I hold a Master's degree in Data Science and Artificial Intelligence with a strong computational background, bringing over 4+ of experience in developing and deploying AI-driven solutions. My expertise lies on Machine Learning (ML) and deep learning (DL), where I design and implement neural networks, natural language processing systems, and computer vision applications using frameworks like TensorFlow, PyTorch, and Scikit-learn. I'm proficient in Python and R for statistical modeling and predictive analytics, with hands-on experience in algorithm optimization, feature engineering, and model evaluation.
My computational skills extend to handling large-scale data processing with Apache Spark and Hadoop, building ETL pipelines, and leveraging cloud platforms like AWS for scalable AI deployment. I'm passionate about pushing the boundaries of AI whether it's training transformer models, implementing reinforcement learning algorithms, or applying advanced analytics to extract meaningful insights from complex datasets. Beyond the technical work, I excel at translating AI concepts into practical business solutions, leading cross-functional teams, and communicating sophisticated computational methods to both technical and non-technical stakeholders.
0 + Projects completed
A Tech-Savvy with over 4+ experience in software development, project management and technical support with a strong ability to analyze complex daata. Proven expertise in data science, statistical analysis and machine learning algorithms.
Three Mills Bakery, a premium bakery brand specializing in fresh breads, pastries, and high-quality café products with a focus on consistency and quality.
Below are the sample projects on SQL, Python, Laravel, Php, Javascript, R programming & and ML.
Deep learning–based lung nodule segmentation and classification system developed using MAW-Net, wavelet attention, and CNN models on CT scans
Interactive R Shiny dashboard developed for analyzing Australian residential dwelling prices and counts using dynamic filtering, visualizations, and heatmaps.
Classified images from the Fashion MNIST dataset into 10 categories of clothing using logistic regression, achieving high accuracy in predicting the correct class of a given image.
Machine learning–based pricing system developed to predict used smartphone resale values using regression and classification models on historical sales data
Machine learning classification system deployed on AWS SageMaker to identify weather-induced flight delays using US aviation data
Data-driven predictive modelling project analyzing Sydney’s restaurant ecosystem using EDA, regression, and classification models to predict pricing and ratings
An android application with a real-time speech recognition system that transcribes spoken words into text with minimal latency.
Developed an effective backend system to handle Netflix accounts, track orders & offer real-time updates to customers
Below are the details to reach out to me!
Canberra, ACT