Efficient Machine Learning Frameworks for Strengthening Cybersecurity in Internet of Medical Things (IoMT) Ecosystems
Developed a cutting-edge Intrusion Detection System for IoMT devices, combining machine learning and efficient design to safeguard healthcare ecosystems against advanced cyber threats.
Exploring the Generalizability of Transfer Learning for Camera Trap Animal Image Classification
Designed a deep learning-powered solution to streamline wildlife conservation by automating the classification of camera trap images, enhancing species monitoring and ecological research.
Efficacy of Transformer Models on Colorectal Gland Segmentation
Investigating the power of transformer-based models for colorectal gland segmentation to advance precision in medical imaging and cancer diagnostics.
Analysis and Classification of Flocking Behavior in Swarms
Utilized machine learning to analyze and classify flocking behavior in swarm robotics, advancing applications like search and rescue, military operations, and dynamic simulations
Exploring the Effects of Global CO2 Emissions on Food Insecurity
Analyzed the global impact of CO2 emissions on food insecurity, uncovering actionable insights to address climate change and ensure sustainable food systems.
Analyzing Factors that Contribute to a Country’s Overall Welfare
Ranked countries based on economic, health, and environmental factors using Unsupervised Learning Methods, uncovering key drivers of quality of life globally
Predicting Click-Through Rates for Smarter and More Effective Ad Campaigns
Optimized display ad performance prediction using advanced Feature Engineering and various Machine Learning Models, achieving impactful insights for digital marketing strategies
Forecasting Germany’s Real GDP with ARIMA Modeling
This project applies a univariate ARIMA model to forecast Germany’s Real GDP and evaluates its performance against random walk forecasts. By analyzing decades of economic data, this study highlights the power of time series modeling in economic forecasting.
