Zhengming Jiang | Computer Science | Best Academic Researcher Award

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Dr. Zhengming Jiang | Computer Science | Best Academic Researcher Award

Teacher from Guangdong Polytechnic Normal University, China

Dr. Zhengming Jiang is a dedicated academic and researcher in the field of information and communication engineering, currently serving as a lecturer at the Industrial Training Center, Guangdong Polytechnic Normal University. With over a decade of experience in academia and research, he has established himself as a promising expert in dual-function radar-communication systems, intelligent reflecting surfaces, and physical layer security. Dr. Jiang obtained his Ph.D. and Master’s degrees from Shenzhen University, which shaped his foundational expertise in advanced communication technologies. In recent years, he has gained further prominence through his postdoctoral work at the Shenzhen International Graduate School of Tsinghua University, in collaboration with Guangdong Kekaida Intelligent Robotics Co., Ltd. His scholarly output includes several first-author papers in top-tier journals such as the IEEE Internet of Things Journal and Digital Signal Processing. He has also been awarded and has led numerous national and provincial research grants, showcasing his capacity for high-impact research. Furthermore, Dr. Jiang has made significant contributions to the applied technology sector, as evidenced by his patented innovations in signal processing and communication security. His academic rigor, project leadership, and technical acumen place him among the leading emerging scholars in the field.

Professional Profile

Education

Dr. Zhengming Jiang has pursued a comprehensive academic path in communication engineering, demonstrating consistent dedication to excellence throughout his educational journey. He began his undergraduate studies in 2007 at Shaoyang University, where he obtained a Bachelor’s degree in Communication Engineering in 2011. His strong academic performance and interest in signal systems led him to Shenzhen University, where he pursued a Master’s degree in Communication and Information Systems, graduating in 2014. Motivated by a desire to delve deeper into advanced research, he continued at Shenzhen University to earn his Ph.D. in Information and Communication Engineering from 2017 to 2020. His doctoral research was instrumental in shaping his specialization in dual-function radar-communication systems and signal processing techniques. His academic foundation not only reflects deep theoretical knowledge but also practical application, which he further developed during his postdoctoral fellowship beginning in 2023 at the Tsinghua Shenzhen International Graduate School and Guangdong Kekaida Intelligent Robotics Co., Ltd. This postdoctoral phase has allowed him to engage in high-level collaborative research and contribute to national-level innovations. Dr. Jiang’s educational background showcases a well-rounded and in-depth mastery of his field, equipping him with the skills necessary for high-impact research and academic leadership.

Professional Experience

Dr. Zhengming Jiang has a diverse portfolio of academic and research experience, reflecting his progression from foundational teaching roles to high-level research leadership. His professional journey began in 2014 when he served as a teaching assistant in the Computer Science Department at Guangdong University of Science and Technology. Over the course of three years, he contributed to curriculum delivery and engaged students in the fundamentals of communication systems. In January 2021, he advanced to a lecturer position at the Industrial Training Center of Guangdong Polytechnic Normal University, where he continues to teach and mentor students while spearheading innovative research projects. His academic expertise is matched by his research initiative; he has successfully secured and managed several university- and province-level research grants as principal investigator. Most recently, in November 2023, Dr. Jiang began a prestigious postdoctoral appointment at the Shenzhen International Graduate School of Tsinghua University in conjunction with Guangdong Kekaida Intelligent Robotics Co., Ltd. This dual-institution position has enabled him to engage in interdisciplinary collaboration and contribute to cutting-edge research in intelligent communication technologies. His professional trajectory reflects a balance between teaching, project leadership, and research excellence, positioning him as a versatile academic and technical expert.

Research Interests

Dr. Zhengming Jiang’s research interests are deeply rooted in the development and integration of communication and radar technologies. He focuses on dual-function radar-communication systems, an emerging field that enhances spectrum efficiency by combining communication and sensing capabilities. His work explores the use of intelligent reflecting surfaces (IRS) to optimize signal propagation, minimize interference, and improve system robustness in dynamic environments. Dr. Jiang is particularly interested in the physical layer security of vehicular and automotive systems, addressing the growing need for secure communication in intelligent transportation infrastructure. Additionally, his research covers robust beamforming design, especially in complex or error-prone environments, which is vital for ensuring reliable wireless performance. Another important theme in his work is the integration of communication and sensing in millimeter-wave systems, contributing to the advancement of next-generation wireless networks. His interests align with current global trends in smart mobility, 6G technologies, and secure wireless communication. Dr. Jiang’s research not only addresses theoretical challenges but also emphasizes practical implementation and innovation, which is evident in his industry collaboration and patent filings. His ability to identify emerging needs and apply theoretical insights to real-world applications makes his research highly impactful and forward-thinking.

