Emmanuel Adebayo

To obtain an internship which will enhance my knowledge and experience in the Computer Science field, management, and related field

Node Alignment: I applied node2vec embeddings, neural network models, and k-nearest neighbors algorithms to align nodes across two graphs, enhancing similarity comparison and facilitating cross-graph analysis. 

https://github.com/emadebay/Graph_Convolutional_neural_network_node_alignment

Natural Language Processing: Designed and implemented a sentiment analysis system. I implemented Feature extraction and logistic regression for sentiment classification. Additionally, fine-tuned a sentiment classifier using Hugging Face's DistilBERT and PyTorch, achieving accurate sentiment classification through a combination of traditional machine learning and deep learning techniques. Demonstrated proficiency in natural language processing, machine learning algorithms, and model development.

https://github.com/emadebay/NLP_HW-PROJECTS

Image Enhancements: From scratch, i designed and implemented histogram equalization, log mapping, gaussian filtering, image rotation and median filtering to remove degradation from images. 

https://github.com/emadebay/image_enhancements

Camera Calibration: Successfully conducted camera calibration project, deriving both intrinsic and extrinsic parameters from a given calibration rig, optimizing imaging accuracy and precision. 

https://github.com/emadebay/camera_calibration

Image Segmentation: Implemented image segmentation techniques to partition images into meaningful regions, enhancing object detection and analysis accuracy for diverse applications.

https://github.com/emadebay/image_segmentation

Fruit-Disease Classification: Utilized Keras deep learning framework to train and predict fruit disease classification, leveraging convolutional neural networks for accurate identification and diagnosis, enhancing agricultural productivity and disease management.

https://github.com/emadebay/fruit_disease_classification_deep_learning

Online-MarketPlace: Developed a Java-based Online Store System incorporating a Model-View-Controller (MVC) architecture and employing various design patterns for scalability and maintainability. Key features include secure user authentication, seamless product browsing, efficient inventory management, and robust user administration capabilities. Leveraged design patterns such as Factory, Command, Authorization, Observer, and Dispatcher to ensure modularity, fault handling, and user access control, providing a reliable and user-friendly platform for both customers and administrators.

https://github.com/emadebay/marketplace

• Statistical Machine learning (CSCI 57800)
• Natural Languahe Processing (CSCI 5900)
• Deep Learning (CSCI 59000)
• Algorithm Design and Analysis (CSCI 58000)
• Image Processing and Computer vision (CSCI 57800)
• Intelligent Systems (CSCI 54900)
• Object Oriented Design and Programming (CSCI 50700)
• Theory of Computation (CSCI 48400)
• Data mining (CSCI 48100)
• Data Science (CSCI 48900)
• Numerical Methods (CSCI 41400)
• Principles of Software Design (CSCI 36300)
• Architecture of Computers (CSCI 40200)
• Operating Systems (CSCI 40300)
• Discrete Computational Structures (CSCI 34000)

A repository for some of the collection of my projects.

https://github.com/emadebay