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About

A research scientist, who is confident and well-versed in advanced Data Science and DBMS literacy empowered by numerous tools/platforms and in-house scriptings, hosted in both High-performance Computing and Cloud environments. Ever-enthusiast to contribute to enhancing peoples' lives and experiences by applying Artificial Intelligence, Machine Learning, and Deep Learning. Key skills: Artificial Intelligence | Deep Learning | Data Science | Bioinformatics | Technical Skills: • R&D technologies: Full-stack Data Science literacy | Nextflow | Keras | Pytorch | Data Analysis | Machine learning | Data analysis | Computational cancer genomics | Computational Biology | Bioinformatics | NGS | Data integration | Bayesian statistical modelling | Natural language generation | Artificial intelligence | MCMC sampling | Bayesian Network | WinBUGS | JAGS | NeticaJ APIs | AgenaRisk APIs • Programming languages: C#.Net | VB.Net | Java/J2EE | Python | MATLAB | C | R • Web technologies: ASP.Net MVC | REST | Web APIs | HTML | CSS3 | JavaScript | Jquery | D3.js | Ajax | XML | JSON | Xampp • IDEs: VSCode | MS Visual Studio | Eclipse | Xamarin | IntelliJ Idea | Xcode | RStudio | Shiny | PyCharm • Database technologies: MongoDB | Microsoft SQL Server | Oracle | MySQL | MS Access | ADO.Net | ODBC | OLE DB • Version control and collaboration tools: Git | GitHub | Bitbucket • Development platforms: Windows | Linux | Mac | IOS • Teaching experience: 5+ years of teaching experience as a teaching associate at Monash University (Artificial Intelligence | Algorithmic problem solving | Algorithms and programming | Introduction to computer science | Discrete mathematics | Techniques for modelling | Research Methods) Career Summary: • Adept in research, analysis, and software development including design, implementation, debugging, integration and testing • 4+ years of proven Australian experience in software development and research work • Highly adept in Agile software development lifecycle (SDLC) in large-scale enterprise solutions • Extensive research experience in the area of computational biology, bioinformatics, machine learning, data analysis and statistical modeling • 14+ years of active involvement in programming, algorithm development, and experienced in solving complex problems • Flexible, organized and excellent team player with quick learning ability to adapt to rapidly changing technological challenges

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Skills

Experience

Organization
Assistant Professor

Imam Muhammad ibn Saud Islamic University

Oct-2022 to Present

Publication

  • dott image November, 2024

LandSin: A differential ML and google API-enabled web server for real-time land insights and beyond

LandSin, a web application with a back-end database, is developed for global land value estimation by combining polynomial regression and differential privacy models. Leveraging local amenit...

  • dott image Alauddin Sabari
  • dott image November, 2024

LandSin: A differential ML and google API-enabled web server for real-time land insights and beyond

LandSin, a web application with a back-end database, is developed for global land value estimation by combining polynomial regression and differential privacy models. Leveraging local amenit...

  • dott image October, 2024

Multi-View Soft Attention-Based Model for the Classification of Lung Cancer-Associated Disabilities

Background: The detection of lung nodules at their early stages may significantly enhance the survival rate and prevent progression to severe disability caused by advanced lung cancer, but i...

  • dott image August, 2024

ASDNet: A robust involution-based architecture for diagnosis of autism spectrum disorder utilising eye-tracking technology

Journal : IET Computer Vision

Autism Spectrum Disorder (ASD) is a chronic condition characterised by impairments in social interaction and communication. Early detection of ASD is desired, and there exists a demand for t...

Deep and Shallow Learning Model-Based Sleep Apnea Diagnosis Systems: A Comprehensive Study

Sleep apnea (SA) is one of the most prevalent sleep-related problems, impacting more than 100 million people worldwide. A full-night Polysomnography (PSG) is an effective SA diagnosis strate...

Exploring gene regulatory interaction networks and predicting therapeutic molecules for hypopharyngeal cancer and EGFR-mutated lung adenocarcinoma

Journal : FEBS Open Bio

Hypopharyngeal cancer is a disease that is associated with EGFR-mutated lung adenocarcinoma. Here we utilized a bioinformatics approach to identify genetic commonalities between these two di...

An effective screening of COVID-19 pneumonia by employing chest X-ray segmentation and attention-based ensembled classification

Journal : IET Image Processing

Quick and accurate diagnosis of COVID-19 is crucial in preventing its transmission. Chest X-ray (CXR) imaging is often used for diagnosis, however, even experienced radiologists may misinter...

Deep and Shallow Learning Model-Based Sleep Apnea Diagnosis Systems: A Comprehensive Study

Sleep apnea (SA) is one of the most prevalent sleep-related problems, impacting more than 100 million people worldwide. A full-night Polysomnography (PSG) is an effective SA diagnosis strate...

Single-cell RNA-seq data analysis reveals functionally relevant biomarkers of early brain development and their regulatory footprints in human embryon...

The complicated process of neuronal development is initiated early in life, with the genetic mechanisms governing this process yet to be fully elucidated. Single-cell RNA sequencing (scRNA-s...

  • dott image January, 2024

ASDNet: A robust involution-based architecture for diagnosis of autism spectrum disorder utilising eye-tracking technology

Journal : IET Computer Vision

Autism Spectrum Disorder (ASD) is a chronic condition characterised by impairments in social interaction and communication. Early detection of ASD is desired, and there exists a demand for t...