Faculty Profile

Zaman, Akib

LecturerEmail : akib@cse.uiu.ac.bd

Akib Zaman is working as a Lecturer in the Department of Computer Science and Engineering at United International University (UIU), Bangladesh. He has completed his BSc. in Computer Science and Engineering from Military Institute of Science & Technology (MIST) in 2021. His thesis was titled “Digitalization of Battlefield Environment and Effect Analysis: Towards Developing an Effective IPB System using R-CNN”.

With Experience in working and leading several projects related to Robotics and AI systems, Deep Learning techniques, Image Processing, , HCI during the undergraduate tenure, he is keen to explore his capabilities in autonomous systems, machine learning techniques and data analytics. Moreover, with the experience of participating in premium robotics competition like the University Rover Challenge (URC), he is also fluent in working with embedded systems and new hardware sensors to modify and build systems to solve practical problems.

He is well capable of management, leadership, and administrative roles with the experience of serving as Team-Leader in Several Complex Projects managing a big group of students. Moreover, He loves Debate and Extempore Speech Competitions, which has given him a good command of Speaking and Presentation.

Personal Interest : Astrology, Science, Technology, Debate, Public Speaking, Music, Travel.

Bachelor of Science (BSc), 2015-2021 :
Department of Computer Science and Engineering (CSE)
Military Institute of Science & Technology (MIST)
CGPA: 3.98 out of 4.00 (Yet to be Published)
Dissertation Supervisor: Lt Col Muhammad Nazrul Islam, PhD


Higher School Certificate (HSC), 2014:
Jhenidah Cadet College [2nd in Jashore Board]


Secondary School Certificate(SSC), 2012:
Jhenidah Cadet College

  • Robotics & Autonomous Systems
  • Machine learning & Data mining
  • Software engineering
  • Human-computer interaction
  • Embedded & Real-time systems



  1. Muhammad Nazrul Islam , Akib Zaman, and Shaoli Sarker. “Beliefs about COVID-19 of Elderly Residents in Rural Bangladesh.” Asia-Pacific journal of public health. 2020;32(8):527-528. doi:10.1177/1010539520964275 (IF = 1.255 and SJR Rank = Q2)


Book Chapter:

  1. Akib Zaman, Muhammad Nazrul Islam, Tarannum Zaki, and Mohammad Sajjad Hossain “ICT Intervention in the Containment of the Pandemic Spread of COVID-19: An Exploratory Study” (Manuscript under Review  in Springer Book: “Healthcare Technology Solutions for Pandemics – A Roadmap”) (Accepted: Preparing Camera Ready Submission on July 2021 )

Conference proceedings:

  1. Akib Zaman, Rafat Tanjim Khan, Nazmul Karim, Muhammad Nazrul Islam, Md Shihab Uddin, and Md Mehedi Hasan ”Intelli-Helmet: An Early Prototype of a Stress Monitoring System Suitable for Military Operations”. In: Garg L. et al. (eds) Information Systems and Management Science. ISMS 2020. Lecture Notes in Networks and Systems, vol 303. Springer, Cham. https://doi.org/10.1007/978-3-030-86223-7_3

University Rover Challenge 2021 [MIST Mongol Barota (Phoenix)]

I lead the team of MIST Mars Rover society “MIST Mongol-Barota” to compete in University Rover Challenge 2021 along with my other teammates. Six sub teams consisted of almost 50 students worked under me towards the completion of the project. Our rover PHOENIX was systematically built to achieve all the missions given by URC 2021. With an outstanding score of 92.78% in the System Acceptance Review (SAR), MIST Mongol Barota was selected in the URC 2021 Final while the qualification benchmark was 77.7%. Following the success of the System Acceptance Review, our team MIST Mongol Barota has topped among all the teams of University Rover Challenge (URC) Virtual Final 2021 with a total score of 180 by attaining a perfect score (100) in Equipment Servicing Mission and 2nd Highest Score(80) in Extreme Retrieval and Delivery Mission. Interestingly, I worked with Robotic Operating System (ROS) for the first time in this project and it was a great experience. Leading such a big team with proper management of resource was enjoyable too.


Object Detection in Military Map (Undergraduate Thesis)

In my undergraduate thesis, we have explored the military map Dataset to facilitate the Intelligence preparation of Battlefield (IPB) by proposing an object detection approach. A unique dataset has been created for the detection of an object in a military map to initiate machine learning-based research on a military map. Initially, the Deep learning algorithm R-CNN has been used to create the desired model. Furthermore, the transfer-learning style has been integrated using Keras pre-trained model named ImageNet to fine-tune the model for achieving improved accuracy. Currently, the model is 97.5% accurate in detecting waterbody from any military map sample.


