Jaehwan Jeong | Generative AI models | Best Researcher Award

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Mr. Jaehwan Jeong | Generative AI models | Best Researcher Award

Ph.D Student,Korea University,South Korea

Jaehwan Jeong is an emerging researcher in AI and computer vision, with a strong academic background and collaborations with top institutions. His work in deepfake defense and generative models positions him well for awards in AI safety and multi-modal learning. However, securing additional accepted publications and leading independent research could further bolster his case for the Best Researcher Award.

Publication Profile
Google Scholar

Education :

Jaehwan Jeong is currently pursuing a Ph.D. in Artificial Intelligence at Korea University, Seoul, South Korea (2024–2029, expected). He completed his Bachelor of Engineering (B.E.) in Electrical & Electronic Engineering from Chung-Ang University, Seoul, in 2021. His academic journey has been focused on artificial intelligence, deep learning, and computer vision.

Experience:

Research Focus:

Skills:

Jaehwan possesses strong expertise in:,Programming: Python, Shell Scripting, Git, LaTeX,Deep Learning Frameworks: PyTorch, PyTorch Lightning, TensorFlow,AI & ML Libraries: Hugging Face, Scikit-Learn

Publication :

  • MTVG: Multi-text Video Generation with Text-to-Video Models

    • Authors: Gyeongrok Oh, Jaehwan Jeong, Sieun Kim, Wonmin Byeon, Jinkyu Kim, Sungwoong Kim, Hyeokmin Kwon, Sangpil Kim
    • Publication: arXiv preprint arXiv:2312.04086
    • Year: 2023
    • Citation: Oh, G., Jeong, J., Kim, S., Byeon, W., Kim, J., Kim, S., Kwon, H., & Kim, S. (2023). MTVG: Multi-text Video Generation with Text-to-Video Models. arXiv preprint arXiv:2312.04086.
      kuai-lab.github.io

  • MEVG: Multi-event Video Generation with Text-to-Video Models

    • Authors: Gyeongrok Oh, Jaehwan Jeong, Sieun Kim, Wonmin Byeon, Jinkyu Kim, Sungwoong Kim, Sangpil Kim
    • Publication: European Conference on Computer Vision (ECCV), pages 401–418
    • Year: 2025
    • Citation: Oh, G., Jeong, J., Kim, S., Byeon, W., Kim, J., Kim, S., & Kim, S. (2025). MEVG: Multi-event Video Generation with Text-to-Video Models. In A. Leonardis, E. Ricci, S. Roth, O. Russakovsky, T. Sattler, & G. Varol (Eds.), Computer Vision – ECCV 2024 (pp. 401–418). Springer.
      pure.korea.ac.kr

  • FaceShield: Defending Facial Image against Deepfake Threats

    • Authors: Jaehwan Jeong, Seungmin In, Sieun Kim, Hyojin Shin, Jaeho Jeong, Seunghyun Yoon, Jaewon Chung, Sungwoong Kim
    • Publication: arXiv preprint arXiv:2412.09921
    • Year: 2024
    • Citation: Jeong, J., In, S., Kim, S., Shin, H., Jeong, J., Yoon, S., Chung, J., & Kim, S. (2024). FaceShield: Defending Facial Image against Deepfake Threats. arXiv preprint arXiv:2412.09921.
Conclusion:

Jeong is a strong candidate for the award but would benefit from more accepted publications and demonstrated leadership in independent research. His ongoing Ph.D. work and collaborations with Samsung, NVIDIA, and Google make him a promising researcher with significant potential.

Ali Reza Keivanimehr | AI in healthcare | Best Researcher Award

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Mr.Ali Reza Keivanimehr | AI in healthcare
| Best Researcher Award

Mr.  Ali RezaKeivanimehr ,  Amirkabir University of Technology (Tehran’s Polytechnic), Iran.