Research Skills

Dr. Zhengming Jiang possesses a comprehensive and advanced skill set in information and communication engineering, with specialized expertise in dual-function radar-communication systems and intelligent signal processing. He has demonstrated exceptional capability in the design and optimization of intelligent reflecting surfaces (IRS), focusing on enhancing wireless signal strength and quality in complex environments. His proficiency in robust beamforming techniques enables him to manage signal integrity in the presence of interference and modeling errors, a critical skill in modern communication systems. Dr. Jiang is also well-versed in millimeter-wave communications, particularly in scenarios requiring high-frequency data transmission and sensing integration. His ability to simulate and model physical layer systems is complemented by strong coding and algorithm development skills, particularly using MATLAB and Python. Furthermore, he is adept at experimental validation and hardware-software interfacing, which are essential for real-world implementation. His capacity to lead multidisciplinary research projects and collaborate with engineering teams has been proven through his work at Guangdong Kekaida and Tsinghua Shenzhen. Whether it is theoretical modeling, algorithm design, or system prototyping, Dr. Jiang exhibits a rare blend of analytical precision and engineering pragmatism, making him a valuable asset in both academic and applied research environments.

Awards and Honors

Dr. Zhengming Jiang has received recognition for his outstanding contributions to the field of communication systems through both academic and innovation-related achievements. Among his notable accomplishments is his role as the principal investigator and key contributor in several research projects funded by prestigious institutions such as the National Natural Science Foundation of China (NSFC). One of his ongoing research contributions includes participation in a significant NSFC general project valued at 550,000 RMB, focused on the modulation mechanisms of AlGaN-based ultraviolet communication devices. He has also led and completed provincial and university-level research grants totaling over 400,000 RMB, demonstrating his ability to conceptualize and execute high-impact studies. His publication record includes multiple first-author papers in high-impact journals such as IEEE Internet of Things Journal and IEEE Systems Journal, underscoring his leadership in scholarly dissemination. In addition, Dr. Jiang is a named inventor in a Chinese patent related to robust anti-interference navigation technologies, further showcasing his innovative contributions. These accomplishments reflect a strong recognition from both academic peers and industry stakeholders. While formal academic honors or teaching awards were not listed, his record of funded research, scholarly output, and intellectual property firmly positions him as a decorated and respected figure in his field.

Conclusion

In conclusion, Dr. Zhengming Jiang stands out as an accomplished early-career researcher with a clear trajectory toward long-term excellence in the fields of communication and radar systems. His educational and professional journey reflects a strong foundation, advanced specialization, and continuous development through prestigious appointments and collaborations. He has consistently demonstrated leadership in research, as evidenced by his role in major grant-funded projects, first-author publications in internationally reputed journals, and innovation in practical technologies such as anti-interference navigation systems. Dr. Jiang’s work directly aligns with pressing global needs, including secure and intelligent vehicular communications, spectrum efficiency, and next-generation wireless networks. His research is not only theoretically robust but also geared toward real-world applications, making a meaningful contribution to both academia and industry. With further expansion into global collaborations, mentorship roles, and interdisciplinary projects, Dr. Jiang is well-poised to reach even higher levels of academic recognition. Based on his current record, he is a strong candidate for awards recognizing research excellence and innovation. His blend of technical expertise, academic productivity, and real-world impact positions him as a leading researcher worthy of distinction.

Publications Top Notes

1. On the Physical Layer Security of Automotive Dual-Function Radar-Communication Systems

Authors: Zheng-Ming Jiang, Mohamed Rihan, Qijun Deng, Ehab Mahmoud Mohamed, Haitham S. Khallaf, Xiaojun Wang, Rasha Omar
Journal: IEEE Internet of Things Journal
Year: 2024
Volume/Issue: 11(3), Pages 5090–5104

2. Intelligent Reflecting Surface Aided Dual-Function Radar and Communication System

Authors: Zheng-Ming Jiang, Mohamed Rihan, Qiang Li, Lei Huang, Qijun Deng, Jihong Zhang, Ehab Mahmoud Mohamed
Journal: IEEE Systems Journal
Year: 2021
Volume/Issue: 16(1), Pages 475–486
Citations: 113 citations

3. Intelligent Reflecting Surface Aided Co-existing Radar and Communication System

Authors: Zheng-Ming Jiang, Qijun Deng, Min Huang, Zhenxing Zheng, Xiaojun Wang, Mohamed Rihan
Journal: Digital Signal Processing
Year: 2023
Volume: 141

4. Robust Beamforming Design for Co-existing Radar and Communication System with Bounded Error Model

Authors: Qijun Deng, Zhengming Jiang, Senming Zhong, Min Huang, Qiang Li, Mohamed Rihan
Journal: IEICE Transactions on Communications
Year: 2024
Volume/Issue: 12(3)

5. Maximum Likelihood Approach to DoA Estimation Using Lens Antenna Array

Authors: Zheng-Ming Jiang, Peichang Zhang, Mohamed Rihan, Lei Huang, Jihong Zhang
Journal: EURASIP Journal on Wireless Communications and Networking
Year: 2019
Volume: 2019: Article 1

Tejasva Maurya | Computer Science | Best Researcher Award

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Mr. Tejasva Maurya | Computer Science | Best Researcher Award

Shri Ramswaroop Memorial University, India

Tejasva Maurya is a dedicated researcher specializing in artificial intelligence, deep learning, and data science. With a strong academic background in computer science and engineering, he has made significant contributions to AI-driven solutions in smart traffic management, healthcare applications, and natural language processing. His work focuses on applying advanced machine learning models to real-world challenges, particularly in image processing, sentiment analysis, and human-computer interaction. Tejasva has published research in reputable journals and book chapters, showcasing his expertise in AI and its interdisciplinary applications. He has also gained valuable industry experience through internships in data science and analytics, working on projects that optimize machine learning models and enhance data-driven decision-making. His technical proficiency includes programming in Python, deep learning frameworks like PyTorch, and working with Hugging Face models for NLP and computer vision tasks. With multiple achievements in AI research, including a Scopus-indexed publication and competition awards, Tejasva continues to push the boundaries of innovation in artificial intelligence. His long-term goal is to contribute groundbreaking research in AI while bridging the gap between theoretical advancements and practical implementations.