UVC-PURGE: A Semi-Autonomous Virus Disinfection Robot

To fight against COVID-19 Pandemic, I lead a project consisting of 09 members to build a semi-autonomous Virus Disinfection robot named UVC-PURGE. This robot has been equipped with six T5 UVC (254 nm) lamps to destroy the SARS-CoV-2 virus (coronavirus) effectively in a standard 12′ x 16′ room with a disinfection time of 2-3 minutes. The Robot provides real-time camera feedback for better navigation. While disinfecting this semi-autonomous robot is capable enough to avoid any obstacles in that room. UVC- PURGE is very user-friendly which can be controlled by a mobile app or computer platform with 1600 square feet coverage area and provides a battery backup of 2 hours. It is applicable for any indoor environment such as an Empty COVID patient ward, Empty ICU, Operation Theatre, Office room, Classroom, Corridor, Personal Apartment etc. At a market price of less than 800$ UVC-PURGE is extremely cost-effective than similar types of disinfection robots all over the world. Our work was recognized in Medical Robotics Challenge for Contagious Disease 2020 organized by UK Robotics & Automation Society (UK-RAS) Network as UVC-PURGE-MIST (Bangladesh) snatched the Championship in Application criteria in parallel with John Hopkins University (USA) in Innovation and Leeds University (UK) in Design. We received £5,000 as a Prize-Money and grant for their research.


Intelli-Helmet : A BCI based Stress Monitoring System for Military Operations

Intelli-helmet was a novel project taken by myself along with my other four groupmates to counter PTSD of soldiers by creating an early prototype of a stress monitoring system suitable for military operations using their brain wave and other physiological data. The electroencephalography (EEG) based brain-computer interfacing (BCI) technology was used to acquire the brain signals, while machine learning techniques were adopted to facilitate the decision-making process for the higher commander. Dataset was collected from soldiers under operational stress and the study found that the Bayes net algorithm showed a higher accuracy of 97.4% followed by the J48 decision tree algorithm of 96.1% while classifying the soldiers’ stress status.


Rock Classification using Transfer Learning & Information Infusion

Detection of Life in Soil and Rock Sample was one of the missions of URC 2021. Creating a dataset of Rock-samples Deep Neural Network with Transfer Learning has been used to classify the Rock Samples. Initial DNN model prepared using Keras Pre-trained model VGG-19 has brought out the accuracy of 92.7% in case of classifying the rock sample. Currently, I am working on this project to infuse texture in a hidden layer of the DNN to increase accuracy, carrying out a comparative study with CNN and collaborate on unique characteristics of rock to automate the life detection process.


Barrier exploration of Pharma 4.0 in Bangladesh:

To explore opportunities to integrate knowledge from Computer Science Domain for creating better Supply Chain Management Methods I along with my three groupmates are working on the Identification of Challenges and drivers while implementing industry 4.0 in the Pharmaceutical Industry of Bangladesh as an aftermath of COVID-19 Pandemic. We are using a Systematic Literature Review (SLR) to explore the Barriers and validating the relationship using multiple criteria decision analysis methods . Moreover, a framework for implementing Phrama4.0 will be proposed to overcome the explored barriers.


Undergraduate Courses
  • CSE 113: Electrical Circuits
  • CSE 422: Computer Graphics Laboratory
  • CSE 430: Digital System Design Laboratory


  • Champion (Application) in Medical Robotics Challenge for Contagious Disease 2020 organized by UK-RAS for UVC-PURGE: A Semi-autonomous Virus Disinfection Robot [Ref] [Ref]
  • Champion Team “MIST Mongol Barota”, University Rover Challenge 2021 organized by The Mars Society, NASA : Team Leader of the Project [Ref] [Ref] [Ref]
  • Awarded with International Award (For Attaining Highest score in Military, Academic and Professional Exams during the Course among the Overseas Students), Officers’ Commissioning Course CC163, Royal Military Academy SandHurst (2018) [Ref]


  • Awarded with MIST Dean’s List of honour (For attaining CGPA more than 3.75 in an academic session): Consecutive 3 Years in Academic Session 2018-2019, 2019-2020 and 2020-2021
  • Received MIST Scholarship (Top 5 Students in Each Semester) in level 2,3 and 4 during undergraduate study at Military Institute of Science and Technology (MIST)
  • Best Speaker (Extempore Speech) in Inter Cadet College Literature Competition (2013)
  • Best Debater and Champion Team (Team Leader) in MIST inter-department English debate competition (2018 and 2019 respectively).
  • Awarded with 60% Scholarship in PTAK 2020 for completing CSCA certification; Organized by ISCEA