Avinash Navlani

Designed and implemented an Integer Programming model to optimize road tanker routing and scheduling, enhancing efficiency in daily order fulfillment from depots to terminals. Developed a flexible rescheduling logic for manual adjustments, allowing business users to modify schedules in real time.

Designed and implemented an Integer Programming model to optimize road tanker routing and scheduling, enhancing efficiency in daily order fulfillment from depots to terminals. Developed flexible rescheduling logic for real-time schedule adjustments.

Developed and deployed price optimization models for retail clients, improving pricing strategy through demand forecasting and mixed-integer programming (MILP). Responsible for model development, evaluation, and deployment on the Azure Cloud Platform.

Developed Custom NER models to extract entities from medical claim PDF documents, enhancing the efficiency of data processing in the health insurance domain.

Created a time series forecasting algorithm for retail anomaly detection, capturing seasonal trends and sudden changes. Developed opinion mining solutions for a fast-food chain, extracting actionable insights on customer satisfaction.

Developed predictive models for candidate engagement and satisfaction levels during online assessments, deployed on a cloud environment for real-time analysis. Created an NLP-based 'NLP Brain' to detect entities from RSS feeds.

Involved in teaching and curriculum development for data science and analytics courses such as MTech, MSc, and MBA courses, contributing to the academic growth of students in data analytics.

Worked on a research project 'Towards an Automated Adaptive and Compliance Audit System' in collaboration with the University of New South Wales, developing a compliance audit system prototype.

Focused on advanced data analysis, decision analysis, operations, and technology management principles.

Completed a rigorous program in Information Technology fundamentals and applications.