Ali Reza Keivanimehr is an exceptional early-career researcher with a solid academic foundation, a promising research trajectory in machine learning applications for healthcare, and strong technical expertise. His combination of research, teaching, and technical projects highlights a well-rounded profile. His contributions, especially in the use of TinyML for cardiovascular diagnosis, are commendable and align with global health priorities.

Publication Profile

Google scholar

Education :

Master of Science in Information Technology Engineering – Internet of Things (IoT) (2022 – 2025)Amirkabir University of Technology (Tehran Polytechnic), Tehran, IranRanked 403rd in QS World University Rankings 2024GPA: 3.53/4 (17.48/20) – 3rd highest in 2022 faculty entranceThesis: Applications of TinyML in Prediction and Diagnosis of Cardiovascular DiseasesSupervisor: Dr. Mohammad Akbari | Advisor: Dr. Abbas AhmadiBachelor of Science in Computer Engineering – Software Engineering (2018 – 2021)Imam Khomeini International University of Qazvin, Qazvin, IranProject: Designing a Software Interface for Industrial Machinery Maintenance

Experience :

Research Assistant (2022 – Present)
Data Science Lab (DSLab), Amirkabir University of Technology, Tehran, IranConducting research on TinyML and edge intelligence applications in cardiovascular disease prediction.Teaching Assistant — Machine Learning and Pattern Recognition (2024 – 2025)Amirkabir University of Technology, Tehran, IranAssisted in course instruction, project supervision, and student evaluations under Dr. Alireza Rezvanian.Teaching Assistant — Data Structure and Algorithms (2019 – 2020)
Imam Khomeini International University of Qazvin, Qazvin, IranSupported coursework delivery, assignments, and exam preparations under Morteza Mohammadi Zanjireh.

Research Focus :

Natural Language Processing (NLP)Graph Neural NetworksEdge IntelligenceExplainable Artificial Intelligence (XAI)Generative Adversarial Networks (GANs)Dr. Keivanimehr’s research centers on Tiny Machine Learning (TinyML) and edge intelligence, with a specific emphasis on their applications in cardiovascular disease monitoring. He explores the deployment of machine learning models on low-power, resource-limited devices to facilitate real-time analytics and pervasive monitoring for patients with cardiac anomalies.

Skills and Expertise:

As a research assistant, Dr. Keivanimehr has developed expertise in machine learning, classification, and supervised learning. His technical proficiency includes a focus on computational health and biomedical applications, particularly in the context of resource-constrained devices.Programming: PythonMachine Learning Frameworks: PyTorch, TensorFlowBig Data Tools: Apache SparkLanguages: TOEFL iBT (Score: 109 | Reading: 28 | Listening: 30 | Speaking: 26 | Writing: 25)

Awards:

 

48th Rank among 5000+ participants, National Entrance Exam for Master Studies in IT Engineering (2022)3rd Rank in IT Engineering Master’s cohort based on GPA (2022 – Present)Full Master’s Scholarship: Awarded for excellence in national entrance exams; covers tuition, dormitory, and partial food expenses (2022 – Present)Full Bachelor’s Scholarship: Granted for top performance in national entrance exams; included tuition, accommodation, and meal support (2018 – 2021)

 

Publication 

 

  • Keivanimehr, A., & Akbari, M. (2024). TinyML and Edge Intelligence Applications in Cardiovascular Disease: A Survey. Computers in Biology and Medicine. DOI: 10.1016/j.compbiomed.2025.109653

 

Conclusion

Ali Reza Keivanimehr is a suitable candidate for the Best Researcher Award. His strong academic record, impactful research, and consistent growth in machine learning and edge intelligence demonstrate his potential as a leading researcher in his field. With further international exposure and expanded publication efforts, he is poised to make significant contributions to both academia and industry.

 

Saba Inam | machine learning | Women Researcher Award

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Dr.Saba Inam |machine learning| Women Researcher Award

Dr Saba InamFatima Jinnah women university, The Mall, Rawalpindi, Pakistan.

