Ali Farooq

Develop dynamic web applications using Node.js for back-end with MongoDB and Vue.js (Quasar) for front-end. Implement advanced AI solutions using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) techniques using Stream-lit, Fast API and Python. Work on Docker and Docker compose for containerization and micro services. Implement Shinny application using R. Work on NextCloud service for data backup using .

Investigation of deep batch active learning methods for marine species detection. Mini-batch active learning method for uncertain and diverse samples using kmeans and entropy. Yolov5 and InceptionV3 models for object detection and classification. Visual studio code, Python and statistical analysis of results.

IT-administration (data backup, system monitoring, software installation). Bone segmentation and scanning using Ct-scan machine.

Worked on Named-entity recognition on historical documents. Researched and implement on Named-entity recognition using BERT algorithm. Data Tagging, Data Preparation and Analysis using Python. Docker, Graph Database using Gremlin, Python, Linux, Visual Studio Code & Rest API.

Implemented and evaluated Machine Learning, Deep Learning algorithms for Geo-Mechanics. Data Preparation, Analysis and Prediction using Python frameworks pandas, Keras, Tensorflow and scikit-learn, Spyder, Jupyter-Notebook and Anaconda IDE.

Cross-Calibration of Cortical bone parameters through CT-scans of embedded human vertebral bodies using image processing algorithms, Matlab, statistical tests and Bland-Altman analysis.

"Bone Age Assessment" project in UKSH with Prof. Dr. Claus-C. Glüer. Implementation and research on Finite element method. Performed Bone segmentation and meshing using Matlab with in-house software Structural Insight. Data management and analysis of patient’s CT-scan.

Worked on the Generative Adversarial networks with Prof. Dr. Hauke Schramm. Research and development of GAN technology, back propagation and Convolutional Neural Network. Using Python 3.6 (TensorFlow, Torch, NumPy), Anaconda 5.1 and Jupyter-notebook 5.2.

Implementation of Urdu Optical Character Recognition using Java. Implementation and management of language dictionaries using C# and .Net. Annotation and analyzing recorded data using C. Research on Urdu plagiarism detection and Urdu search engine projects.

Development of web application using PHP Zend Framework. Full stack web application. Use google API Import.io to import data from other shopping websites.

Specialization in "Intelligent Systems" Master Project: "Cross-Calibration of Cortical bone parameters through CT-scans of embedded human vertebral bodies". Master Thesis: "Investigation of deep batch active learning methods for marine species detection". Specialization Courses: Machine Learning, Neural Networks and Deep Learning, Pattern Recognition, Mastering Java, Advanced C++, Requirement Engineering, Advanced Software Programming and Research Course on Deep Learning algorithms.

Development(Web, System and mobile) applications, Mathematics, Networking or Computer Architecture.