West New York, NJ

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About Me

Greetings, I'm Tanvir Ahamed, a Data Science and Operations Research Specialist based in West New York, NJ. I specialize in developing high-performance algorithms and heuristics for solving complex OR problems. Additionally, I have extensive experience managing and analyzing large datasets, using visualization tools to identify patterns, and deploying cutting-edge decision support tools.

Throughout my career, I have had the privilege of being involved in the modernization of optimization tools, which have played a vital role in enabling Jet Ownership business to achieve revolutionary new business model goals. In addition to this, I have made valuable contributions to the advancement of research in Supply Chain and Logistics. More specifically, I have been instrumental in developing highly effective planning and scheduling tools for jet ownership services, as well as pushing the boundaries of research in last-mile delivery to expand knowledge in the field. I am dedicated to utilizing my skills and experience to continue making significant contributions to these areas and beyond.

Industry Experience

• Developed efficient planning and scheduling heuristic for Wheels Up's jet ownership services.
• Demonstrated value of flex-related implementation style and parameters.
• Proposed alternative crew rest scenarios and reported operational impact, leading to changes in crew duty hours for July 2022.
• Modernized legacy Optimizer Engine by replacing CPLEX with GUROBI for Virtual Machine usage.
• Contributed to the development of a Crew Scheduling Optimizer to optimize crew resource allocation.
• Improved Optimizer Engine functionality by editing, debugging, and experimenting with existing features.

Research Contributions

• Investigated efficient crowdsourcee-request assignment and relocating idle crowdsourced individuals for distributed on-demand crowdsourced delivery.
• Developed a deep reinforcement learning approach for efficient crowdsourcee-request assignment and a comprehensive and novel characterization of crowdshipping system states.
• Built a queueing network-based framework to optimize crowdsourced urban delivery systems and determined the optimal pool size of crowdsourcees to meet given shipping requests.
• Conducted research on pricing behavior in spot markets, and provided recommendations to logistics company on future pricing strategies.