Debanjan Naskar

A highly adaptable and motivated computer science engineer with a keen eye for detail, a disciplined approach to coding and debugging, and proven capabilities in Machine Learning research and software development. Seeking to leverage former experience and unrivaled enthusiasm to build an exceptional ML model and take on innovative projects for a company that values excellence and forward-thinking.

• NPTEL online certification in DBMS, 02/01/18
• Spoken Tutorial online certification in RUBY, 11/01/18
• Value-added training program in programming aptitude, DSA, and OOPs concept, 01/01/18 (GLOBSYN SKILLS)

Thesis title: An AP(access point) placement strategy for fingerprint-based indoor localization, (2022-2023)

Proposed work: My proposed work focuses on addressing the problem of finding the optimal placement of Access points (APs) to improve AP coverage for a specific set of location points, while minimizing number of APs required. The problem is formulated as a weighted graph coloring problem, where each location point is represented as a node in the graph and the goal is to assign APs (colors) to the nodes in a way that minimizes interference and maximizes location ability. To solve this problem the proposed algorithm called GLOC_coloring, is introduced. The algorithm begins by applying a machine learning classifier to obtain a confusion matrix which is used to create a weighted graph.The objective was to achieve accurate localization with minimal error, ideally 2.5 meters and my proposed algorithm successfully achieved it.