Research

Research Interests: Humanitarian Logistics, Stochastic Optimization, Machine Learning

• Click the link to visit my ResearchGate profile: Researchgate

• All of the drafts are added below:

• As The fact that I discovered the common domain between ML and IE, as an industrial engineer, is my competitive advantage in higher studies. This is because selection procedures for higher studies have always been competitive. Accordingly, my thesis is on a Multi-objective Multi-Echelon Humanitarian Logistics Model with Branch and Cut Algorithm. Based on my thesis topic, my conference paper has been accepted for the IEOM 2022 conference taking place in March in Turkey. In this model, transportation costs, facility location costs, and warehouse costs are minimized, along with providing optimal routes for vehicles at the lowest cost. Coding of the entire model was done in IBM ILOG CPLEX optimizer 20.1 version. The whole process from scratch to top was my first grasp at writing a complete code for a real-life problem, and I really enjoyed the process.

• Certificate of Participation:

• Having Dr. Ferdous Sarwar as my thesis advisor helped me stay focused and motivated throughout my undergraduate career. In addition, he encourages the pursuit of knowledge in the fields of optimization, data analysis, and machine learning. After that, I worked with my supervisor on a project called "Customer segmentation and satisfaction level prediction of e-commerce sectors -- A machine learning method," which is presently being peer-reviewed in a publication. Customer satisfaction levels are predicted using robust principal component analysis, K-medoid and SVM algorithms, all of which are used in this work.