Hi, I'm Abdullahil
AI Engineer | Software Engineer from Berlin, GermanyExperienced software engineer with a strong background in Python, Go, PHP, and SQL optimization, aiming to advance career progress through impactful API development and system migration initiatives. A demonstrable history of improving team efficiency by employing frameworks such as React and Django. A record of contributing to agile teams by fostering innovation and resolving intricate issues, leading to enhanced operations and pioneering solutions. Proficient in developing and refining new systems, with a substantial emphasis on analytical problem-solving and perpetual advancement.
Projects
Here are a few projects I have worked on recently.
Segmenting Audio Data and Analyzing the Credibility of the Speaker with Gender and Emotion Detection
Audio segmentation based on energy level of the audio and detecting the noise part. Classification of gender and emotion with deep learning. Analyzing the authenticity of the audio. Explainable data points in each audio modality to ensure AI explainability. Created a Framework (MFAF) tool to visualise and process audio.
Fake Audio Detection using Deep Learning
Synthetic audio detection using deep learning to prevent spoof attacks. Fake Audio Generation using Variational Autoencoder. Fake Audio Detection using CNN (Residual). Scientific evaluation of accuracy.
MPA Pathway Tool Visualization of Chemical Reactions
Frontend development of a chemical reaction web-application. Built using ReactJS and Graph d3 library. Improved reaction analysis by utilizing Java application to calculate reaction flux.
Integrating GPU Libraries in Database Query Processing
Using GPU to process database queries alongside CPU. OpenCL, CUDA-based database management system. Integrating Boost Compute into the existing system by using VexCL.
Genre Identification on (a subset of) Gutenberg Corpus
Using Machine learning classifying the genres of fictional books. Collected features from fictional corpus to determine genre of the book. Application of four features to train models (LR, Naive Bayes, Random Forest, SGD).
Artificially Intelligent Smart Mirror
Building an AI based smart mirror using Raspberry Pi and AI libraries. Smart mirror based on Raspberry Pi. Usage of AI library (WIT AI). Backend based on Python. Facial recognition with OpenCV.