Dr. Saba Inam is a lecturer in the Department of Mathematical Sciences at Fatima Jinnah Women University in Rawalpindi, Pakistan. She earned her PhD in Algebraic Cryptography from the Capital University of Science and Technology, completing her studies between February 2014 and January 2019. Her research interests include Algebraic Number Theory, Algebraic Cryptography, Applied Cryptography, image encryption, Cloud Computing, Machine Learning, and Deep Learning. Dr. Inam has contributed to over 20 publications, accumulating 247 citations, and her work has garnered more than 3,367 reads. Notably, she co-authored the article “An efficient image encryption algorithm using 3D-cyclic Chebyshev map and elliptic curve,” published in November 2024.

Publication Profile

Google Scholar

Orcid

Education :

Dr. Saba Inam holds a PhD in Mathematics from Capital University of Science and Technology (CUST), Islamabad (2019). She completed her MS in Mathematics from COMSATS Institute of Information Technology, Islamabad, in 2007 with a CGPA of 3.6/4, achieving 1st Division. She earned her M.Sc. in Mathematics from Quaid-i-Azam University, Islamabad (2005), and her B.Sc. in Mathematics (Maths A, Maths B, Stats) from the University of the Punjab (2003), both with 1st Division.

Experience :

Dr. Inam has extensive academic and research experience. Since September 2007, she has been serving as a Lecturer in Mathematics at Fatima Jinnah Women University, Rawalpindi. She also held the position of Incharge, Department of Mathematical Sciences from August 2016 to January 2018. Before that, she worked as a Research Associate at COMSATS Institute of Information Technology, Islamabad, from March to August 2007.

Research Focus :

Dr. Inam’s research interests span across multiple domains, including:

Cryptography & Security: Algebraic Cryptography, Cryptology, CryptanalysisAI & Data Security: Image Encryption, Blockchain, IoT, Deep Learning, Machine LearningMathematical Sciences: Fluid Mechanics, Geometric Function Theory.

 

Awards:

Dr. Inam’s academic excellence has been recognized through various awards and honors:

Scholarship – Capital University of Science and Technology (CUST), Islamabad (2013-2018)Dean’s Roll of Honor – Received twice during PhD courseworkDiploma in Academic Excellence in Discrete Mathematics – Abdul Salam School of Mathematical Sciences, GC University, Lahore (2012)Scholarship – COMSATS Institute of Information Technology, Islamabad (2005-2007)

Skills:

Dr. Inam possesses expertise in:Programming & Computational Tools: Matlab, Python, Mathematica, APCoCoA, Scientific Workplace, LaTeXOffice & Documentation: Proficient in Microsoft Office Suite,Dr. Saba Inam continues to contribute significantly to the fields of cryptography, image encryption, and mathematical security frameworks, with a strong focus on deep learning and blockchain applications.

Publication :

 

Three dimensional boundary layer flow of a viscoelastic nanofluid with Soret and Dufour effects

Numerical simulation of Darcy–Forchheimer 3D unsteady nanofluid flow comprising carbon nanotubes with Cattaneo–Christov heat flux and velocity and thermal slip conditions

An effective color image encryption based on Henon map, tent chaotic map, and orthogonal matrices

A new ElGamal-like cryptosystem based on matrices over groupring

Analytic study of a novel color image encryption method based on the chaos system and color codes

Blockchain based medical image encryption using Arnold’s cat map in a cloud environment

A numerical study of rotating Bödewadt flow of micropolar fluid over porous disk

A Novel Public Key Cryptosystem and Digital Signatures

A new method of image encryption using advanced encryption Standard (AES) for network security

Research on color image encryption approach based on chaotic Duffing map

Conclusion

Dr. Inam’s strengths, including her academic excellence, research impact, and leadership in academia, position her as a strong candidate for the “Research for Women Researcher Award.” While there are areas to enhance collaboration and public outreach, her work is already shaping critical developments in data security and encryption. Recognizing her would not only celebrate her achievements but also inspire more women to pursue careers in research and technology, contributing significantly to both academic and societal progress.