Professional Profile

Education

Tejasva Maurya is currently pursuing a Bachelor of Technology in Computer Science and Engineering at Shri Ramswaroop Memorial University, where he has developed a strong foundation in programming, machine learning, and AI-driven applications. His coursework has provided extensive exposure to algorithms, data structures, deep learning, and computer vision techniques. Prior to his undergraduate studies, he completed his Intermediate education under the CBSE Board in 2021, securing an impressive 88.88%, which highlights his academic excellence and analytical abilities. His passion for artificial intelligence and research was evident early on, leading him to explore AI-related projects and specialized training in machine learning. Throughout his education, he has engaged in practical AI applications, contributing to his ability to develop innovative solutions in deep learning, NLP, and computer vision. His university studies have been complemented by self-driven research initiatives and internships, allowing him to apply theoretical knowledge to real-world problems. Tejasva’s continuous learning approach and commitment to AI research position him as an emerging talent in the field of artificial intelligence.

Professional Experience

Tejasva Maurya has gained substantial industry experience through internships and research projects in data science and machine learning. As a Data Scientist Intern at DevTown (June 2023 – December 2023), he worked on developing and optimizing deep learning models using PyTorch for real-world applications, focusing on NLP, image classification, and generative adversarial networks (GANs). He was responsible for designing data pipelines, preprocessing data, and conducting exploratory data analysis, ensuring the models were efficient and accurate. Additionally, Tejasva worked as a Data Analyst Trainee at MedTourEasy (August 2023 – August 2023), where he specialized in data visualization and statistical analysis. His role involved extracting actionable insights from large datasets using Python and Tableau and collaborating with different teams to implement data-driven strategies. His professional experience has strengthened his ability to apply AI techniques to practical problems, enhancing his understanding of machine learning implementation in different sectors. Through these roles, he has built strong analytical skills and technical expertise, preparing him for more advanced research in artificial intelligence and data science.

Research Interests

Tejasva Maurya’s research interests lie in artificial intelligence, deep learning, natural language processing, and computer vision. His primary focus is on developing AI-driven solutions for real-world applications, including smart traffic management, healthcare technology, and human-computer interaction. His work in vehicle classification using deep learning demonstrates his expertise in YOLO-based object detection models and their application in traffic surveillance and smart city planning. Additionally, he is keen on sentiment analysis and speech processing, contributing to AI models that improve text-to-speech (TTS) synthesis and NLP-based insights. His interest in federated learning for agricultural applications highlights his commitment to interdisciplinary research, exploring AI’s role in optimizing farming techniques and market stability. Tejasva is also exploring artificial emotional intelligence for psychological and mental health assessments, aiming to create AI models that assist in mental health diagnosis and emotional analysis. With a strong foundation in machine learning and AI, he aims to bridge the gap between theoretical advancements and practical AI implementations, driving innovation in multiple domains.

Research Skills

Tejasva Maurya possesses advanced research skills in machine learning, deep learning, and AI model development. His technical expertise includes Python programming, with proficiency in PyTorch, scikit-learn, NumPy, and OpenCV for implementing AI-based solutions. He has hands-on experience in computer vision techniques, including real-time object detection, image segmentation, and gesture-based human-computer interaction, leveraging tools like Mediapipe and Haar Cascades. In natural language processing (NLP), he is skilled in text processing, speech-to-text, and fine-tuning transformer models using Hugging Face frameworks. His research methodology includes data preprocessing, model fine-tuning, hyperparameter optimization, and performance evaluation using metrics like mAP and F1-score. He is proficient in working with large-scale datasets and has successfully published research on vehicle classification, federated learning, and AI-based healthcare applications. Additionally, he has experience in GANs and diffusion models, focusing on synthetic media generation and speech dataset augmentation. His ability to integrate AI solutions across different fields demonstrates his versatility as a researcher and innovator.

Awards and Honors

Tejasva Maurya has received multiple accolades for his contributions to AI research and innovation. One of his most notable achievements is publishing a Scopus-indexed journal article, “Real-Time Vehicle Classification Using Deep Learning—Smart Traffic Management,” in Engineering Reports (Wiley), which underscores the real-world impact of his research. He has also co-authored multiple book chapters in prestigious publishers like Nova Science, Wiley, and Bentham Science, covering AI applications in healthcare, federated learning, and artificial emotional intelligence. His research has been recognized for its contribution to intelligent traffic systems, patient-centric healthcare, and AI-powered decision-making. In addition to his research achievements, he secured 1st position in KIMO’s-Edge’ 23 Technology Competition, a testament to his problem-solving skills and technical expertise. His consistent excellence in AI research and project development has positioned him as an emerging leader in the field of artificial intelligence, with a strong track record of achievements.

