Yahya Almardeny

Analysis and modelling of telematics data.
Mathematical derivation and Statistical analysis of the Online Metrics.
Manipulating high-volume from varying sources to highlight patterns, anomalies, and relationships.
Applying machine learning methodology and techniques.
Analysis and fusion of crowdsourced data.
Producing key insights for business and product owners to pursue Zero Crashes, Zero Emissions, and Zero Congestion.
Building data visualisations to summarise the conclusion of the advanced analysis.
Supervising and providing guidance/consultation to other developers and scientists.

▪ Analysis and modelling of telematics data.
▪ Mathematical derivation and Statistical analysis of the Online Metrics.
▪ Manipulating high-volume from varying sources to highlight patterns, anomalies, and relationships.
▪ Applying machine learning methodology and techniques.
▪ Analysis and fusion of crowdsourced data.
▪ Producing key insights for business and product owners to pursue Zero Crashes, Zero Emissions, and Zero Congestion.
▪ Building data visualisations to summarise the conclusion of the advanced analysis.
▪ Supervising and providing guidance/consultation to other developers and scientists.

Analysis and modelling of telematics data
Mathematical derivation and Statistical analysis of the Online Metrics
Manipulating high-volume from varying sources to highlight patterns, anomalies, and relationships
Applying machine learning methodology and techniques
Analysis and fusion of crowdsourced data
Producing key insights for business and product owners to pursue Zero Crashes, Zero Emissions, and Zero Congestion
Building data visualisations to summarise the conclusion of the advanced analysis
Supervising and providing guidance/consultation to other developers and scientists

Developing and operating a real-time analytics platform for automated driving development.
Building APIs for data consumption and machine learning modelling.
Data Pre-processing, Cleaning and Statistical Analysis.
Collecting and processing big data from a vast fleet of vehicles.
Building distributed data streaming systems and applying big data systems enhancements.
Developing real-time deep learning systems ML algorithms.
Supervising and providing guidance/consultation to new developers and engineers.

Applying feature transformations for machine learning models on new data.
Designing and implementing the ML programs and working on frameworks.
Developing deep learning systems for various use cases based on business needs.
Undertaking machine learning experiments and Fine-tuning test results.
Testing and continuously improving the accuracy of the ML models to ensure optimised performance.

Delivering modules: Data Structures and Algorithms for two programs: BSc in Computing and NUIST.
Demonstrating the practical implementation and design of the data structures and the algorithms.
Monitoring the students’ performance and providing the required assistance in the class/lab.
Writing the exam questions, interviewing students, and correcting exam answers.
Participating in the board meetings and future planning and curriculum.

Implementing the sensors models from their datasheets.
Running and testing the Pythonic system on Raspberry Pi and its configurations.
Hardware Connectivity of the devices and sensors on the breadboard.
Developing the server-side and middleware using NodeJS.
Developing the data visualisation interface and its real-time charts for the end-users.
Deploying the system and collecting and analysing data received in real time.

Developing and operating a real-time analytics platform for automated driving development
Building APIs for data consumption and machine learning modelling
Data Pre-processing, Cleaning and Statistical Analysis
Collecting and processing big data from a vast fleet of vehicles
Building distributed data streaming systems and applying big data systems enhancements
Developing real-time deep learning systems ML algorithms
Supervising and providing guidance/consultation to new developers and engineers

Applying feature transformations for machine learning models on new data
Designing and implementing the ML programs and working on frameworks
Developing deep learning systems for various use cases based on business needs
Undertaking machine learning experiments and Fine-tuning test results
Testing and continuously improving the accuracy of the ML models to ensure optimised performance

Delivering modules: Data Structures and Algorithms for two programs: BSc in Computing and NUIST
Demonstrating the practical implementation and design of the data structures and the algorithms
Monitoring the students’ performance and providing the required assistance in the class/lab
Writing the exam questions, interviewing students, and correcting exam answers
Participating in the board meetings and future planning and curriculum

Implementing the sensors models from their datasheets
Running and testing the Pythonic system on Raspberry Pi and its configurations
Hardware Connectivity of the devices and sensors on the breadboard
Developing the server-side and middleware using NodeJS
Developing the data visualisation interface and its real-time charts for the end-users
Deploying the system and collecting and analysing data received in real time