Harshavardhini Selvaraajan

Role across the career: Integrating advanced document retrieval and natural language processing (NLP) capabilities to guarantee contextually accurate responses to a wide range of maritime-related inquiries. Innovating interactive feedback functionalities, enabling users to refine chatbot responses and contributing to continuous improvements in accuracy and user satisfaction. Collaborating with cross-functional teams to identify and address operational challenges, ensuring seamless integration of AI solutions into existing workflows. Conducting comprehensive testing and validation of machine learning models, ensuring optimal performance and reliability in real-world applications, while implementing CI/CD pipelines using Kubernetes and GitHub for streamlined deployment. Developing and maintaining robust data pipelines to ensure efficient collection, transformation, and analysis of large datasets, enabling real-time insights and decision-making. Implementing advanced machine learning techniques for anomaly detection, enhancing system monitoring and proactively identifying potential issues before they impact operations. Designing and optimizing data storage architectures to support large-scale data processing and ensure high availability for real-time applications. Leading efforts to automate and streamline business processes through AI-driven tools, reducing operational bottlenecks and improving overall productivity. Developing a comprehensive user feedback analysis system using sentiment analysis to gauge customer satisfaction, leading to actionable insights for product improvement. Key Achievements: Played a key role in driving projects across both Indian and Singaporean markets, enhancing adaptability and cross-cultural collaboration skills. Enhanced user engagement metrics through the implementation of interactive feedback mechanisms, leading to improved customer satisfaction ratings. Streamlined operational workflows, resulting in reduction in response times for customer inquiries, significantly enhancing overall service delivery. Recognized for excellence in project delivery, consistently achieving project milestones on time and within budget constraints. Contributed to reduction in operational costs through the application of data-driven insights and predictive maintenance techniques. Vessel Reporting Chatbot for Maritime Operations | Dec 2024 - Present Developed and deployed a scalable Vessel Reporting Chatbot on AWS to enhance customer support and operational efficiency. Deployed on AWS for scalability, availability, and secure query handling. Implemented a two-step response system: immediate Slack acknowledgment followed by detailed responses through background processing. Integrated robust document retrieval and NLP to ensure accurate maritime-related responses. Added interactive feedback functionality to improve response accuracy based on user input, continuously refining the chatbot. Projects; Tech: Python, Slack Bolt API, FastAPI, LLM, Asyncio, Docker, AWS. Advanced Hull Performance Analytics | Dec 2023 - Present Developed a Hull Performance Module to optimize fuel consumption, reduce operational costs, and enhance vessel longevity. Used machine learning to monitor hull performance, providing actionable insights for optimizing fuel use. Integrated predictive maintenance techniques for accurate dry-dock scheduling, reducing downtime and improving operational efficiency. Tech: Pandas, NumPy, Scikit-Learn, TensorFlow, Matplotlib, Seaborn, Plotly, AWS. AI Data Assurance Tool | Jan 2024 - Apr 2024 Created a custom AI tool using Langchain to interface with internal APIs, automating data availability checks across business processes. Integrated Generative AI for real-time feedback on data accessibility, streamlining data verification, and reducing delays. The tool improved system responsiveness and reduced manual intervention, enhancing workflow efficiency and business continuity. Tech: Python, Langchain, Hugging Face Transformers, Pandas, Numpy.

Role across the career: Integrating advanced document retrieval and natural language processing (NLP) capabilities to guarantee contextually accurate responses to a wide range of maritime-related inquiries. Innovating interactive feedback functionalities, enabling users to refine chatbot responses and contributing to continuous improvements in accuracy and user satisfaction. Collaborating with cross-functional teams to identify and address operational challenges, ensuring seamless integration of AI solutions into existing workflows. Conducting comprehensive testing and validation of machine learning models, ensuring optimal performance and reliability in real-world applications, while implementing CI/CD pipelines using Kubernetes and GitHub for streamlined deployment. Developing and maintaining robust data pipelines to ensure efficient collection, transformation, and analysis of large datasets, enabling real-time insights and decision-making. Implementing advanced machine learning techniques for anomaly detection, enhancing system monitoring and proactively identifying potential issues before they impact operations. Designing and optimizing data storage architectures to support large-scale data processing and ensure high availability for real-time applications. Leading efforts to automate and streamline business processes through AI-driven tools, reducing operational bottlenecks and improving overall productivity. Developing a comprehensive user feedback analysis system using sentiment analysis to gauge customer satisfaction, leading to actionable insights for product improvement. Key Achievements: Played a key role in driving projects across both Indian and Singaporean markets, enhancing adaptability and cross-cultural collaboration skills. Enhanced user engagement metrics through the implementation of interactive feedback mechanisms, leading to improved customer satisfaction ratings. Streamlined operational workflows, resulting in reduction in response times for customer inquiries, significantly enhancing overall service delivery. Recognized for excellence in project delivery, consistently achieving project milestones on time and within budget constraints. Contributed to reduction in operational costs through the application of data-driven insights and predictive maintenance techniques. Projects. Cargo Planning - Decision Support System (CP-DSS) | Dec 2021 - Nov 2023 Developed a decision support system for VLCC, Suezmax, and Aframax vessels to automatically generate optimized loading and discharge plans. Used constrained optimization to balance cargo load, ensuring vessel stability and maximizing efficiency. Integrated operational sequences for both loading and discharging processes to improve overall operational efficiency and safety. Tech: Python, Numpy, Pandas, AMPL, Gurobi.