Conclusion

Tejasva Maurya is a promising researcher in artificial intelligence, with expertise in deep learning, NLP, and computer vision. His strong academic foundation, technical proficiency, and impactful research make him a strong contender for recognition as a leading researcher in AI. With multiple publications, real-world AI applications, and industry experience, he has demonstrated both theoretical knowledge and practical problem-solving abilities. While he has made significant contributions, focusing on publishing in high-impact AI conferences, securing patents, and expanding interdisciplinary collaborations would further enhance his research portfolio. His dedication to bridging AI theory with real-world applications highlights his potential to contribute groundbreaking advancements in artificial intelligence.

Publications Top Notes

  1. Title: Real Time Vehicle Classification Using Deep Learning—Smart Traffic Management
    Authors: Maurya, T., Kumar, S., Rai, M., Saxena, A.K., Goel, N., and Gupta, G.
    Publication: Engineering Reports, 7: e70082 (2025)
    DOI: https://doi.org/10.1002/eng2.70082

  2. Title: Patient Centric Healthcare
    Authors: Maurya, T., Kumar, S., Rai, M., Saxena, A.K.
    Book: Harnessing the Power of IoT-Enabled Machine Learning in Healthcare Applications
    Editors: Mritunjay Rai, Ravindra Kumar Yadav, Neha Goel, and Maheshkumar H. Kolekar

  3. Title: Integrating Artificial Intelligence and Deep Learning in Classification and Taking Care of DFU
    Authors: Kumar, S., Maurya, T., Rai, M., Saxena, A.K., Pandey, J.K.
    Book: Machine Learning-Based Decision Support Systems for Diabetic Foot Ulcer Care
    Editors: Mritunjay Rai, Jay Kumar Pandey, and Abhishek Kumar Saxena

  4. Title: Federated Learning-Based Approach for Crop Recommendation and Market Stability in Agriculture
    Authors: Kumar, S., Maurya, T., Rai, M., Saxena, A.K.
    Book: Federated Learning for Smart Agriculture and Food Quality Enhancement
    Editors: Padmesh Tripathi, Bhanumati Panda, Shanthi Makka, Reeta Mishra, S. Balamurugan, and Sheng-Lung Peng

  5. Title: Artificial Emotional Intelligence for Psychological State and Mental Health Assessment
    Authors: Kumar, S., Maurya, T., Rai, M., Saxena, A.K.
    Book: Artificial Emotional Intelligence: Fundamentals, Challenges and Applications
    Editors: Padmesh Tripathi, Krishna Kumar Paroha, Reeta Mishra, and S. Balamurugan

Wisal Zafar | Computer Science | Best Researcher Award

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Mr. Wisal Zafar | Computer Science | Best Researcher Award

Lecturer at Cecos university of information technology and emerging sciences, Pakistan.

Mr. Wisal Zafar is a dedicated researcher and lecturer with a strong background in software engineering, focusing on artificial intelligence, machine learning, and deep learning applications in healthcare. Born on March 25, 1999, in Peshawar, Pakistan, he has consistently demonstrated a passion for advancing technology’s role in solving real-world problems. He has developed and published research that leverages machine learning for medical diagnoses, including brain tumor analysis and diabetes prediction. As a lecturer and Electronic Data Processing (EDP) Officer at Iqra National University, he is committed to mentoring students and contributing to the field through both teaching and research. His work is distinguished by his continuous learning, keeping pace with emerging trends in AI and big data. Mr. Zafar’s career is marked by his enthusiasm for interdisciplinary research, integrating software engineering with advancements in health and data science. He is eager to expand his research contributions further through collaborations and innovative projects that address global challenges using advanced technologies.

Professional Profile

Education

Wisal Zafar holds an MS in Software Engineering from Iqra National University, Hayatabad Peshawar, completed in July 2024 with a commendable CGPA of 3.62/4.00. His postgraduate studies provided him with in-depth knowledge of advanced topics like artificial intelligence, data analysis, and big data. Prior to this, he earned a BS in Software Engineering from the same institution in October 2020, with a CGPA of 3.47/4.00, building a strong foundation in software development and computer science principles. His academic journey started with an intermediate qualification from Capital Degree College, Peshawar, where he scored 700 out of 1100 marks, and continued with his matriculation from The Jamrud Model High School, achieving 824 out of 1100 marks. His educational background is characterized by consistent academic performance and a focus on both theoretical and practical aspects of software engineering, which has prepared him for his subsequent roles in academia and research.

Professional Experience

Wisal Zafar currently serves as a Lecturer at Iqra National University, Hayatabad, Peshawar, where he has been teaching various software engineering subjects since January 2023. His areas of instruction include Data Science, Artificial Intelligence, Machine Learning, Data Structures, and Algorithms, allowing him to impart advanced knowledge to students and prepare them for careers in technology. Alongside his role as a lecturer, he also holds the position of Electronic Data Processing (EDP) Officer at the same university, a role he has been fulfilling since October 2021. In this capacity, he manages data processing tasks, ensuring the effective handling of academic data and resources. Previously, he gained practical experience as a Junior Web Developer at Pakistan Online Services Software House, where he worked from November 2020 to April 2021, specializing in web development using PHP, Laravel, JavaScript, and other technologies. This diverse experience in academia and industry has equipped Mr. Zafar with the skills to blend theoretical concepts with real-world applications, making him an effective educator and a valuable contributor to research.

