Summary
Lahari Sengupta is an AI engineer and operations researcher with nine years of experience applying mathematical modeling, MIP and machine learning to large-scale logistics and container terminal problems. She holds a PhD in Computer Science and has translated research on TSP and local search into commercial optimisation engines and revenue-constrained VRP solutions for European freight marketplaces. Comfortable from low-level C/Java to modern Python ML stacks (TensorFlow, PyTorch, scikit-learn), she balances rigorous theory with production deployment and modular software design. Her background ranges from sensor-driven automation projects and GIS web systems to teaching algorithms and ML, reflecting a rare combination of hands-on engineering, empirical research, and pedagogy. Notably, she has built closed-tour VRP engines with economic feasibility constraints and proposed validation frameworks that bridge academic rigor and real-world operations. Based in Kolkata, she continues to blend optimisation research with practical AI solutions for complex routing and scheduling challenges.
9 years of coding experience
14 years of employment as a software developer
Higher Secondary, Science, Higher Secondary, Science at KBNSM
Madhyamik, Madhyamik at BCBBV
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Eastern Finland
M.Tech, Radio Physics & Electronics, M.Tech, Radio Physics & Electronics at University of Calcutta
B.Tech, Electronics & Communication, B.Tech, Electronics & Communication at West Bengal University of Technology, Kolkata
Spanish, German, English, Hindi, Bengali, Finnish