Mahmoud Marhamati |Artificial | Best Researcher Award

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Mr.Mahmoud Marhamati |Artificial | Best Researcher Award

Mr. Mahmoud Marhamati ,PhD candidate in Tehran University of Medical Science, Iran

Mr. Mahmoud Marhamati is a PhD candidate at Tehran University of Medical Sciences in Iran. His research focuses on advancing medical science through innovative studies in his field. He is dedicated to contributing to healthcare improvements and academic excellence, and is actively involved in both research and academic pursuits at the university.

Summary:

Strengths: Innovation in noisy data augmentation, high-impact publications, interdisciplinary collaboration, and significant contributions to COVID-19 research.,Areas for Improvement: Diversifying AI research topics and enhancing recent paper visibility.

Professional Profiles:

Google Scholar

🎓 Education :

M. Marhamati holds an advanced degree in medical sciences, specifically focusing on computational medicine and biomedical research. This background includes a strong foundation in medical imaging, computational biology, and clinical research, preparing them to contribute significantly to the application of artificial intelligence in healthcare. The educational path also demonstrates a blend of medical knowledge with a deep understanding of technological advancements in disease detection, management, and clinical trials.

🏢 Experience:

M. Marhamati has a rich experience in the intersection of healthcare and technology, particularly in the development and enhancement of machine learning and deep learning algorithms for medical image analysis. Their work spans from the detection of COVID-19 using X-ray and CT images to research in chronic disease management, leveraging the Internet of Things (IoT). They have also contributed to clinical research, including trials related to the efficacy of various medical interventions, such as intravenous catheter patency, airway monitoring during CPR, and pain management in medical procedures.

🛠️Skills:

Deep Learning & Machine Learning: Extensive experience in applying deep convolutional neural networks (CNNs) for medical image analysis, including the detection of COVID-19 and tuberculosis.,Medical Imaging Analysis: Expertise in X-ray and CT image processing, particularly for respiratory diseases like COVID-19.,Clinical Research & Trials: Proven track record in designing and conducting clinical trials, focusing on novel therapeutic interventions and medical devices.,Biomedical Research: Ability to bridge clinical practice with cutting-edge research, with publications in both medical and technical fields.,Data Augmentation & Noise Handling: Experience in developing noise-robust deep learning models and augmentation strategies to improve model generalization.,Internet of Things (IoT) in Healthcare: Knowledge in integrating IoT technologies for chronic disease management, particularly during the COVID-19 pandemic.

🔬Awards:

Throughout their career, M. Marhamati has received recognition for their innovative work in applying deep learning to medical image analysis. Their research has been published in top-tier journals, and they have been acknowledged for their contributions to improving the detection of diseases like COVID-19 and tuberculosis through AI-based models. Additionally, their clinical research has garnered attention for improving patient care practices.

Research Focus:

M. Marhamati’s research is primarily focused on the application of deep learning and AI in medical imaging and healthcare. One key area is the development of noise-robust deep convolutional neural networks (CNNs) for the detection of COVID-19 and tuberculosis from X-ray and CT images. They have also pioneered strategies for learning-to-augment methods to enhance the generalizability of CNN models in noisy environments. Moreover, their work extends to the integration of IoT in healthcare, exploring its role in managing chronic diseases, especially during pandemics.

Conclusion:

Mr. Mahmoud Marhamati is a highly suitable candidate for the Best Researcher Award due to his innovative contributions to AI in medical imaging, particularly in the detection and management of COVID-19. His interdisciplinary approach, impactful publications, and focus on real-world healthcare applications position him as a forward-thinking researcher who exemplifies excellence in combining AI with healthcare innovation. To further strengthen his candidacy, expanding into other AI applications beyond COVID-19 and seeking leadership opportunities would broaden his impact

Publications :