Research Interests

Wisal Zafar’s research interests are centered around artificial intelligence (AI), machine learning (ML), deep learning, and their applications in healthcare and data analysis. He is particularly fascinated by the potential of AI and ML in developing advanced diagnostic tools, aiming to improve medical outcomes through data-driven insights. His recent research projects have explored the use of deep learning techniques like YOLOv8s and U-Net for multi-class brain tumor analysis, integrating detection, localization, and segmentation of tumors using MRI data. Additionally, he has delved into predictive models for diabetes diagnosis using various ML algorithms, such as Decision Trees, K-Nearest Neighbors, Random Forest, Logistic Regression, and Support Vector Machines. His interests extend to big data analytics and the role of data science in enhancing information retrieval and management in medical libraries. Through his work, Wisal Zafar seeks to advance the intersection of technology and healthcare, utilizing cutting-edge algorithms and data processing techniques to solve critical challenges and improve human well-being.

Research Skills

Wisal Zafar possesses a diverse skill set in artificial intelligence, machine learning, data analysis, and big data management, making him adept at tackling complex research challenges. He has extensive experience in using programming languages like Python and C++, which he applies to develop machine learning models and algorithms. His technical expertise includes working with deep learning frameworks, as seen in his research on brain tumor analysis using advanced models such as YOLOv8s and U-Net. Additionally, Wisal has proficiency in cloud computing and handling large datasets, which supports his work in big data analytics and the implementation of data-driven decision-making tools. His hands-on experience as a Research Assistant has further refined his skills in conducting surveys, data preprocessing, and statistical analysis. Mr. Zafar is also skilled in web development using frameworks like Laravel and JavaScript, allowing him to create interactive platforms for research applications. His ability to integrate these skills into interdisciplinary projects makes him a capable researcher with a focus on innovation and problem-solving.

Award Recognition

Wisal Zafar’s dedication to research and academic excellence has earned him recognition in the academic community, though he is still working towards broader award recognitions. His recent research publications, including studies on brain tumor analysis and diabetes prediction using machine learning, have been well-received and published in respected journals. These works have contributed significantly to the fields of AI in healthcare and big data analytics, positioning him as a promising researcher. His role as a Lecturer at Iqra National University also reflects the acknowledgment of his expertise, as he is entrusted with educating the next generation of software engineers. Additionally, Wisal has completed several certified courses from platforms like Coursera, receiving certificates in advanced learning algorithms, deep learning, and image processing with Python, which underscore his commitment to continuous learning. While he may not yet have specific awards, his publications, teaching contributions, and commitment to research excellence serve as strong indicators of his potential for future recognition in the field.

Awards and Honors

Wisal Zafar has demonstrated a commitment to continuous professional development through various certifications and achievements, contributing to his expertise in software engineering and AI. He has completed notable courses such as AI for Everyone and Advanced Learning Algorithms through Coursera, which are associated with respected institutions like DeepLearning.AI and Stanford University. These certifications have enhanced his knowledge of machine learning, deep learning, and image processing, enabling him to apply advanced concepts in his research. While he has not yet received specific formal awards, his role as a Lecturer at Iqra National University and his position as an Electronic Data Processing (EDP) Officer are testaments to his skills and recognition within the academic community. His contributions to research, especially in the areas of AI applications in healthcare, have been acknowledged through the publication of his work in peer-reviewed journals. Wisal Zafar’s ongoing pursuit of excellence, both in research and teaching, positions him as a candidate worthy of future awards and honors in the field of software engineering and AI.

Conclusion:

Wisal Zafar has demonstrated considerable research skills and expertise in the field of software engineering, particularly in applying machine learning and AI to medical problems. His academic background, technical skills, and research publications make him a strong contender for the Best Researcher Award. While he could benefit from diversifying his research and increasing his international presence, his current achievements in AI-driven healthcare solutions and data analytics set a solid foundation for this recognition.

Publications Top Notes

  1. Enhanced TumorNet: Leveraging YOLOv8s and U-net for superior brain tumor detection and segmentation utilizing MRI scans
    • Authors: Zafar, W., Husnain, G., Iqbal, A., AL-Zahrani, M.S., Naidu, R.S.
    • Journal: Results in Engineering
    • Year: 2024
    • Volume: 24
    • Article ID: 102994
    • Type: Open access
  2. Revolutionizing Diabetes Diagnosis: Machine Learning Techniques Unleashed
    • Authors: Shaukat, Z., Zafar, W., Ahmad, W., Ghadi, Y.Y., Algarni, A.
    • Journal: Healthcare (Switzerland)
    • Year: 2023
    • Volume: 11
    • Issue: 21
    • Article ID: 2864
    • Citations: 1
    • Type: Open access

 

 

 

 

Umaa Mahesswari G | Artificial Intellugence Engineering | Best Researcher Award

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Ms. Umaa Mahesswari G | Artificial Intellugence Engineering | Best Researcher Award

Research Scholar at College of Engineering Guindy, Anna University, India

G. Umaa Mahesswari is a highly motivated research scholar from Chennai, India, with a passion for innovation and technology. With a solid foundation in Computer Science, her academic journey spans from her B.E. at R.M.K College to a Ph.D. at Anna University, specializing in Big Data Analytics. Umaa has worked on significant projects like IoT-based air pollution detection and digital inscription readers for ancient Tamil stone inscriptions. A recipient of the prestigious Anna Research Fellowship, she is dedicated to leveraging technology for social good. Her technical expertise and passion for research make her a valuable asset in the R&D domain.

