Digital Twin Builder
Standalone Unreal Engine 5.6 editor tool. Pick photos or a video, run YOLO-World on system Python, and spawn a furniture-level digital twin in the level.
AI/ML Engineer — computer vision, digital twins & Unreal tooling
I train custom models and ship editor tools that turn photos, video, and 3D assets into production-ready scenes — digital-twin pipelines and standalone Unreal Engine plugins.
About
I specialize in custom model training — computer vision, NLP, and agentic systems — then wrap that work in tools people can actually run. Lately that means Unreal Engine Python plugins, synthetic data pipelines, and digital twins built from photos or video.
Outside Unreal I work across TensorFlow, PyTorch, YOLO, RAG agents, and freelance computer-vision systems for cameras, drones, and inspection workflows.
Stack
The full stack behind the work — models, Unreal tooling, agents, and the libraries I ship with.
Selected work
Unreal Engine tools and AI projects — Digital Twin Builder is a standalone editor tool that drops into any UE5 project.
Standalone Unreal Engine 5.6 editor tool. Pick photos or a video, run YOLO-World on system Python, and spawn a furniture-level digital twin in the level.
Standalone UE5.6 tool: images or video → YOLO-World detection → spawned digital twin. Drops into any Unreal project.
Unreal editor plugin that imports FBX or ZIP packages with textures, materials, and folder structure. Supports skeletal or static meshes from Tools → Import FBX Package.
Right-click Unreal assets or components and package them with every dependency into a standalone ZIP or another local project.
Cook and package the Unreal project as Developer or Shipping builds, with live UAT progress streamed to the Output Log.
Multi-sensor FPV drone detection in Isaac Sim using synchronized RGB and LWIR cameras, YOLO, and ground-truth pose for Kalman tracking.
Computer vision pipeline for tennis footage: court calibration, ball tracking, bounce detection, and YOLO-based player analysis.
Computer vision assistant for Call of Duty. The match ran on a PS4 while we remotely accessed the stream on PC, then ran enemy detection on that live feed.
Pose-retargeting pipeline that turns sketches and Canny edges into consistent anime frames with Gemini, Streamlit UI, and Docker.
Ensemble CNN pipeline comparing SimpleCNN, MobileNetV3, and ResNet50 with voting, stacking, and statistical ablation studies.
Detects and counts vehicles in traffic footage using object detection algorithms in real time.
Browser automation bots for repeating web tasks, scraping, and agent-style navigation in Python.
Computer vision model that classifies fruit from images for inspection and sorting workflows.
Generative adversarial network implemented from the ground up to learn image generation without high-level wrappers.
Attention, encoder-decoder stacks, and training loops built by hand to understand modern NLP architectures.
VAE implementation covering encoder-decoder structure, latent sampling, and reconstruction loss.
Desktop/web tooling for office records, staff workflows, and day-to-day operations.
Real-time chat application for browser-based messaging and conversation threads.
Robotics experiments covering control, perception, and Python simulation for motion tasks.
Core machine-learning algorithms reimplemented from scratch for learning and debugging.
Streaming-style UI clone with catalog browsing and playback layout patterns.
Classic iris flower classifier using feature analysis and supervised learning.
Vision/graphics experiment for detecting and tracking dice rotation from image sequences.
Detects damage in car manufacturing parts using deep learning for automated quality control.
Identifies and classifies playing cards from images even under partial visibility or varied lighting conditions.
Automated attendance tracking using real-time face detection and recognition without manual input.
Human body pose detection and skeleton tracking from video streams for fitness coaching and gesture control.
U-Net model that segments regions of interest in medical scans for early detection of anomalies.
Tracks player movements, ball trajectories, and shot accuracy in real time from game footage.
AR overlay of nail art onto live hand video so users can try styles before applying them.
Tracks player positions, tactical formations, and match statistics from broadcast footage.
Retail surveillance that detects shoplifting, monitors customer flow, and triggers real-time alerts.
Multi-agent system built with CrewAI that gathers, analyzes, and summarizes news from various sources.
Retrieval-augmented generation that answers queries over large document collections with cited responses.
Autonomous agent that browses the web, extracts information, and compiles structured research reports.
