Projects

projects

2024

Outlier.ai

Data Annotation

As an expert contributor on Outlier.ai, I have had the opportunity to work on a wide range of data annotation tasks. Each project presents its own set of challenges and learning opportunities, keeping the work engaging and fulfilling. The platform’s emphasis on RLHF and SFT methodologies ensures that every contribution directly impacts the performance and quality of the AI systems we help train.

2023

Birmingham City University

Medical Image Segmentation

As my dissertation for my Master's degree at Birmingham City University, I implemented U-Net and Duck-Net deep learning architectures for precise medical image segmentation using Python and compared both convolutional neural networks CNNs on the CVC-ClinicDB dataset available through Kaggle. Yielded a Dice Coefficient of 0.91 with slight modifications to the original Duck-Net architecture

2021

Style Textile (Pvt) Ltd.

Heat Recovery Unit Erection and Automation

At Style Textile, I led the automation of a heat recovery unit to enhance energy efficiency in the dyeing process. Using advanced PLC and HMI systems, I designed and implemented an automated control mechanism to recover heat from waste warm water and use it to preheat incoming fresh water. This innovation reduced the facility’s reliance on conventional energy sources, resulting in annual savings of over £1 million in coal costs and a 20% reduction in carbon emissions. Collaborating with German engineers during commissioning, I ensured adherence to international quality standards, showcasing my ability to deliver sustainable engineering solutions.

2021

Style Textile (Pvt) Ltd.

Dyeing Plant Automation

Automated the plant's operational processes using Orgatex and Lawer systems for automated dye and chemical dispensing. Implemented real-time monitoring systems for predictive maintenance and operational efficiency. Reduced production downtime and improved operational accuracy through data-driven solutions.

2020

Style Textile (Pvt) Ltd.

Machine Erection and Commissioning

Led the commissioning of several high-tech dyeing machines, including Orgatex and Lawer systems, ensuring smooth integration with existing systems. Coordinated with vendors and internal teams to complete the project 20% ahead of schedule, reducing downtime by 25%. Utilised data analysis techniques to improve machine uptime by 30%, enhancing production capacity and reducing operational costs.

2019

National University of Science and Technology (NUST)

Automated Identification of Abnormal EEG

As my final year project for my Bachelor's degree at NUST, I did research on enhancing the accuracy of the chronoNET algorithm for identifying abnormal EEG patterns using deep learning techniques. This research contributed to advancements in EEG analysis using Deep Neural Networks