  • Learning-to-augment strategy using noisy and denoised data: Improving generalizability of deep CNN for the detection of COVID-19 in X-ray images
    • Authors: M. Momeny, A.A. Neshat, M.A. Hussain, S. Kia, M. Marhamati, et al.
    • Journal: Computers in Biology and Medicine
    • Year: 2021
    • Citations: 67

 

  • Learning-to-augment incorporated noise-robust deep CNN for detection of COVID-19 in noisy X-ray images
    • Authors: A. Akbarimajd, N. Hoertel, M.A. Hussain, A.A. Neshat, M. Marhamati, et al.
    • Journal: Journal of Computational Science
    • Year: 2022
    • Citations: 36

 

  • Greedy Autoaugment for classification of mycobacterium tuberculosis image via generalized deep CNN using mixed pooling based on minimum square rough entropy
    • Authors: M. Momeny, A.A. Neshat, A. Gholizadeh, A. Jafarnezhad, E. Rahmanzadeh, et al.
    • Journal: Computers in Biology and Medicine
    • Year: 2022
    • Citations: 32

 

  • Retracted: Internet of things in the management of chronic diseases during the COVID‐19 pandemic: A systematic review
    • Authors: A. Shamsabadi, Z. Pashaei, A. Karimi, P. Mirzapour, K. Qaderi, M. Marhamati, et al.
    • Journal: Health Science Reports
    • Year: 2022
    • Citations: 27

 

  • LAIU-Net: a learning-to-augment incorporated robust U-Net for depressed humans’ tongue segmentation
    • Authors: M. Marhamati, A.A.L. Zadeh, M.M. Fard, M.A. Hussain, K. Jafarnezhad, et al.
    • Journal: Displays
    • Year: 2023
    • Citations: 18

 

  • Active deep learning from a noisy teacher for semi-supervised 3D image segmentation: Application to COVID-19 pneumonia infection in CT
    • Authors: M.A. Hussain, Z. Mirikharaji, M. Momeny, M. Marhamati, A.A. Neshat, R. Garbi, et al.
    • Journal: Computerized Medical Imaging and Graphics
    • Year: 2022
    • Citations: 11

 

  • Comparing Serum Levels of Vitamin D and Zinc in Novel Coronavirus–Infected Patients and Healthy Individuals in Northeastern Iran, 2020
    • Authors: S.J. Hosseini, B. Moradi, M. Marhamati, A.A. Firouzian, E. Ildarabadi, A. Abedi, et al.
    • Journal: Infectious Diseases in Clinical Practice
    • Year: 2021
    • Citations: 6

 

  • Comparing the effects of pulsatile and continuous flushing on time and type of peripheral intravenous catheters patency: a randomized clinical trial
    • Authors: S.J. Hosseini, F. Eidy, M. Kianmehr, A.A. Firouzian, F. Hajiabadi, M. Marhamati, et al.
    • Journal: Journal of Caring Sciences
    • Year: 2021
    • Citations: 4

 

  • Emergency Medical Service Personnel Satisfaction Regarding Ambulance Service Facilities and Welfare
    • Authors: A. Jesmi, H.M. Ziyarat, M. Marhamati, T. Mollaei, H. Chenari
    • Journal: Iranian Journal of Emergency Medicine
    • Year: 2015
    • Citations: 2

 

  • Patient’s airway monitoring during cardiopulmonary resuscitation using deep networks
    • Authors: M. Marhamati, B. Dorry, S. Imannezhad, M.A. Hussain, A.A. Neshat, et al.
    • Journal: Medical Engineering & Physics
    • Year: 2024
    • Citations: 1

 

  • Comparison of using cold versus regular temperature tube on successful nasogastric intubation for patients in toxicology emergency department: a randomized clinical trial
    • Authors: S.R. Mazlom, A.A. Firouzian, H.M. Norozi, A.G. Toussi, M. Marhamati
    • Journal: Journal of Caring Sciences
    • Year: 2020
    • Citations: 1

 

  • Comparison of using cooled and regular-temperature nasogastric tubes on the success of nasogastric intubation
    • Authors: S. Mazlom, M. Marhamati, H. Norozi, A. Ghasemi Toosi
    • Journal: Evidence Based Care
    • Year: 2015
    • Citations: 1

 

 

MD. HUMAUN KABIR | Machine Learning| Best Researcher Award

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Mr.MD. HUMAUN KABIR | Machine Learning| Best Researcher Award

Mr , MD. HUMAUN KABIR, Department of Computer Science and Engineering, Bangamata Sheikh Fojilatunnesa Mujib Science & Technology University,Bangladesh.