Profile

Education 📘🎓

Bachelor of Engineering (B.E.) in Computer Science from R.M.K College of Engineering and Technology, Chennai (2015-2019), with a CGPA of 8.65.Master of Engineering (M.E.) in Computer Science with a Specialization in Big Data Analytics from College of Engineering, Guindy, Anna University, Chennai (2019-2021), with a CGPA of 9.07.Ph.D. in Computer Science from College of Engineering, Guindy, Anna University (2023-present).Completed the Google Data Analytics Professional Specialization Course via Coursera (2021), enhancing her skills in data-driven problem-solving.

Experience 💼📊

Research Project Assistant at Tamil Virtual Academy (2022), working on the development of an inscription reader for ancient Tamil temple inscriptions, supervised by Dr. P. Uma Maheswari.Undergraduate project on IoT-based air pollution detection and analysis, focusing on real-time data collection and environmental monitoring.Postgraduate project on predictive analytics for plastic disposal by Walmart India, contributing to sustainable business solutions.Proficient in machine learning, data visualization, and SQL, with significant contributions to the field of Big Data Analytics.

Awards and Honors 🏆🎖

Academic Topper in the third year of her B.E. program, demonstrating her dedication to academic excellence.Nominee for Best Outgoing Student Award at the end of her undergraduate studies.Prize winner in several intra-college cultural competitions, showcasing her versatility beyond academics.Anna Research Fellowship Holder from 2023 to 2025, awarded in recognition of her research potential in Big Data Analytics.Published academic papers in esteemed venues like Springer ICTIS and Computer Society of India, highlighting her contributions to the academic community.

Research Focus 🔍💡

Umaa Mahesswari’s research focuses on leveraging Big Data Analytics, Machine Learning, and Deep Learning to solve pressing societal challenges. Her projects span diverse areas such as IoT-based environmental monitoring, predictive analytics for waste management, and digital solutions for heritage preservation (Tamil inscriptions). She aims to develop data-driven solutions that improve sustainability and drive innovation. Her ongoing Ph.D. research explores pattern recognition and data visualization techniques to extract meaningful insights from large datasets, with the goal of enhancing decision-making processes in both academic and practical settings.

Conclusion

G. Umaa Mahesswari is an exceptional candidate for the Best Scholar Award due to her innovative research, academic achievements, and technical expertise. By further broadening her research scope and international collaborations, she could elevate her already impressive profile and contribute even more profoundly to the global research community.

Publication Top Notes

SmartScanPCOS: A Feature-Driven Approach to Cutting-Edge Prediction of Polycystic Ovary Syndrome using Machine Learning and Explainable Artificial Intelligence

Journal: Heliyon
Published: October 2024
DOI: 10.1016/j.heliyon.2024.e39205
Contributors: G. Umaa Mahesswari; P Uma Maheswari

Abid Iqbal | Artificial Intelligence | Best Researcher Award

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Assist Prof Dr. Abid Iqbal | Artificial Intelligence | Best Researcher Award

Assistant Professor at King Faisal University, Saudi Arabia

Dr. Abid Iqbal is an accomplished Assistant Professor at the University of Engineering and Technology Peshawar, specializing in Electrical Engineering and artificial intelligence. He earned his Ph.D. from Griffith University, Australia, where he researched piezoelectric energy harvesters. With a strong academic background, he ranked first in his Master’s program at Ghulam Ishaq Khan Institute, Pakistan. Dr. Iqbal has a diverse professional experience, including roles as an Electrical Design Engineer and Research Assistant. His expertise encompasses developing embedded devices and innovative teaching methodologies, mentoring students, and conducting impactful research. He has successfully secured funding for multiple projects in AI applications for health and agriculture. Dr. Iqbal’s publication record includes numerous papers in reputable journals, reflecting his commitment to advancing knowledge in his field. His technical skills in programming and software further enhance his research capabilities, making him a valuable asset to academia and industry.

Profile

Education

Dr. Abid Iqbal is a highly accomplished academic with a solid educational foundation in electrical and electronics engineering. He earned his Ph.D. from the Queensland Micro- and Nanotechnology Centre at Griffith University, Australia, from April 2013 to February 2017. His doctoral research focused on the design, fabrication, and analysis of aluminum nitride (AlN)/silicon carbide (SiC)-based piezoelectric energy harvesters, contributing significantly to renewable energy technologies. Prior to his Ph.D., Dr. Iqbal completed his Master’s degree in Electronics Engineering at the Ghulam Ishaq Khan Institute in Topi, Swabi, Pakistan, graduating with a remarkable GPA of 3.88/4 and securing the top position in his class. His academic journey began with a Bachelor’s degree in Electrical Engineering from the University of Engineering & Technology in Peshawar, Pakistan, where he was recognized as an outstanding student. Dr. Iqbal’s educational background reflects his dedication and expertise in his field, laying a strong foundation for his professional career.

