Mr. Md. Kawsar Ahmed | Engineering | Best Researcher Award

Mr. Md. Kawsar Ahmed | Engineering | Best Researcher Award

Mr. Md. Kawsar Ahmed, Daffodil International University, Bangladesh

Md. Kawsar Ahmed is an innovative electrical engineer from Bangladesh, specializing in antenna design, 5G/6G technology, and wireless communication. He completed his B.Sc. in Electrical and Electronics Engineering at Daffodil International University (DIU) with a CGPA of 3.50, showcasing a passion for advanced technologies and modern communication systems. His expertise has led him to work on groundbreaking research projects under esteemed international mentors at Universiti Teknologi PETRONAS, Malaysia. Md. Kawsar’s focus on millimeter-wave applications for next-gen communication systems reflects his visionary mindset in the ever-evolving tech landscape. With strong leadership in event management and extracurricular activities, including his role as Secretary of the DIU Voluntary Service Club, Kawsar demonstrates a commitment to both his academic and social responsibilities. His career objective is to apply his skills and creativity in modern technology, pushing the boundaries of electrical engineering for a more connected future.

Professional Profile

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Summary of Suitability for the ‘Research for Best Researcher Award’

Md Kawsar Ahmed demonstrates a well-rounded profile of academic excellence, research potential, and extracurricular involvement. His research contributions in antenna design and wireless communication, coupled with his technical skills, leadership, and international collaborations, make him a suitable candidate for the ‘Research for Best Researcher Award.’ His growing body of work and dedication to technological advancements in 5G and 6G demonstrate significant potential for future contributions to the field.

 🎓Education 

Md. Kawsar Ahmed has a solid educational foundation in Electrical and Electronics Engineering. He graduated with a B.Sc. from Daffodil International University, Dhaka, Bangladesh, earning a CGPA of 3.50 out of 4, from 2020 to 2023. Prior to that, he completed his Higher Secondary Certificate (HSC) from Agricultural University College, Mymensingh, in the Science stream with a CGPA of 3.78 out of 5, in 2019. He also holds a Secondary School Certificate (SSC) from Pacchim Jaynagor Secondary School, Bhola, Barisal, securing a CGPA of 4.82 out of 5 in 2017. Kawsar’s education has been focused on science and technology from the beginning, paving the way for his success in antenna design, wireless communication, and innovative research. His drive for academic excellence has equipped him with practical and theoretical knowledge essential for addressing complex engineering challenges in today’s technology-driven world.

 💼 Experience 

Md. Kawsar Ahmed’s experience is centered on research and academic involvement in the field of electrical engineering. He began as a Student Associate at Daffodil Central Transport Management in 2022, continuing his journey as a Researcher under the mentorship of Dr. Md. Ashraful and Dr. Samir Salem Al-Bawri from Universiti Teknologi PETRONAS, Malaysia, in early 2023. His work focuses on advanced research in antenna design for 5G/6G applications and artificial neural network (ANN)-based performance estimations. His collaboration with renowned researchers has strengthened his expertise in designing highly efficient multi-port antennas for next-gen communications. Additionally, he contributed as a Student Associate in the Office of the Director of Students’ Affairs at DIU from 2022 to 2024. His commitment to both technical research and administrative work demonstrates his versatility and dedication to achieving excellence in his professional career.

 🏅Awards and Honors 

Md. Kawsar Ahmed has received numerous awards and honors that reflect his diverse talents and contributions. He participated in the 7th National Cub Camporee (2011) and the ICT Work Camp (2018) organized by Bangladesh Scouts, demonstrating his early leadership qualities. He has been part of the “International Astronomical Search Collaboration” project by NASA (2021), showcasing his academic prowess in science. Kawsar’s technical training includes the Industrial Training by BREB and a specialized Unique Automation Training. He also played key organizational roles at Daffodil International University, including events such as the Duke of Edinburgh International Award Conference, Parents’ Day, and International Mother Language Day. His participation in disaster response exercises and field training further highlights his diverse skill set. Through these achievements, Kawsar has proven his ability to excel not only in academics but also in extracurricular activities, event management, and community involvement.

 🌍 Research Focus 

Md. Kawsar Ahmed’s research focus revolves around the development of advanced antenna designs for next-generation communication technologies, including 5G and 6G millimeter-wave applications. His work includes performance estimation of slotted inverted F-shaped tri-band antennas for satellite and 5G/mm-wave communications using artificial neural networks (ANN). His research addresses the growing demand for compact and efficient multi-port MIMO antennas, which are crucial for high-frequency communication systems. By leveraging machine learning techniques, he aims to improve the directivity prediction of these systems, enhancing overall performance in real-world applications. His research extends to optimizing antenna structures for various applications in wireless communication, pushing the boundaries of innovation in this rapidly evolving field. Kawsar’s contributions to the field are not only academically significant but also have the potential to make practical impacts in telecommunications, helping industries transition to more advanced and efficient communication technologies.

