Eroju Collin
About Candidate
AI Software Engineer with over 3 years of experience in developing and deploying computer
vision and deep learning models for production-scale applications. Proficient in Python and
Java, with expertise in frameworks such as TensorFlow, Keras, and PyTorch for image
classification, object detection, and segmentation. Experienced in building scalable software
architectures, developing data pipelines, and leading teams in innovative AI solutions. Adept
at solving complex computer vision problems and delivering machine learning applications
that meet business needs.
Education
Library and Information Science (LIS) training covers a wide range of topics and skills related to organizing, accessing, and managing information. I learn about information organization, retrieval, collection development, information literacy, and library management. I learn about different metadata standards, classification schemes, and indexing tools for classifying and cataloging information resources. I also learn about search strategies, search engines, and evaluation criteria for information sources. Collection development covers selection criteria, acquisition processes, and budgeting strategies for libraries and information centers. Information literacy involves teaching others to effectively locate, evaluate, and use information resources. Library management covers staffing, budgeting, facilities management, and strategic planning. As a graduate, I can work in libraries, archives, museums, and information centers.
My Master's training in Information Technology (IT) focused on developing your technical and analytical skills in various areas related to the field of IT. I learned programming languages like Java, Python, and Ruby, as well as frameworks and development methodologies, which are important for creating software applications. I also learned about database management systems, data modeling, and SQL, which are necessary for designing and managing databases for various applications. I learned about networking protocols, security measures, and system administration tools, which are important for designing, deploying, and managing computer networks and systems. Additionally, I learned about data analysis and visualization tools, such as Tableau, which are useful for collecting, processing, and analyzing data to gain insights and make informed decisions. Finally, I gained knowledge in project management methodologies, tools, and best practices, which are necessary for managing IT projects.
Work & Experience
Developed a secure, efficient, and user-friendly Mobile Money Payment System integrating payment gateways with mobile networks for seamless transactions. Designed the system architecture using Java & Spring Boot, ensuring scalability and security. Implemented core functionalities for transaction processing, account management, and API integrations. Managed the MySQL database, optimizing queries for high-volume transactions. Developed RESTful APIs, facilitating smooth front-end integration. Applied encryption techniques to protect financial data and conducted penetration testing to identify security risks. Utilized JUnit for unit and regression testing, ensuring system reliability. Collaborated with cross-functional teams, including product managers and front-end developers, aligning development with business goals. Used Git for version control and maintained clear documentation. Demonstrated strong problem-solving, teamwork, and communication skills throughout the project.
Developed an AI-powered medical image analysis system to detect tumors, fractures, and infections in X-rays, MRIs, and CT scans, improving diagnostic accuracy and reducing radiologists’ workload. Collected and preprocessed medical image datasets using NumPy and scikit-image, ensuring HIPAA compliance. Designed and trained CNN models in TensorFlow, optimizing performance with Optuna and TensorBoard. Implemented data augmentation to enhance model generalization and minimize false positives. Integrated the AI model into a Django web application, ensuring a secure, scalable backend. Deployed on AWS (S3, EC2, CloudWatch) with Docker for seamless updates. Collaborated with radiologists and DevOps engineers to refine predictions, automate testing via CI/CD pipelines, and improve system usability. Monitored performance with CloudWatch, iterating based on feedback. Applied Python, TensorFlow, Django, AWS, and DevOps tools, demonstrating expertise in AI, cloud deployment, and cross-functional collaboration.
Developed an AI-powered personalized treatment recommendation system using patient data, including medical history, genetics, and lifestyle factors, to improve healthcare outcomes. Conducted comprehensive data analysis, integrating diverse datasets while ensuring privacy compliance. Preprocessed data using pandas and NumPy, handling missing values and feature extraction. Designed and trained deep learning models in PyTorch, applying clustering and collaborative filtering for tailored treatment plans. Built ETL pipelines with Apache Spark, optimizing large-scale data processing from EHRs and genetic databases. Developed a Django backend, integrating PyTorch models for real-time recommendations. Managed structured data with PostgreSQL for scalable storage. Collaborated with healthcare experts to validate model accuracy and used Tableau for data visualization and decision-making. Deployed on AWS (EC2, S3, CloudWatch) with Docker, ensuring system scalability and performance monitoring. Demonstrated expertise in AI, data engineering, and healthcare analytics through cross-functional collaboration and iterative improvements.
