Abdelrahman Abozied

Collaborated with experts/stakeholders to understand fraud scenarios, refine feature engineering strategies, and align project objectives with business requirements. Integrated diverse data sources (customer info, account types, transactions) to create a comprehensive view of financial activity. Designed feature engineering pipeline, leveraging customer account relationships and transaction data. Created time rolling periods for transaction data, capturing patterns/trends for accurate fraud detection.

Translated business requirements into AI and machine learning solutions. Utilized NLP techniques to collect and filter data, extracting valuable insights. Worked on large-scale, real-time data and analytics projects, employing advanced machine learning models. Designed and implemented a new database by scraping data from various sources, conducting analysis, and preparing it for use. Engineered cost-efficient alternatives to a paid API service, resulting in significant cost savings for the company.

Contributed to the Editing Large Language Model Predictions with Natural Language Feedback project, working under the supervision of Prof. Derry Wijaya and mentorship of Afra Feyza Akyürek, a Ph.D. student.Conducted research on improving the accuracy of OpenAI GPT-3 code-davinci-002 predictions on GSM8K and MBPP datasets, using natural language feedback. Created and implemented new ideas to enhance the accuracy of the project's predictions and generate high-quality prompts.

Acquired a comprehensive understanding of AI and Machine Learning fundamentals through extensive training and hands-on projects. Built machine learning models using the scikit-learn library and gained hands-on experience. Designed and implemented deep learning models using TensorFlow and Keras, solidifying my knowledge of deep learning algorithms and techniques.

Acquired knowledge on generating innovative ideas through design thinking and mind-mapping techniques. Improved entrepreneurial skills by gaining exposure to the fundamental principles of entrepreneurship and interactive learning opportunities to apply essential tools to turn ideas into a business. Demonstrated leadership abilities by managing team tasks and overseeing performance with mentor guidance.

Translated business requirements into high-quality, production-ready code to enhance the end-user experience. Developed web pages using HTML5, CSS3, and JavaScript with a focus on clean implementation, ensuring the pages were responsive and designed with mobile-first principles. Implemented modular websites using Bootstrap and SASS to ensure a smooth user experience.

Area: Artificial Intelligence and Machine Learning.

GPA: 3.64 / 4 (1.3 German Scale) Grade: Excellent Thesis: Emotion Recognition using Artificial Intelligence Solutions. (A* Excellent)