Mr. MD. Humaun Kabir is a distinguished faculty member in the Department of Computer Science and Engineering at Bangamata Sheikh Fojilatunnesa Mujib Science & Technology University, Bangladesh. He is dedicated to advancing computer science education and research, with a focus on cutting-edge technologies and innovations that drive the field forward. Through his commitment to academic excellence, Mr. Kabir continues to inspire and mentor the next generation of engineers and computer scientists.

Summary:

  • Achieved a high CGPA in both M.Sc. (3.88) and B.Sc. (3.82) in Engineering, indicating strong academic performance.
  • Consistently strong performance throughout academic life, with excellent results in HSC and SSC.

Professional Profiles:

Google Scholar

Education :

Md. Humaun Kabir completed his M.Sc. in Engineering with a specialization in Applied Physics and Electronic Engineering from the University of Rajshahi in 2015, earning an impressive CGPA of 3.88 on a 4.00 scale. He also holds a B.Sc. in Engineering from the same department, achieved in 2014, with a CGPA of 3.82 on a 4.00 scale. Prior to his university education, he excelled in his secondary and higher secondary studies, achieving a GPA of 5.00 in HSC from Police Line’s School & College, Kushtia (Jashore Board) in 2010, and a GPA of 4.94 in SSC from Patachora Secondary School, Chuadanga (Jashore Board) in 2008. Notably, on December 24, 2018, the Department of Applied Physics and Electronic Engineering was renamed to the Department of Electrical and Electronic Engineering.

Work Experience:

With a professional career spanning around seven years, Md. Humaun Kabir has served in multiple academic roles. He began as a Lecturer in the Department of Computer Science and Engineering at Pundra University of Science & Technology, Bogura, where he worked from May 23, 2017, to February 9, 2019. He then continued as a Lecturer at Bangamata Sheikh Fojilatunnesa Mujib Science & Technology University (BSFMSTU), Jamalpur, from February 10, 2019, to February 19, 2022. He was promoted to Assistant Professor at the same institution on February 20, 2022, and later took on the additional role of Chairman of the Department of Computer Science and Engineering on April 9, 2022. Additionally, he holds the position of Additional Director (In-charge) of the ICT Cell at BSFMSTU, where he has been serving since April 12, 2022.

Research Focus :

Md. Humaun Kabir’s research interests encompass a broad spectrum of topics, including Signal/Image Processing, Computer Vision, Brain-Computer Interfaces (BCI), Human-Computer Interaction (HCI), and Biomedical Engineering. He is also passionate about Wireless Communication & Networks, and his work extends into the realms of Machine Learning & Deep Learning. His research endeavors have led to several significant contributions to the field, with a focus on enhancing performance in BCI systems and improving wireless communication systems.

Skills:

Throughout his career, Md. Humaun Kabir has developed a robust technical skillset. He is proficient in programming languages such as MATLAB, Python, C, and C++, and has expertise in using LaTeX and Overleaf for academic writing. His technical repertoire is further enriched by his experience with the Internet of Things (IoT) and embedded systems, as well as networking knowledge gained through Cisco Certified Network Associate (CCNA) training.

 Awards:

Md. Humaun Kabir has been recognized for his outstanding academic and professional achievements. He received the prestigious Dean’s Award during both his B.Sc. and M.Sc. Engineering programs from the Faculty of Engineering at the University of Rajshahi. Additionally, he was awarded a Merit Scholarship from the University of Rajshahi for his academic excellence. His research excellence has been further acknowledged through his involvement in various government and university-funded research projects, including a current project on EEG-based motor imagery tasks classification for BCI systems.

