Mr. Md Nazmus Shakib | Green University of Bangladesh

Mr. Md Nazmus Shakib

Lecturer

 

B.Sc. in Computer Science and Engineering

Institution: Khulna University of Engineering & Technology (KUET)
Duration: 2017-2022
Result: Degree with Honors

Higher Secondary Certificate (H.S.C)

Institution: Govt. Azizul Haque College, Bogura
Duration: 2014-2016
Result: GPA 5.00 out of 5.00

Secondary School Certificate (S.S.C)

Institution: Bogura Zilla School, Bogura
Duration: 2006-2014
Result: GPA 5.00 out of 5.00

 

 

Lecturer in Computer Science and Engineering (CSE)

Institution: Green University of Bangladesh (GUB)
Duration: June 01, 2022 – present
Responsibilities: Teaching and Research

Course Conduction:

Fall 2024 (Current):

  • Object Oriented Programming (Theory+Lab)
  • Microprocessor and Micro-controller (Theory+Lab)
  • Algorithm (Lab)

Spring 2024 :

  • Algorithms (Theory+Lab)
  • Database Systems (Theory+Lab)

Fall 2023:

  • Computational Thinking and Problem Solving Lab
  • Object Oriented Programming (Theory and Lab)
  • Database System Lab
  • Data Mining
  • Artificial Intelligence Lab

Spring 2023:

  • Object Oriented Programming (Theory and Lab)
  • Digital Logic Design
  • Artificial Intelligence Lab

Fall 2022:

  • Object Oriented Programming
  • Digital Logic Design Lab
  • Computer Network
  • Artificial Intelligence (Theory and Lab)

Summer 2022:

  • Microprocessor & Microcontroller Lab
  • Data Communication Lab
  • Information System & Design Lab
  • Data Mining (Theory and Lab)

 

 

International Conference Papers

  1. M. N. Shakib, M. Shamim, M. N. H. Shawon, M. K. F. Isha, M. Hashem, and M. Kamal (2021). An Adaptive System for Detecting Driving Abnormality of Individual Drivers Using Gaussian Mixture Model. 2021 5th International Conference on Electrical Engineering and Information Communication Technology (ICEEICT) (pp. 1-6). IEEE. [Best Paper Award]. Read Paper
  2. M. K. F. Isha, M. N. H. Shawon, M. Shamim, M. N. Shakib, M. Hashem, and M. A. S. Kamal (2021). A DNN Based Driving Scheme for Anticipative Car Following Using Road-Speed Profile. 2021 IEEE Intelligent Vehicles Symposium (IV) (pp. 496-501). IEEE. Read Paper
  3. M. R. Alom, T. A. Opi, H. I. Polak, M. N. Shakib, M. P. Hossain, and M. A. Rahaman (2023). Enhanced Road Lane Marking Detection System: A CNN-based Approach for Safe Driving. 2023 5th IEEE International Conference on Sustainable Technologies for Industry 5.0 (STI) (pp. 1-6). Read Paper
  4. M. R. Alom, M. N. Shakib, and M. A. Rahaman (2023). Enhanced Hamming Codes: Reducing Redundant Bit for Efficient Error Detection and Correction. 2023 5th IEEE International Conference on Sustainable Technologies for Industry 5.0 (STI) (pp. 1-6). Read Paper

 

Last Updated: 05 June, 2024

 

 

Awards & Achievements

Best Paper Award
Won 1st prize award in the “Best Paper Category” out of 103 accepted papers at the 5th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT 2021).
Dean’s Award
Achieved the Dean’s Award for outstanding academic performance in 3 consecutive years from session 2017-18 to session 2019-20.
Faculty of EEE, KUET.
Education Board Scholarship
Awarded the Education Board Scholarship for exceptional achievements at the Primary level (2008), Secondary level (2014) and higher Secondary level (2016).
Rajshahi Education Board, Bangladesh.
Intra-district Chess Champion
Secured first place in the Intra-district Chess Championship.
District Sports Officer’s Office, Bogura, Bangladesh.

 

 

Research Areas

  • Application of Machine Learning for Traffic Flow Prediction and Optimization

    This area focuses on using ML algorithms to analyze traffic data and predict future traffic patterns. These predictions can be used to optimize traffic flow, reduce congestion, and improve overall transportation efficiency.

  • Deep Learning for Autonomous Vehicles and Advanced Driver-Assistance Systems (ADAS)

    This area explores the use of DL techniques to develop intelligent systems for autonomous vehicles and ADAS. These systems can perceive their surroundings, make decisions, and navigate safely on the roads.

  • Image processing, Computer Vision and Neural Network

    This area focuses on developing various deep neural network for efficient information extraction.

 

Thesis/Project Supervision

  • Fall 2023:

    1. Traffic flow prediction

    2. Depression detection

    3. Canteen Management

  • Spring 2023:

    1. CheapFinder: Extract minimum price from e-commerce site

    2. HelpMom: Android app for pregnant women

  • Fall 2022:

    1. VIATER: A Car Rental Solution