh skyline --user ParsaVictor --year 2026Outputs a real |
Drive it β the same graph as a drivable 3D city, courtesy of GithubCity by honzaap. Every commit grows a building. 
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I'm publishing my portfolio here one repository at a time β each with architecture, reproducible setup, real metrics and a demo. Status badges below are honest and live.
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Problem β inspection teams can't trust black-box AI on a production line. Approach β Random Forest over 33 hand-engineered CV features; every prediction traceable to a readable decision path. Result β 93.3% holdout accuracy, calibrated confidence lifts to 98.9% precision at 79% coverage.
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Problem β detecting 50 component classes on dense, populated PCBs from raw images alone. Approach β YOLOv8 baseline on 675k real annotations, plus dataset tooling and an honest diagnosis of what limits the baseline. Result β a documented reference point for what pure detection can and cannot do on PCBs.
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Problem β industrial 3D-printing scans are noisy; curve reconstruction must survive them. Approach β benchmark of 5 peer-reviewed algorithms for denoising and feature-preserving reconstruction, with a full visual story. Result β reproducible comparison with 43 tests, CI green, clear guidance on which method wins when.
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Problem β retail security needs to tell a masked robber from a customer wearing a surgical mask, in real time. Approach β pre-trained models only, no custom training required, wired into a deployable pipeline. Result β a practical, ethical-by-design concealed-face detector anyone can reproduce.
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Industrial Visual Inspection Β· Deep-learning AOI system detecting surface defects and missing components on the production line.
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Modular real-time AI over 32+ CCTV streams β face recognition, tracking, anomaly detection (14 event classes), fire/smoke and intrusion alerts, per-camera web panel.
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Temporal video understanding combining pose estimation and object tracking to flag suspicious in-store behavior.
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Content + collaborative hybrid solving the cold-start problem, evaluated with Precision@K, Hit Rate and NDCG.
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Retinal disease detection: classification and feature extraction.
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Natural-language search across a media library with face/species/food recognition and incremental embeddings, on a VRAM-safe pipeline.
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ai-project-template β a clean, reproducible starting point for CV/ML projects. Config-driven training, seeded runs, framework-free metrics, pytest suite and CI out of the box.
π Every public repo I own, sorted by field β this index grows automatically whenever I publish something new.
π€ AI & Computer Vision Β· 11 repos
| Repo | What it is | Language | Stars |
|---|---|---|---|
PPE_detection-Sentinel |
βοΈ Real-time PPE compliance monitoring for construction CCTV β person-grounded two-stage pipeline (COCO person + ByteTrack β head/torso geometric association β temporal hysteresis). TensorRT FP16, all weights included, Colab-ready. |  |
β 0 |
code-context-engine |
MCP context engine for AI coding agents: a local code graph answers "which files does this task need?" β folded evidence packets instead of whole files. Recall 1.000 on repos it was never tuned on, 45% fewer context tokens in a real Claude Code session. Rust, local-first, MIT. |  |
β 5 |
FireGuuard_Fire_detection_smoke |
π₯ Real-time fire & smoke detection for indoor CCTV β YOLO26 detector, hazard-state alerting, and instant email alarms. Full pipeline: dataset audit β training β TensorRT export β live inference. | |
β 5 |
pelakx-license-plate-detection |
πͺ§πͺOpen-source multilingual ALPR / car license plate recognition: YOLO vehicle (car, bus, truck, motorcycle) + plate detection, Persian & Latin OCR, per-country plate grammar validation, temporal fusion, and a config-driven demo notebook. Iran plate support out of the box. | |
β 4 |
thief-face-detection |