📖 Publications Top Notes

ANN-based performance estimation of a slotted inverted F-shaped tri-band antenna for satellite/mm-wave 5G application
  • Citations: 1

Mr.Danish Javed | Data Science | Best Researcher Award

Mr.Danish Javed | Data Science | Best Researcher Award

Mr.Danish Javed, Taylor’s University Lakeside Campus, Malaysia

Danish Khan is a Ph.D. scholar specializing in Data Science at Taylor’s University, Malaysia, where he is advancing research in natural language processing (NLP). With a strong academic background in Software Engineering from Bahria University, Islamabad, Danish has built expertise in Python, machine learning, and deep learning. He has held teaching roles as a Senior Lecturer at the University of Central Punjab, Lahore, and is currently a tutor at Taylor’s University, Malaysia. His career reflects a commitment to advancing computer science education, mentoring students, and leading post-graduate councils. Danish is also a prolific researcher, contributing to various data science and sentiment analysis projects, particularly in the analysis of social media content and NLP.

Professional Profile

google scholar

Summary of Suitability for the Research for Best Researcher Award

Danish Javed presents a strong candidacy for the Research for Best Researcher Award based on his significant academic and research contributions, particularly in the fields of data science, machine learning, and natural language processing (NLP). His ongoing PhD in Data Science from Taylor’s University demonstrates his deep commitment to advancing research, especially in topics like sentiment analysis, deep learning, and Twitter bot detection. Danish has published research in Scopus-indexed conferences and Q1/Q4 journals, which highlights the academic impact of his work.

🎓 Education 

Danish Khan has consistently pursued excellence in academia, currently working toward his Ph.D. in Data Science at Taylor’s University, Lakeside Campus, Malaysia. His doctoral research focuses on natural language processing (NLP), specifically exploring frameworks for sentiment analysis, bot detection, and text analytics. Prior to his Ph.D., Danish earned his M.S. in Software Engineering from Bahria University, Islamabad, Pakistan, where he delved into the intricacies of machine learning, image processing, and artificial intelligence. His academic foundation also includes a B.S. in Software Engineering from Bahria University, during which he developed strong programming skills in Python, Java, and C++, equipping him with the tools to tackle complex computational problems. His academic journey reflects his deep interest in understanding data structures and algorithms, making him proficient in implementing advanced analytics and programming solutions.

💼 Experience 

Danish Khan has a broad range of teaching and leadership experience, with over five years in academia. He is currently a Tutor at Taylor’s University, Malaysia, where he conducts tutorials in data science, supervises student projects, and plays a key role in shaping the post-graduate student experience. He previously served as the President of the Post-Graduate Student Council, organizing events and representing student perspectives in university meetings. Prior to his current role, Danish was a Senior Lecturer in the Faculty of Information Technology at the University of Central Punjab, Lahore, where he taught computer science and software engineering courses, supervised final-year projects, and contributed to extracurricular activities such as organizing sporting events. Additionally, Danish has experience as a QA Analyst at Orbit Institute of Technology in Lahore, where he maintained the quality standards in the Software Engineering department.

🏅Awards and Honors

Danish Khan has received notable recognition throughout his academic and professional career. His published research in data science and natural language processing has been featured in prominent Scopus-indexed conferences and reputed journals. As a Ph.D. scholar, he has been honored with several merit-based scholarships for academic excellence. Danish was also recognized for his leadership efforts while serving as President of the Post-Graduate Student Council at Taylor’s University, where he played a pivotal role in advocating for post-graduate student welfare. During his tenure at the University of Central Punjab, Lahore, he earned commendations for his outstanding contributions to teaching and student mentorship. Additionally, his development of an Android application, “Forex Profit Gain,” has garnered attention, earning placement in the Google Play Store. These accolades reflect his deep commitment to both academic rigor and innovative problem-solving in the field of data science.

🌐 Research Focus 

Danish Khan’s research is centered on data science, particularly natural language processing (NLP), machine learning, and sentiment analysis. His Ph.D. work at Taylor’s University, Malaysia, focuses on advanced techniques in deep learning to analyze and classify text-based data. His key areas of research include social media analytics, Twitter bot detection, and sentiment analysis of public opinion during crises such as the COVID-19 pandemic. Danish has contributed to frameworks that improve sentiment analysis by leveraging oversampling techniques and random minority oversampling, which enhance the accuracy of sentiment classification in user-generated content. His research also extends to explainable artificial intelligence (AI), where he has designed models for transparent and interpretable detection of bots on social media platforms. Danish’s academic pursuit aims to contribute practical, data-driven insights to solve real-world problems using cutting-edge AI and NLP technologies.

📖 publications Top Notes

“Framework for Improved Sentiment Analysis via Random Minority Oversampling for User Tweet Review Classification.”
Citation count: 25
“Deep Learning Based Sentiment Analysis of COVID-19 Tweets via Resampling and Label Analysis.”
Citation count: 6
“Football Analytics for Goal Prediction to Assess Player Performance.”
Citation count: 4
“Explainable Twitter Bot Detection Model for Limited Features.”
Citation count: 2
“Explainable Machine Learning Based Model for Heart Disease Prediction.”
“Analyzing the Efficacy of Bot Detection Methods on Twitter/X.”