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My name is Liban A. and I have over 2 years of experience in the tech industry. I specialize in the following technologies: Python, Django, FastAPI, RESTful API, Python Script, etc.. I hold a degree in . Some of the notable projects I’ve worked on include: Location Scraping, Coffe Plants Disease Detection, Patient registration and Appointment scheduling system, RATE EAT. I am based in Addis Ababa, Ethiopia. I've successfully completed 4 projects while developing at Softaims.
I value a collaborative environment where shared knowledge leads to superior outcomes. I actively mentor junior team members, conduct thorough quality reviews, and champion engineering best practices across the team. I believe that the quality of the final product is a direct reflection of the team's cohesion and skill.
My experience at Softaims has refined my ability to effectively communicate complex technical concepts to non-technical stakeholders, ensuring project alignment from the outset. I am a strong believer in transparent processes and iterative delivery.
My main objective is to foster a culture of quality and accountability. I am motivated to contribute my expertise to projects that require not just technical skill, but also strong organizational and leadership abilities to succeed.
Main technologies
Backend, AI and Database Platforms
2 years
Python
1 Year
Django
1 Year
FastAPI
1 Year
Additional skills
- Python
- Django
- FastAPI
- RESTful API
- Python Script
- API Integration
- AI Agent Development
- Telegram API
- Machine Learning
- MongoDB
- Artificial Intelligence
- Web Scraping
- PostgreSQL
- MySQL
- Selenium
Direct hire
Potentially possible
Previous Company
Kifiya Financial Technology
Experience Highlights
Location Scraping
The Australian Location Data Scraper is a Python-based web scraping tool developed to extract comprehensive location information from Australian hotel website. The tool utilizes the Selenium framework to automate the data extraction process, ensuring accuracy and efficiency in gathering location details across different pages.
Coffe Plants Disease Detection
• Conducted image segmentation on coffee plant images to isolate disease-affected areas, providing accurate input data for the deep learning model. • Developed a deep learning model using TensorFlow to classify various coffee plant diseases, including leaf rust, coffee berry disease, and black rot. • Created Python scripts for data preprocessing and augmentation to enhance the training dataset for the deep learning model. • Implemented a mobile app using Flutter to deliver a user-friendly interface for farmers and coffee plant enthusiasts, enabling them to detect and diagnose coffee plant diseases using their smartphones. - Applied transfer learning techniques to fine-tune a pre-trained deep learning model for coffee plant disease classification, leveraging the power of machine learning to achieve higher accuracy and faster convergence. - Collaborated with domain experts and agronomists to validate the accuracy and effectiveness of the machine learning model, ensuring its practical applicability in real-world coffee plant disease scenarios. • Contributed to the advancement of the coffee industry by providing a valuable tool for farmers to quickly identify and address plant diseases, leading to improved crop yields and coffee quality.
Patient registration and Appointment scheduling system
1. Developed the frontend UI/UX using Flutter: I was responsible for designing and implementing the user interface of the mobile application using Flutter framework. I created visually appealing screens for patient registration, appointment scheduling, checkup results, medication availability, and next appointment information. 2. Implemented the patient notification system: I integrated a notification feature that sends reminders to patients regarding their scheduled appointments, checkup results, and medication availability. This involved working with push notification services and integrating them into the mobile app. 3. Designed and developed the doctor's dashboard: I created a dedicated dashboard for doctors to access patient information and update their medical records after each checkup. The dashboard provided a user-friendly interface to view and manage patient data efficiently. 4. Implemented the pharmacy management module: I developed a module for the pharmacist to manage the numerical data of available medicines in the hospital's pharmacy. This included designing a database schema, implementing CRUD operations, and integrating it with the overall system. 5. Worked on the backend using Node.js and Express.js: I contributed to the development of the server-side logic using Node.js and Express.js. This involved handling API requests, implementing authentication and authorization mechanisms, and integrating with the MongoDB database. 6. Collaborated in system testing and bug fixing: I actively participated in system testing to ensure the smooth functioning of the application. I identified and resolved bugs, conducted unit testing, and collaborated with the team to improve the overall performance and stability of the system. These contributions helped enhance the overall functionality, usability, and user experience of the patient registration and appointment scheduling system, making it more efficient and user-friendly for patients, doctors, and pharmacists.
RATE EAT
• Worked as a software engineer on a team responsible for developing a cross-platform mobile application using Flutter. • Developed and maintained the backend server using Node.js, implementing RESTful APIs for communication with the mobile app. • Utilized Python for data processing and analysis, implementing machine learning algorithms for personalized recommendations and improving the overall user experience. • Participated in the design and architecture of the application, contributing to the development of a scalable and maintainable system. • Collaborated with other team members and stakeholders to ensure the timely delivery of project milestones and to meet client requirements. • Performed code reviews and provided feedback to other team members to ensure code quality and consistency. • Conducted testing and debugging of the application to ensure a bug-free and seamless user experience. • Stayed up-to-date with the latest technologies and trends, continuously learning and implementing best practices to improve the project's overall quality and performance.
Education
Addis Ababa University
in Software Engineering(AI)
Languages
- Amharic
- English
- Oromo
Github