Hello, my name is
Bisaam Amir
Data Scientist
- [email protected]
- +447780758827
- linkedin.com/in/bisaam
- github.com/BisaamAmir
About me
I am a passionate Data Analyst with a strong background in Artificial Intelligence, Data Science, and Machine Learning. With hands-on experience in cutting-edge technologies and a commitment to continuous learning, I strive to turn data into actionable insights and innovative solutions. Whether it's developing sophisticated machine learning models, optimizing data pipelines, or visualizing complex datasets, I bring creativity and precision to every project. Explore my portfolio to discover how I can contribute to your next big challenge.
I Turn Data into Impact
As a Data Analyst with expertise in Artificial Intelligence and Machine Learning, I specialize in transforming complex datasets into meaningful insights. My work involves developing and deploying machine learning models using techniques like GANs, RNNs, CNNs, and LLMs to solve diverse challenges. I am skilled in building data pipelines, performing advanced statistical analysis, and visualizing data through tools like Tableau and PowerBI. My proficiency in Python, C/C++, SQL, and R, combined with experience in cloud platforms like AWS and Google Cloud, enables me to design efficient, scalable solutions. With a strong foundation in mathematics, computer vision, and natural language processing, I am dedicated to leveraging data to drive informed decision-making and innovation.
Education
2023
Birmingham City University
Master's in Artificial Intelligence
Modules: Machine Learning (Merit), Applied Artificial Intelligence (1st), Deep Learning (2:1), Data Visualisation (2:1), Impact of AI (1st)
Project: Implemented U-Net and Duck-Net deep learning architectures for precise medical image segmentation using Python and compared both convolutional neural networks CNNs on CVC-ClinicDB dataset available through Kaggle. Yielded a Dice Coefficient of 0.91 with slight modifications to the original Duck-Net architecture (1st)
2019
National University of Science and Technology (NUST)
Bachelors of Engineering in Electrical Engineering
Modules: Object Oriented Programming (1st), Data Structures and Algorithms (1st), Digital Signal Processing (1st), Digital Logic Design (1st), Microprocessor Systems (1st), Embedded System Design (1st).
Project: Automated Identification of Abnormal EEG (Enhanced the accuracy of the chronoNET algorithm for identifying abnormal EEG patterns using deep learning techniques. Contributed to advancements in EEG analysis using Deep Neural Networks)
What I do
I turn complex data into actionable insights and innovative solutions. From analyzing trends and building predictive models to automating industrial processes, I harness the power of data and technology to solve real-world challenges efficiently and effectively. My expertise spans Data Analysis, Machine Learning/AI, Embedded Systems, Automation, and SEO, allowing me to approach problems from multiple angles and deliver comprehensive results.
Data Analysis
Transforming complex datasets into actionable insights using tools like Python, SQL, Tableau, and PowerBI.
Machine Learning & AI
Developing and deploying advanced machine learning models like GANs, RNNs, CNNs, and LLMs using TensorFlow, Keras, and PyTorch.
Embedded Systems
Designing and implementing hardware-software integration solutions with expertise in C/C++, MATLAB, AutoCAD, and Proteus.
Automation
Streamlining industrial processes through the automation of machinery using PLCs, HMIs, and advanced control systems.
SEO
Enhancing digital presence through data-driven SEO strategies, combining technical optimization and content strategy for improved search rankings.
Top Skills
Other Skills
My Experience
2022-2024
Chipman Ltd
Data Analyst and Operations Coordinator
Lead data analysis on customer orders, preferences, and sales trends to support strategic decision-making. Utilize natural language processing for sentiment analysis, optimize inventory levels, and create data visualizations to communicate insights and drive operational efficiency.
2021-2022
Al-Rehman Internationals
Data Science and Engineering Manager
Led the engineering department to optimize machine performance through data-driven insights and predictive maintenance. Spearheaded R&D initiatives, leveraging machine learning algorithms to innovate machinery and implementing modifications based on data analysis to enhance technology standards.
2019-2021
Style Textile
Assistant Manager
Conducted R&D to advance automation processes using machine learning algorithms. Oversaw the commissioning of new machinery, managed predictive maintenance, and implemented compliance initiatives to enhance operational efficiency and ensure adherence to industry standards.
Projects
Explore a diverse range of projects where I’ve applied my expertise in data analysis, machine learning, automation, and embedded systems. Each project showcases my ability to tackle complex problems, innovate solutions, and deliver impactful results across various domains.
Medical Image Segmentation
Conducted a comparative analysis of U-Net and Duck-Net deep learning architectures for precise medical image segmentation, demonstrating the superior performance of later, contributing to advancements in medical image analysis. Demonstrated proficiency in deep learning techniques and data management within the critical context of AI in healthcare.
Abnormal EEG Identification
Worked on improving accuracy of chronoNET algorithm to identify abnormal EEG. This project falls in the domain of deep learning. For more details on this project, read my Thesis.