Dhanesh Rodriguse

• Served as the primary liaison for ERP and iCABS software, facilitating and enhancing operations across PAN India branches
• Proficiently employed visualization tools and Google Sheets to extract, analyze, and present tailored data-driven reports aligning with diverse business requirements
• Efficiently managed SLA tickets through ServiceNow, ensuring prompt issue resolution and adherence to service level agreements
• Spearheaded comprehensive data collection, cleansing, and migration for the integration of the newly acquired Canon Hygiene business
• This successful integration led to a substantial revenue increase of $100 million
• Led the implementation of transformative process enhancements for key business portals (e.g., Service Docket Management, Termination Portal, Invoicing) in Microsoft Dynamics Nav, resulting in heightened operational efficiency and effectiveness.

• Grade: Second Class Honors 2:1 – 64%
• Thesis: Future Sales Prediction using Machine Learning and Deep Learning Techniques. Researched advanced machine learning and deep learning techniques using the Amazon Sales Dataset to develop robust sales prediction models based on diverse attributes. Explored methods like attention mechanisms, GNNs, RNNs, LSTM networks, ARIMA, and VAR models, showcasing the superior predictive accuracy of deep learning over traditional models. Demonstrated the effectiveness of these techniques in different scenarios and evaluated ensemble methods to enhance forecasting accuracy, contributing to informed decision-making and optimized resource allocation in businesses.

• Grade: Second Class – 59%
• Thesis: Mona - Secure Multi-Owner Data Sharing for Dynamic Groups in the Cloud. This project proposes a secure multi-owner data sharing scheme for dynamic groups in the cloud. By combining group signature and dynamic broadcast encryption techniques, Mona enables anonymous data sharing among cloud users. The project was implemented using J2EE as the coding language and MYSQL as the database management system.

• Grade: First Class – 73.16%
• Thesis: Airline Reservation System. Developed an airline reservation system utilizing ASP.NET as the front-end framework and MS-Access as the back-end database. The system allowed users to book and manage flights, view seat availability, and generate e-tickets, providing a user-friendly and efficient solution for airline reservation management.

Grade: Second Class – 59%

Grade: First Class – 66%