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umitkacar/README.md

Welcome! I'm Umit KACAR, PhD

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🎯 Passionate about making AI accessible, efficient, and impactful for everyone

"The best way to predict the future is to invent it" - Alan Kay

🌟 Senior AI/ML Researcher & Engineer | Algorithm Innovator | Computer Vision & Biometrics Expert 🌟

πŸ”’ Digital Identity & Anti-Spoofing Specialist | πŸ€– Generative AI Consultant | πŸ“± Mobile AI Optimization

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πŸš€ About Me

ML Engineering

I'm an AI Researcher & Engineer with 14+ years of AI/ML experience (since 2011) and 7+ years in academia (2 years Master's, 5+ years Doctorate) specializing in Machine Learning for Computer Vision applications. Expert in biometrics with focus on face and fingerprint detection, anti-spoofing and developing innovative algorithms, especially for mobile platforms.

🎯 Current Focus

  • 🌱 Developing low-cost, efficient, and lightweight AI models for resource-constrained environments
  • πŸš€ Creating novel, breakthrough algorithms for biometric systems
  • πŸ“± Optimizing AI models for iOS & Android deployment
  • πŸ€– Exploring Generative AI, Large Vision Models, and Multimodal Systems

πŸŽ“ Academic Excellence

  • πŸŽ“ PhD in Electronic Engineering - Istanbul Technical University (2013-2019)
    • Focus: Computer Vision, Artificial Intelligence, Deep Learning Algorithms
    • GPA: 3.92/4.00
    • πŸ† 1st Winner in Unconstrained Ear Recognition Challenge (UERC) Competition
  • πŸŽ“ Master's in Electronic Engineering - Istanbul Technical University (2011-2013)
    • Focus: Computer Vision, Machine Learning, Embedded Systems
    • GPA: 4.00/4.00 - Best GPA in 2013
  • πŸ“š 5+ years of Doctoral research with groundbreaking contributions
  • πŸ“ 10+ Publications in top-tier conferences and journals

πŸ“ˆ Career Journey

timeline
    title Career Milestones & Achievements
    
    2007-2011 : Electronics & Embedded Systems
               : Hardware & System Design
    
    2011-2013 : AI/ML Career Start + Master's
               : Electronic Engineering Master's
               : Best GPA (4.00/4.00)
               : ARM-based Biometric Systems
               
    2013      : Published First IEEE Papers
               : Embedded Biometric Systems
               
    2013-2019 : PhD in Electronic Engineering
               : GPA 3.92/4.00
               : 10+ Research Publications
               
    2018      : ScoreNet Algorithm Development
               : IET Biometrics Journal Publication
               : Private Sector Career Start
               
    2019      : πŸ† 1st Place UERC Competition
               : PhD Thesis Completion
               
    2019-2023 : 100+ AI Models Deployed
               : Mobile Biometric Solutions
               : KYC/AML Platform Development
               
    2023-2025 : πŸ† LivDet2023 Winner
               : iBeta Level 2 Certification
               : Generative AI Innovations
               : Continuing Innovation
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πŸ› οΈ Technical Expertise

Core Specializations

πŸ” Biometric Systems & Digital Identity
  • Multi-biometric expertise: Face, Fingerprint, Iris, Sclera, Ear, Voice, Signature, Palm vein, Palmprint
  • Applications: Detection, Verification, Recognition, Anti-spoofing (Liveness Detection), DeepFake Detection
  • Production Systems:
    • KYC/AML platforms with document verification (ID Card, Passport, Driver License)
    • Hologram detection and document liveness
    • iBeta Level 2 certified fingerprint liveness detection
    • Contact to contactless fingerprint matching
    • Real-time face recognition for mass transit systems
  • Technologies: ONNX Runtime C++, ncnn, CoreML, TensorFlow Lite
  • Achievements: LivDet2023 Winner, UERC 2019 Champion
🎨 Generative AI & Large Models
  • Large Vision Models: SAM, FastSAM, MobileSAM, Paligemma, CLIP, Florence, Flamingo, BLIP, LLaVA
  • Language Models: ChatGPT 4.5, Claude 3.7, Perplexity, Grok 3, Le Chat, Gemini 2.0, LLama, Mistral
  • Generative Models: Stable Diffusion, GANs, VAEs
  • Production Implementations:
    • AI Model deployment using ONNX Runtime in C++
    • Cryptograph AI Detector & Image Quality Assessment
    • Synthetic data generation pipelines with Stable Diffusion
    • Face photo editor with beauty tools, background removal, inpainting
    • Video object segmentation and matting
  • Model Optimization: Pruning, Quantization, Knowledge Distillation
  • AutoLabelling System: 50+ AI models integrated with fusion methods
πŸ“± Edge Computing & Mobile AI
  • TinyML Implementation: Model optimization for edge devices
  • Optimization Techniques: Pruning, Quantization, Knowledge Distillation
  • Neural Architecture Search: Automated model design for efficiency
  • Mobile Deployment: Real-time biometric systems on iOS (Swift, CoreML) and Android

