computer science and engineering

Bachelor of Science (BSc), 2017-2021 :
Department of Computer Science and Engineering (CSE)
Military Institute of Science & Technology (MIST)
CGPA: 3.98 out of 4.00
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
• Computer Vision
• Brain-Computer Interfacing
• Data Minning

Journal:

1. Zaman, Akib, Mohammad Shahjahan Majib, Shoeb Ahmed Tanjim, Shah Md Ahasan Siddique, Fardeen Ashraf, Shafayetul Islam, Abu Hena Md Maruf Morshed et al. “Phoenix: Towards Designing and Developing a Human Assistant Rover.” IEEE Access 10 (2022): 50728-50754. (IF = 3.367 and SJR Rank = Q1)
2. Zaman, Akib, Mohammad Shahjahan Majib, Shoeb Ahmed Tanjim, Shah Md Ahasan Siddique, Shafayetul Islam, Md Shadman Aadeeb, Nafiz Imtiaz Khan, et al. “UVC-PURGE: A Novel Cost-Effective Disinfection Robot for Combating COVID-19 Pandemic.” IEEE Access 10 (2022): 37613-37634. (IF = 3.367 and SJR Rank = Q1)
3. 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)
4. Mukta, Md Saddam Hossain, Salekul Islam, Swakkhar Shatabda, Mohammed Eunus Ali, and Akib Zaman. “Predicting Academic Performance: Analysis of Students’ Mental Health Condition from Social Media Interactions.” Behavioral Sciences 12, no. 4 (2022): 87. (IF = 2.325, SJR = Q2)

Conference proceedings:

1. Akib Zaman, Anika Tahsin, Mostafizur Rahman, Rabeya Akhter, Hinoy Rahman, Shobnom Mustary, and Dewan Md. Farid “Emotion Detection for Children on the Autism Spectrum using BCI and Web Technology”. (Accepted for Presentation at 21st IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2022), November 17-20, 2022, Canada)
2. 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
3. Md. Saddam Hossain Mukta, Akib Zaman, Md. Adnanul Islam, and Bayzid Ashik Hossain. “Predicting Users’ Eat-Out Preference from Big5 Personality Traits”. Presented in 3rd Congress on Intelligent Systems (CIS 2022), September 05-06, 2022 (Accepted for Publication) [Best Paper in BIG DATA ANALYTICS Category]
4. Ahmed Rafi Hasan, Akib Zaman, Puja Ghosh, Tazkia Tasnim Bahar Audry, Fardina Bhuiyan, Arindam Kundu Amit and Md. Saddam Hossain Mukta. “Degrees of Anger Prediction from Speech” In 25^th International Conference on Computer and Information Technology 2022 (ICCIT 2022). (Accepted for Publication)
5. Sumsuttibriz Riad, Md.Sojib Ahmed, Mahammudul Hassan Himel, Md Rayhan Ahmed, Md.Mynul hasan, Ahsan Habib Mim, Akib Zaman, Salekul Islam and Md. Saddam Hossain Mukta “Prediction of Soil Nutrients using Hyperspectral Satellite Imaging”. Presented at International Conference on 4^th Industrial Revolution and Beyond on 10^th December 2021 (Accepted for Publication) [Ref]  [THESIS CO-SUPERVISION with Associate Prof. Saddam Hossain Mukta]
6. Ahmed Shabab Noor, Muhib Al Hasan, Ahmed Rafi Hasan, Rezab Ud Dawla, Afsana Airin, Akib Zaman, and Dewan Md. Farid. “The Impact of Data Locality on the performance of Cluster-Based Under-Sampling”. Presented In International Conference on Machine Intelligence and Emerging Technologies (MIET 2022), September 23-25, 2022 (Accepted for Publication) [THESIS CO-SUPERVISION with Prof. Dewan Farid]
7. Ahmed Shabab Noor, Afsana Airin, Rezab Ud Dawla, Ahmed Rafi Hasan, Muhib Al Hasan, Akib Zaman, and Dewan Md. Farid. A novel method for imbalanced data classification based on label reassignment. In IEEE Region 10 Conference (TENCON), pages 1–6, Hong Kong, November 2022 [THESIS CO-SUPERVISION with Prof. Dewan Farid]
8. Afsana Airin, Rezab Ud Dawla, Ahmed Shabab Noor, Muhib Al Hasan, Ahmed Rafi Hasan, Akib Zaman, and Dewan Md. Farid. Attention-based scene graph generation: A review. In 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA 2022), pages 1–6, Phnom Penh, Cambodia, December 2022 [THESIS CO-SUPERVISION with Prof. Dewan Farid]
9. Abdullah Al Masud, Sabbir Hossain, Muhsina Rifa, Farhana Akter, Akib Zaman, and Dewan Md. Farid. Meta-learning in supervised machine learning. In 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA 2022), pages 1–6, Phnom Penh, Cambodia, December 2022 [THESIS CO-SUPERVISION with Prof. Dewan Farid]

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 consisting of almost 50 students worked under me toward 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 for 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 the 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 resources 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 the 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 was 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 prize-money and a 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 the PTSD of soldiers by creating an early prototype of a stress monitoring system suitable for military operations using their brain waves 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. The 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.

Teaching:

• CSE 5031: Data Structures and Algorithms

International:

• 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]
• Awarded with International Award (For Attaining the Highest score in Military, Academic, and Professional Exams during the Course among Overseas Students), Officers’ Commissioning Course CC163, Royal Military Academy Sandhurst (2018) [Ref]

National:

• Awarded with MIST Medal (Highest CGPA in the Department of CSE, MIST)
• Awarded with MIST Dean’s List of honour (For attaining a CGPA of 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 levels 2,3 and 4 during undergraduate study at the 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