Ian Lusule | Software Developer

Hi, I'm Ian Lusule.

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Self-driven, quick starter, passionate programmer with a curious mind who enjoys solving a complex and challenging real-world problems.

About

I am a Computer Science Grad Student at Dedan Kimathi University. I enjoy problem-solving and coding. Always strive to bring 100% to the work I do. I have worked on technologies like Python, Django, Flask, MySQL,MongoDB, HTML5, CSS, Java, C++ during my bachelor's. I have close to a year of practical work experience which helped me strengthen my experience in Python, front and Backend Development. I am passionate about developing complex applications that solve real-world problems impacting millions of users. On my free time I do scripting alot,mainly in python and abit of bash scripts.

Languages: Python, Java, JavaScript, C, HTML/CSS, Bash
Databases: MySQL, MongoDB
Libraries: NumPy, Pandas
Frameworks: Flask, Django, Node.js, PyTorch,Apache Beam
Tools & Technologies: Git, Docker

Looking for an opportunity to work in a challenging position combining my skills in Software Engineering, which provides professional development, interesting experiences and personal growth.

Projects

  
Music Player Web-App A music streaming web app based on Django 
AccomplishmentsTools: Django, HTML, CSS, Bootstrap, SQLite, AWS S3, Heroku
Register/login to the web app(with OAuth-based Google Sign-In).
Search and filter songs based on language and singer.
Create multiple playlists and add/remove songs to/from playlist.
Scroll through recently played/viewed songs.
   
  
Quiz Web-App A quiz playing web app based on Django 
AccomplishmentsTools: Django, HTML, CSS, Bootstrap, SQLite, Heroku
Register/login to the web app(with OAuth-based Google Sign-In).
Play Quiz and see the leaderboard
   
  
Blog Web-App A simple and extensible blog web-app based on Flask. 
AccomplishmentsTools: HTML, CSS, Bootstrap, Flask, Python
Users can view posts and contact the admin via Contact Page.
Admin can Add, Delete, Update posts.
   
  
Visual Question Answering An attention-based classification model that aims at generating an answer for a given input image. 
AccomplishmentsIncorporated Convolution Neural Networks (CNN) for extracting image features and Long Short Term Memory for extracting question embeddings.
Tested the model on the COCO dataset, abstract scenes images, and got 69% overall accuracy on the VQA evaluation metric.
  
  
Video Summarizer A Seq2Seq model that generates a short summary of the given input video. 
AccomplishmentsIncorporated CNN to detect and classify objects in the video frames and Long Short Term Memory for generating a summary.
Evaluated the model on MSVD (Microsoft Video Description Corpus) dataset; achieved 0.77, 0.71, 0.52 scores respectively on ROGUE, BLEU, METEOR evaluation metrics.
  
  
Image Generator An image generator based on the concept of adversarial networks (GANs) 
AccomplishmentsDeveloped system was tested on a human-face database and loss was calculated by comparing the PCAs of generated and original image.
Calculated difference in PCA was less than 10%, depicting the successful generation of an image by the generator.
  
  
Head Counting System A system that calculates the attendance of the class from a panoramic image of a live classroom. 
AccomplishmentsUsed Singular Value Decomposition for image compression; applied various image processing techniques and morphological operations to detect the number of heads.
  