Professional Experience

Dr. Abid Iqbal is an accomplished electrical engineer currently serving as an Assistant Professor at the University of Engineering and Technology Peshawar since August 2019. In this role, he has been instrumental in teaching undergraduate courses in Electrical Engineering, developing innovative teaching methods, and mentoring students on research projects. Prior to this position, he worked as an Electrical Design Engineer at Alliance Power and Data in Australia, focusing on ERGON and NBN projects. He also contributed to the development of embedded systems for individuals with disabilities while employed as an Electronic Engineer at Community Lifestyle Support. His research experience includes a significant role as a Research Assistant at Griffith University, where he worked on piezoelectric devices for harsh environments and gained expertise in various semiconductor fabrication processes. Additionally, he has served as a lecturer at Comsat Institute of Information Technology and worked as a research associate at the City University of Hong Kong, demonstrating a robust and diverse professional background in academia and industry.

Research Interest

Dr. Abid Iqbal’s research interests lie at the intersection of electrical engineering and artificial intelligence, focusing on the development of innovative technologies that enhance energy efficiency and improve healthcare outcomes. His work includes designing and fabricating advanced piezoelectric energy harvesters using AlN/SiC materials, aimed at harnessing renewable energy sources. Additionally, Dr. Iqbal is deeply involved in projects utilizing artificial intelligence for agricultural applications, such as real-time disease detection in crops, and developing telehealth systems that leverage IoT technology to monitor patient health remotely. He has a keen interest in embedded systems and the design of hardware for assistive technologies, including portable ventilators and muscle sensors for individuals with disabilities. Through his research, Dr. Iqbal aims to contribute to sustainable energy solutions and advancements in healthcare technology, fostering a multidisciplinary approach that integrates engineering principles with artificial intelligence for practical applications.

Research Skills

Dr. Abid Iqbal possesses a robust set of research skills that underscore his expertise in Electrical Engineering and artificial intelligence. His extensive experience in designing and fabricating piezoelectric energy harvesters highlights his proficiency in materials science and device characterization. Dr. Iqbal is adept at using advanced simulation tools such as COMSOL, Ansys, and Coventorware, which facilitate in-depth analysis and optimization of microelectromechanical systems (MEMS). His work on artificial intelligence applications in telehealth and agricultural systems showcases his ability to integrate machine learning techniques with practical engineering solutions. Additionally, Dr. Iqbal has a strong background in programming languages such as Python and MATLAB, enhancing his capability to develop innovative software solutions for complex engineering problems. His involvement in funded projects and numerous publications further illustrates his commitment to advancing research and contributing to knowledge in his field. Overall, Dr. Iqbal’s diverse skills position him as a valuable asset to any research team.

Award and Recognition

Dr. Abid Iqbal is a distinguished electrical engineer and academic known for his significant contributions to the field of electrical and electronics engineering. He has received multiple accolades for his research and academic excellence, including the IGNITE funding for four innovative projects focused on machine learning applications in health and agriculture. Dr. Iqbal was awarded publication scholarships and prestigious Griffith University PhD scholarships, recognizing his outstanding academic performance during his doctoral studies. Additionally, he ranked first among his peers in the Master’s program at Ghulam Ishaq Khan Institute, further demonstrating his commitment to excellence in engineering. His dedication to teaching and mentoring future engineers is evident in his role as an Assistant Professor at the University of Engineering and Technology Peshawar, where he has developed innovative curricula and guided numerous student research projects. Dr. Iqbal’s work has been widely published, contributing significantly to advancements in artificial intelligence, embedded systems, and renewable energy technologies.

Conclusion

Dr. Abid Iqbal is a highly qualified candidate for the Best Researcher Award, demonstrating exceptional expertise in Electrical Engineering and a strong commitment to research and education. His accomplishments in renewable energy research, successful project management, and dedication to mentoring future engineers make him a standout choice. While he has areas for growth, particularly in expanding collaborative networks and enhancing commercialization efforts, his current achievements and potential for future contributions position him as an inspiring figure in his field. This award would not only recognize his past efforts but also encourage his continued pursuit of excellence in research and education.

Publication Top Notes

  1. Enhanced TumorNet: Leveraging YOLOv8s and U-net for superior brain tumor detection and segmentation utilizing MRI scans
    • Authors: Zafar, W., Husnain, G., Iqbal, A., AL-Zahrani, M.S., Naidu, R.S.
    • Year: 2024
    • Journal: Results in Engineering
    • Volume/Page: 24, 102994
  2. Novel dual absorber configuration for eco-friendly perovskite solar cells: design, numerical investigations and performance of ITO-C60-MASnI3-RbGeI3-Cu2O-Au
    • Authors: Hasnain, S.M., Qasim, I., Iqbal, A., Amin Mir, M., Abu-Libdeh, N.
    • Year: 2024
    • Journal: Solar Energy
    • Volume/Page: 278, 112788

 

 

 

