Graduate Research Assistant (WHB - Wissenschaftliche Hilfskräfte)
Technische Universität Dortmund
May 2024 - Oct 2024
Dortmund, North Rhine-Westphalia, Germany
German Research Foundation (DFG) Project (Grant KE 1413/14-1): Conditionals and ASP for Expert Reasoning (CASPER), A hybrid knowledge-based system based on conditionals and ASP with an interactive modeling environment and application to warehouse planning.
Contributed to building CASPER, a hybrid knowledge-based system that combines conditionals with Answer Set Programming (ASP) to improve expert reasoning.
Developed with interdisciplinary teams to create an interactive warehouse planning modeling environment that integrated complicated algorithms and user-friendly interfaces.
Assisted with literature studies, data analysis, and testing to support evidence-based decision-making and promote knowledge-based systems and logistics optimization.
Prove analytical and problem-solving skills by actively participating in research debates, predicting, and conducting experiments, resulting in peer-reviewed journal publications and academic conference presentations.
Graduate Research Assistant (WHB - Wissenschaftliche Hilfskräfte)
Ruhr University Bochum
Sep 2022 - Mar 2023
Bochum, North Rhine-Westphalia, Germany
I guided the patent analysis project using R programming to analyze data and create engaging visualizations. I clearly explained difficult data insights.
Extensive data analysis and visualization revealed key trends and patterns to inform corporate strategy. Strategic decision-making and performance improved as a result of the insights gained.
Data entry, cleaning, and Power BI outlier handling were expertly done. Provided rigorous dataset preparation, demonstrating data integrity and data management proficiency.
presented data analysis expertise utilizing Microsoft Excel and R. Used descriptive statistics and regression analysis to get insights, aiding data-driven decision-making.
Graduate Research Assistant (WHB - Wissenschaftliche Hilfskräfte)
Technische Hochschule Lübeck
Jan 2023 - Feb 2023
Lübeck, Schleswig-Holstein, Germany
As a research assistant in computer science, I collaborated with a team of researchers to investigate and apply deep learning techniques to various research problems. Some of my primary responsibilities included.
Preparing and preprocessing data sets for use in machine learning models, including data cleaning, normalization, and feature extraction.
Developing and implementing deep learning models, including convolutional neural networks (CNNs), using frameworks such as TensorFlow and keras.
Analyzing and interpreting the results of machine learning experiments, and collaborating with other researchers to refine the models and improve
performance.
The name of our project is Benzol graph prediction, In this project, we used deep learning to classify different types of images, achieving classification
accuracy. My specific contribution to the project was developing and training the CNN model.
Overall, my experience as a research assistant in deep learning has provided me with strong skills in data analysis, machine learning, and programming, as
well as an ability to work collaboratively in a research team.