π΄ββ οΈπ΄ββ οΈTells a robber in a balaclava from a customer in a surgical mask β real-time concealed-face detection for retail CCTV. Pose-based orientation, occlusion-hardened tracking, zero training.π΄ββ οΈ | |
β 5 |
melkai-realestate-platform |
ππAI-powered Persian real estate platform β Next.js 16 demo (private preview)ππ |  |
β 4 |
point-cloud-curve-reconstruction |
ππFive peer-reviewed algorithms for 3D point cloud denoising and curve reconstruction, benchmarked on industrial 3D-printing scan data | |
β 5 |
pcb-component-classifier |
Explainable classification of electronic components from images - Random Forest over 33 hand-engineered CV features, 93.3% holdout accuracy, every prediction traceable to a readable decision path | |
β 4 |
pcb-component-detection-yolov8 |
YOLOv8 detection of electronic components on populated PCBs - 50 classes, 675k annotations, with dataset tooling and a full diagnosis of what limits the baseline | |
β 5 |
visual-intelligence-engine |
π§ π§ Multimodal search over an image archive - face recognition, species detection, food recognition and open-vocabulary text search on one unified index.π§ π§ | |
β 4 |
ai-project-template |
π€Clean, reproducible project template for Computer Vision & Machine Learning - config-driven training, seeded runs, tests and CI out of the box.π€ |  |
β 4 |
π Web & Full-Stack Β· 5 repos
| Repo | What it is | Language | Stars |
|---|---|---|---|
ParsaVictor.github.io |
πMohammad Parsa Karkooti β AI Engineer portfolio (GitHub Pages mirror) |  |
β 3 |
portfolio |
ππMotion-led personal portfolio β a WebGL particle instrument that morphs through the work as you scroll. React + Three.js + GSAP.ππ | |
β 4 |
neuromesh |
π§ The Biomimetic Context Engine & Neural Runtime for AI Coding Assistants | β 3 | |
b2b-marketplace |
ππ B2B International Marketplace ππ | |
β 5 |
Construction-Site-Safety-PPE-Detection |
βοΈβοΈ Custom object detection for PPE Detection of Construction Site Workers. This repo contains notebook for PPE Detection using YoloV8. | β 1 |
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Computer Vision Object detection & tracking, face recognition, pose estimation, image retrieval, video understanding, open-vocabulary / multimodal models. |
AI Systems Engineering Modular inference pipelines, real-time multi-stream processing, DB-integrated AI apps, model optimization, hardware-aware deployment. |
ML & Data Science Feature engineering, EDA, classical ML (XGBoost/LightGBM/SVM), recommender systems, rigorous offline evaluation. |
- β¬οΈ Pushed 1 commit to
ParsaVictor/portfolio - β¬οΈ Pushed 1 commit to
ParsaVictor/ParsaVictor.github.io - β¨ Created branch
maininParsaVictor/PPE_detection-Sentinel - π merged PR in
pinoox/neuromesh
- π¦
code-context-enginev1.0.0β v1.0.0 β the right files, measured on repositories it never saw (2026-09-22)
π Whatever's actually pinned on the profile
π Auto-refreshed daily Β· 6 pinned repos Β· language colours match GitHub's own
| Repo | Description | Language | |
|---|---|---|---|
ai-project-template |
π€Clean, reproducible project template for Computer Vision & Machine Learning - config-driven training, seeded runs, tests and CI out of the box.π€ | |
β 4 Β· π΄ 0 |
ParsaVictor |
My GitHub profile README - AI Engineer | Computer Vision & Deep Learning |  |
β 6 Β· π΄ 2 |
code-context-engine |
MCP context engine for AI coding agents: a local code graph answers "which files does this task need?" β folded evidence packets instead of whole files. Recall 1.000 on repos it was never tuned on, 45% fewer context tokens in a real Claude Code session. Rust, local-first, MIT. | |
β 5 Β· π΄ 4 |
visual-intelligence-engine |
π§ π§ Multimodal search over an image archive - face recognition, species detection, food recognition and open-vocabulary text search on one unified index.π§ π§ | |
β 4 Β· π΄ 2 |
FireGuuard_Fire_detection_smoke |
π₯ Real-time fire & smoke detection for indoor CCTV β YOLO26 detector, hazard-state alerting, and instant email alarms. Full pipeline: dataset audit β training β TensorRT export β live inference. | |
β 5 Β· π΄ 3 |
thief-face-detection |
π΄ββ οΈπ΄ββ οΈTells a robber in a balaclava from a customer in a surgical mask β real-time concealed-face detection for retail CCTV. Pose-based orientation, occlusion-hardened tracking, zero training.π΄ββ οΈ | |
β 5 Β· π΄ 3 |
Passing through? Leave a note β I read every one. The guestbook lives in issues; it doubles as my feedback wall.