Conclusion:

Md. Humaun Kabir demonstrates strong potential as a researcher, with a solid academic foundation, relevant research interests, and considerable teaching and administrative experience. However, to strengthen his candidacy for the Best Researcher Award, it would be beneficial to have a more robust record of research publications, greater international collaboration, and evidence of securing research funding. Addressing these areas could make him a more competitive candidate for the award.

Publications :

  • Title: Strain-driven optical, electronic, and mechanical properties of inorganic halide perovskite CsGeBr3
    Authors: MR Islam, MRH Mojumder, R Moshwan, ASMJ Islam, MA Islam
    Source: ECS Journal of Solid State Science and Technology, 11(3), 033001
    Year: 2022
    Citations: 42

 

  • Title: Investigating feature selection techniques to enhance the performance of EEG-based motor imagery tasks classification
    Authors: MH Kabir, S Mahmood, A Al Shiam, AS Musa Miah, J Shin, MKI Molla
    Source: Mathematics, 11(8), 1921
    Year: 2023
    Citations: 21

 

  • Title: Design of Rectangular Microstrip Patch Antenna at 3.3 GHz Frequency for S-band Applications
    Authors: MI Hossain, MT Ahmed, MH Kabir
    Source: International Journal of Engineering and Manufacturing, 12(4), 46-52
    Year: 2022
    Citations: 10

 

  • Title: Smart attendance and leave management system using fingerprint recognition for students and employees in academic institute
    Authors: MH Kabir, S Roy, MT Ahmed, M Alam
    Source: International Journal of Scientific & Technology Research, 10(6), 268-276
    Year: 2021
    Citations: 10

 

  • Title: IoT based solar powered smart waste management system with real-time monitoring – An advancement for smart city planning
    Authors: MH Kabir, S Roy, MT Ahmed, M Alam
    Source: Global Journal of Computer Science and Technology, 20(5), 11-20
    Year: 2020
    Citations: 9

 

  • Title: Gender Recognition of Bangla Names Using Deep Learning Approaches
    Authors: MH Kabir, F Ahmad, MAM Hasan, J Shin
    Source: Applied Sciences, 13(1), 522
    Year: 2022
    Citations: 7

 

  • Title: Secured voice frequency signal transmission in 5G compatible multiuser downlink MIMO NOMA wireless communication system
    Authors: MH Kabir, J Rahman, SE Ullah
    Source: International Journal of Networks and Communications, 8(4), 97-105
    Year: 2018
    Citations: 6

 

  • Title: A neural attention-based encoder-decoder approach for English to Bangla translation
    Authors: AA Shiam, SM Redwan, MH Kabir, J Shin
    Source: Computer Science Journal of Moldova, 91(1), 70-85
    Year: 2023
    Citations: 5

 

  • Title: Web-based student registration and exam form fill-up management system for educational institutes
    Authors: MT Ahmed, MH Kabir, S Roy
    Source: International Journal of Information Engineering and Electronic Business
    Year: 2022
    Citations: 5

 

  • Title: Design and implementation of web-based smart class routine management system for educational institutes
    Authors: S Roy, MH Kabir, MT Ahmed
    Source: International Journal of Educational Management Engineering, 12(2), 38-48
    Year: 2022
    Citations: 4

 

  • Title: A Methodological and Structural Review of Hand Gesture Recognition Across Diverse Data Modalities
    Authors: J Shin, ASM Miah, MH Kabir, MA Rahim, AA Shiam
    Source: arXiv preprint arXiv:2408.05436
    Year: 2024
    Citations: 1

 

  • Title: Design of a High-Gain 2× 1 Array Antenna for S-Band Applications
    Authors: MI Hossain, MA Islam, MT Ahmed, MH Kabir
    Source: World Journal of Engineering and Technology, 11(2), 293-302
    Year: 2023
    Citations: 1