Nafisa Tabassum is a Lecturer in the Department of Civil Engineering at United International University (UIU), where she has been teaching since March 1, 2021. She is actively involved in curriculum development and academic committees, serving as a member of the curriculum and accreditation committees. Prior to joining UIU, she worked as a Lecturer in the Department of Civil Engineering at Stamford University Bangladesh from January 2019 to February 2021.

She holds an M.Sc. in Civil Engineering (Transportation Engineering) from Bangladesh University of Engineering and Technology (BUET) and an M.Sc. in Applied Statistics and Data Science (MASDS) from Jahangirnagar University. She completed her B.Sc. in Civil Engineering from BUET, specializing in Structural Engineering with a minor in Transportation Engineering.

Her research expertise lies in transportation planning, machine learning applications in transportation, urban mobility, and service quality assessment. For her M.Sc. in Civil Engineering, she developed trip production and attraction models for urban educational institutions in Dhaka using XGBoost and Random Forest, comparing their performance with traditional approaches.

Her MASDS research focused on demographic-based tree modeling to analyze public bus service quality in Dhaka, providing insights into service variations across user segments and offering data-driven policy recommendations.

Her undergraduate thesis focused on built-up steel-concrete composite sections, where she analyzed material property relationships, validated numerical modeling using Abaqus, and evaluated the reliability of design codes such as AISC and EUROCODE. A conference paper based on this work received the Best Paper Award in the Structural Engineering Division.

Beyond academia, she gained industry experience as a Research Assistant in the “Building Code Implementation and Enforcement Strategy” project at BUET, where she worked on practical applications of engineering policies and regulations.

She is proficient in Python, R, STATA, SPSS, VISSIM (for traffic simulation), Abaqus (for structural modeling), SAS, and Minitab. Her technical expertise includes machine learning frameworks, statistical analysis methods, and transportation modeling techniques. With a strong background in data-driven transportation research and engineering applications, she continues to contribute to academia through research, teaching, and curriculum development.

• MSc., Transportation Engineering, Bangladesh University of Engineering and Technology.
• Masters in Applied Statistics and Data Science, Jahangirnagar University.
• BSc., Major in Structural Engineering & Minor in Transportation Engineering, Bangladesh University of Engineering and Technology.
• HSC, Science, Chittagong College, Chittagong.
• SSC, Science, Dr. Khastagir Government Girls’ High School, Chittagong.

• Transportation planning and policy
• Machine learning applications in transportation engineering
• Urban mobility and travel behavior modeling
• Trip generation and travel demand forecasting
• Service quality assessment in public transportation
• Statistical modeling and data-driven decision-making in transportation

• Lecturer, Department of Civil Engineering, United International University. (March 01, 2021 to present)
• Lecturer, Department of Civil Engineering, Stamford University Bangladesh. (January 17, 2019 to February 28, 2021)
• Research Assistant, BUET. (November 16, 2018 to January 16, 2019).

Ms. Nafisa Tabassum has experience of teaching these courses:

• Engineering Mechanics
• Engineering Materials
• Engineering Materials
• Mechanics of Solids I
• Mechanics of Solids II
• Structural Analysis and Design I
• Design of Concrete Structures I
• Design of Concrete Structures II
• Prestressed Concrete
• Engineering Geology and Geomorphology
• Civil Engineering Drawing I
• Computer Aided Drafting
• Engineering Materials Sessional
• Concrete Structures Design Sessional I
• Concrete Structures Design Sessional II
• Highway Design and Railway Engineering
• Highway Materials and Traffic Engineering Design Lab