Tech Stack

Programming Languages

Python C++ Swift JavaScript

AI/ML Frameworks

PyTorch CoreML ONNX ncnn scikit-learn

Computer Vision & Deep Learning

OpenCV YOLO Detectron2 Albumentations Weights & Biases

Mobile Development

iOS Android Swift Kotlin

MLOps & Cloud

AWS Google Cloud Docker Flask FastAPI

πŸ”¬ Research & Expertise Areas

Biometrics
Biometric Systems
Face, Fingerprint, Iris
Anti-spoofing & Liveness
Mobile AI
Mobile AI
iOS & Android
Real-time Performance
Generative AI
Generative AI
Stable Diffusion, LLMs
Vision-Language Models
Edge AI
Edge Computing
TinyML, Model Optimization
Resource-constrained Devices

πŸš€ Major Projects & Achievements

πŸ† Award-Winning Projects

  • πŸ₯‡ LivDet2023 Winner - Fingerprint Liveness Detection

    • iBeta Level 2 Certified Solution
    • Implemented using ncnn C++ for mobile deployment
    • State-of-the-art anti-spoofing algorithms
  • πŸ† UERC 2019 1st Place - Unconstrained Ear Recognition Challenge

    • Developed ScoreNet: Deep Cascade Score Level Fusion algorithm
    • Outperformed international research teams

πŸ’‘ Innovation Projects

  • AutoLabelling System

    • Integrated 50+ AI models using advanced fusion methods
    • Automated image segmentation pipeline
    • Reduced manual labeling effort by 90%
  • AI Model Portfolio

    • Successfully trained and deployed 100+ AI models
    • Specialized in biometric and computer vision applications
    • Optimized for mobile and edge devices

πŸ” Biometric Systems

  • Istanbul Metro Face Recognition System

    • Real-time face detection, verification & recognition
    • Implemented in C++ for high performance
    • Handles millions of daily transactions
  • Contact to Contactless Fingerprint Matching

    • Cross-modal biometric matching system
    • C++ implementation with ONNX Runtime
    • Mobile-optimized for iOS and Android
  • Multi-Modal KYC/AML Platform

    • ID Card, Passport, Driver License verification
    • Document liveness and hologram detection
    • DeepFake and anti-spoofing protection

🎨 Generative AI & Computer Vision

  • Advanced Face Photo Editor

    • Beauty enhancement algorithms
    • Background removal & replacement
    • Video inpainting and object segmentation
    • Real-time filters and effects
  • Synthetic Data Generation Pipeline

    • Stable Diffusion integration
    • Custom image processing workflows
    • Advanced augmentation techniques

🌍 Industry Applications

  • Agricultural AI - Weed & crop detection with multi-spectral cameras
  • Manufacturing - Steel defect detection system
  • Automotive - Advanced Driver Assistance Systems (ADAS)
  • Security - Video Analytics for IP CCTV systems
  • Mobile AI - Cryptograph detector & image quality assessment

🏒 Domain Experience

I've delivered AI solutions across multiple sectors:

  • πŸ” Biometrics & Security: Multi-biometric authentication systems
  • πŸ₯ Healthcare & Medicine: Medical image analysis and diagnostics
  • 🌾 Agriculture: Computer vision for crop monitoring
  • πŸ’° Fintech: KYC/AML systems, fraud detection
  • 🎬 Film Production: AI-powered visual effects
  • 🚁 Unmanned Vehicles: Autonomous navigation systems

πŸ“Š GitHub Analytics

GitHub Stats Top Languages

πŸ“š Research Publications

Selected Publications

  1. ScoreNet: Deep Cascade Score Level Fusion for Unconstrained Ear Recognition

    • IET Biometrics Journal, 2018
    • Introduced Automated Fusion Learning (AutoFL) and Deep Cascade Score Level Fusion
    • Key algorithms: CNN (VGG, Inception, ResNet, DenseNet), LBP, LPQ, BSIF, HOG, PCA, LDA
  2. The Unconstrained Ear Recognition Challenge 2019

    • ICB 2019 - The 12th IAPR International Conference On Biometrics
    • πŸ† 1st Place Winner with ScoreNet algorithm
    • Novel approach combining deep learning with traditional features
  3. Twins Recognition Using Hierarchical Score Level Fusion

    • arXiv.org, 2019
    • Multi-modal biometric system using voice and ear features
    • Algorithms: LSTM, DTW, MFCC, DenseNet-CNN, HOG, PCA
  4. SCORENET: UNCONSTRAINED EAR RECOGNITION WITH DEEP CASCADE SCORE LEVEL FUSION

    • PhD Thesis - Istanbul Technical University, 2019
    • Comprehensive framework for ear biometrics
    • Novel fusion strategies outperforming state-of-the-art methods
  5. A Multi-Biometrics for Twins Identification Based Speech and Ear

    • arXiv.org, 2018
    • Innovative approach to challenging twin identification problem
    • Combined DTW, MFCC, Gabor Filters, DCVA algorithms
  6. ARM-based Ear Recognition Embedded System

    • EUROCON 2013, IEEE
    • First real-time ear recognition on ARM Cortex processors
    • Optimized PCA implementation using Jacobi iteration
  7. An Embedded Biometric System

    • 16th International Conference on Information Fusion, 2013
    • Hardware: STM32F407VGT6 ARM Cortex-M4
    • Novel embedded implementation of DCVA algorithm

Research Impact

  • Citations: 100+ (Google Scholar)
  • h-index: Growing research influence
  • Key Contributions: Score fusion methods, embedded biometrics, real-time processing

πŸ† Featured Open Source Projects

AI-powered ear detection and segmentation using deep learning models. Implementation of cutting-edge computer vision algorithms for biometric applications.

Tech Stack: Python, PyTorch, OpenCV

Curated collection of Large Language Model resources, papers, and tools. Comprehensive guide for researchers and practitioners.

Tech Stack: Documentation, Research Papers

πŸ“ˆ Contribution Activity

GitHub Activity Graph

πŸ… Professional Highlights

  • πŸŽ“ PhD in Electronic Engineering - Istanbul Technical University (GPA: 3.92/4.00)
  • πŸŽ“ Master's in Electronic Engineering - Istanbul Technical University (GPA: 4.00/4.00 - Best in Class 2013)
  • πŸ† Competition Winner: 1st Place in Unconstrained Ear Recognition Challenge (UERC) 2019
  • πŸ† LivDet2023 Winner: Fingerprint Liveness Detection Competition
  • πŸ“š 14+ Years AI/ML Experience (since 2011) + 4 years electronics background
  • πŸ”¬ 7+ Years Academic Research with 10+ publications
  • πŸ’― 100+ AI Models trained and deployed in production
  • πŸš€ Innovation Leader: Developed ScoreNet and AutoFL algorithms
  • πŸ“± Mobile AI Expert: iBeta certified biometric solutions
  • 🌍 Industry Impact: Solutions deployed across multiple industries locally and internationally

πŸ’­ Innovation Philosophy

⚑ "Committed to pushing the boundaries of AI with innovative approaches to solve complex vision and biometric challenges" ⚑

🀝 Let's Connect and Collaborate!

I'm always interested in discussing AI innovations, research collaborations, and challenging projects.

LinkedIn Email Google Scholar

Pinned Loading

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