Reviews pull requests, detects bugs and code smells, and explains issues in plain language.
Handles queries via RAG, keeps conversation memory, and escalates complex issues intelligently.
Extracts, classifies, and routes information from invoices, contracts, and forms with no manual effort.
Analyzes behavior and purchase history to deliver personalized product recommendations in real time.
Monitors industrial equipment metrics, detects anomalies, and triggers maintenance before failures.
Generates concise summaries of academic papers while preserving key findings and conclusions.
Regression model predicting house prices from location, size, and amenities using ensemble methods.
Predicts car prices from make, model, year, and specs using ensemble ML algorithms.
Predicts which customers are likely to leave a service using behavioral data for retention.
Hybrid engine combining collaborative filtering and content-based methods for movie suggestions.
Anomaly detection for fraudulent transactions using imbalanced learning and ensemble classifiers.
LSTM time-series model forecasting Bitcoin prices using historical data and technical indicators.
Forecasts greenhouse gas emissions for the next 30 years using historical environmental data.
Multi-step forecasting combining LSTM and Transformer architectures on historical market data.
Forecasts temperature, precipitation, and wind patterns from historical meteorological data.
Predicts residential and industrial energy consumption patterns to optimize grid management.
Reads books and PDFs aloud using text-to-speech for a hands-free audio experience.
Identifies artificially generated or manipulated voices using spectral analysis and deep learning.
Identifies bird species from songs and calls using MFCC feature extraction and CNN classification.
Classifies human emotions from audio recordings using MFCC and spectrogram features.
Voice biometrics that identify who is speaking by comparing speaker-specific vocal features.
Live transcription using Whisper and streaming pipelines with low latency and high accuracy.
Python GUI to download YouTube videos and audio with quality and format options.
Scrapes anime sites to track and notify users about the latest episodes of their favorite series.
Generates QR codes from text or URLs with customizable size and error correction settings.
Measures internet download/upload speed and ping with a clean interface and visualization.
ML system detecting network intrusions by analyzing traffic patterns in real time.
Analyzes password strength using entropy calculation, pattern detection, and dictionary attack simulation.
Deep learning system analyzing file behavior to detect zero-day threats and classify malware.
NLP and computer vision to detect phishing attempts in emails and websites.
Learning
Coursera — Stanford University
December 2023
Supervised learning, neural networks, unsupervised learning, and reinforcement learning.
Coursera — DeepLearning.AI
August 2023
CNNs, sequence models, attention mechanisms, and transformers.
freeCodeCamp
July 2022
Python libraries for data analysis, visualization, and machine learning.
Coursera
April 2023
Developing and training GANs for generation tasks.
DeepLearning.AI
February 2023
Vector-based search for semantic analysis and retrieval.
DeepLearning.AI
January 2023
Fundamentals of AI and vector search technologies.
DeepLearning.AI
March 2023
Prompt engineering for ChatGPT and similar LLMs.
DeepLearning.AI
April 2023
Model quantization techniques in the Hugging Face ecosystem.
DeepLearning.AI
May 2023
Using Mistral language models for downstream applications.
DeepLearning.AI
June 2023
Building and deploying multi-agent systems with CrewAI.
DeepLearning.AI
July 2023
Running AI models on edge devices and optimization techniques.
DeepLearning.AI
August 2023
Multimodal LLaMA 3.2 for combined text and visual tasks.
DeepLearning.AI
September 2023
Vector search with Atlas for efficient information retrieval.
DeepLearning.AI
October 2023
Fundamentals of diffusion models and generative AI applications.
Career
Custom AI models for computer vision, NLP, and predictive analytics — plus Unreal Engine editor plugins and digital-twin tooling.
Built and deployed AI-powered solutions, contributing to model development and production ML pipelines.
Assisted in developing ML models and data preprocessing pipelines with TensorFlow, PyTorch, and data analysis tools.
Worked on AI research projects in robotics and computer vision, assisting with experiments and data collection.
Background
Focused on artificial intelligence, machine learning, and software engineering with hands-on projects in computer vision, NLP, and data science.
Contact
Open to freelance, Unreal tooling, and computer-vision work. Email is the fastest way to reach me.