Fahd Alharithi | Artificial Intelligence | Best Researcher Award

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Assoc Prof Dr. Fahd Alharithi | Artificial Intelligence | Best Researcher Award

Department chair at Taif University, Saudi Arabia

Dr. Fahd Saad Alharithi is an accomplished researcher and academic with a Ph.D. in Computer Science from Florida Institute of Technology and extensive experience in both teaching and research. Currently an Assistant Professor at Taif University, his research spans a wide array of topics, including medical data categorization, oil spill detection, COVID-19 diagnosis, and IoT security. Dr. Alharithi has published numerous papers in high-impact journals such as Sensors and Remote Sensing, showcasing his innovative approaches and significant contributions to his field. In addition to his research, he has a strong background in teaching, having served as a lecturer and teaching assistant at various institutions. His involvement in volunteer work and leadership roles further highlights his commitment to community service. While his diverse research and impactful publications are noteworthy, highlighting research grants and awards could strengthen his profile for recognition.

Profile

Education

Dr. Fahd Saad Alharithi completed his educational journey with a strong foundation in Computer Science. He earned his Ph.D. from the Florida Institute of Technology, USA, in 2019, where he focused on advanced topics in the field. Prior to that, he obtained his Master of Science degree in Computer Science from the University of New Haven, USA, in 2013. His academic journey began with a Bachelor of Science degree in Computer Science from Taif University, Saudi Arabia, in 2008. This comprehensive educational background, spanning both international and local institutions, has equipped Dr. Alharithi with a robust theoretical and practical understanding of Computer Science, paving the way for his subsequent research and teaching career. His diverse educational experiences contribute significantly to his expertise and innovative approaches in the field.

Professional Experience

Dr. Fahd Saad Alharithi has garnered extensive experience in academia and education, currently serving as an Assistant Professor in the Computer Science Department at Taif University since 2019. His career began with roles as a Lecturer and Teacher Assistant at Taif University and the University of New Haven, where he honed his teaching and research skills. Dr. Alharithi has also contributed as a Trainer at New Horizons Institute, showcasing his versatility in the field. His professional journey is marked by significant research achievements, including innovative publications in medical data categorization, AI-assisted algorithms, and IoT security. His role extends beyond teaching, encompassing volunteer work with the Hemaya Group and leadership positions like President of the Saudi Student Club. Dr. Alharithi’s career reflects a robust blend of research excellence, educational dedication, and active community involvement.

Research Interest

Dr. Fahd Saad Alharithi’s research interests primarily focus on advancing computational methods and applications across various domains. His work explores medical data categorization using flexible mixture models, oil spill detection through SAR image analysis, and the development of hybrid convolutional neural network models for diagnosing diseases from chest X-ray images. Dr. Alharithi is also deeply involved in enhancing IoT security with AI-assisted bio-inspired algorithms and addressing environmental challenges through intelligent garbage detection systems. His research extends to secure communication protocols and energy-efficient solutions for sensor networks, demonstrating a strong emphasis on both practical and theoretical advancements. By integrating innovative methodologies such as deep learning and AI, Dr. Alharithi aims to address complex problems in medical imaging, environmental monitoring, and network security, reflecting a broad and impactful approach to computational science.

Research Skills

Dr. Fahd Saad Alharithi exhibits a robust set of research skills, underscored by his extensive work in computer science and related fields. His proficiency in advanced methodologies, including deep learning, AI-assisted algorithms, and hybrid models, highlights his capacity for innovative problem-solving. Dr. Alharithi’s experience with diverse data types and applications, such as medical data categorization, oil spill detection, and IoT security, demonstrates his ability to tackle complex, interdisciplinary challenges. His strong analytical skills are evident from his impactful publications in high-impact journals like Sensors and Remote Sensing. Additionally, his adeptness in leveraging various computational techniques and his commitment to exploring novel solutions further underscore his research capabilities. Dr. Alharithi’s contributions reflect a deep understanding of both theoretical and practical aspects of his field, positioning him as a skilled researcher with a significant impact on advancing technology and knowledge.

Award and Recognition

Dr. Fahd Saad Alharithi’s research has garnered considerable recognition within the academic community. He has published extensively in high-impact journals, including Sensors, Remote Sensing, and Computers, Materials & Continua, showcasing his significant contributions to fields such as medical data categorization, oil spill detection, and AI-assisted algorithms. His innovative work, particularly in developing hybrid convolutional neural network models and intelligent systems for garbage detection, underscores his leadership in advancing technology. Although specific awards and formal recognitions are not detailed in his resume, Dr. Alharithi’s influential publications and his role in mentoring and educating future researchers highlight his exceptional impact in computer science. His involvement in volunteer activities and community service further demonstrates his commitment to fostering academic and professional excellence.

Conclusion

Dr. Taimoor Asim is a strong candidate for the Best Researcher Award due to his substantial contributions to Mechanical Engineering, particularly in fluid dynamics and renewable energy systems. His extensive research experience, leadership roles, and professional achievements make him a noteworthy contender. To strengthen his candidacy, he could focus on broadening his research impact, exploring diverse research areas, and enhancing community engagement related to his work. Overall, Dr. Asim’s profile reflects a high level of expertise and dedication, aligning well with the criteria for the Best Researcher Award.

Publications Top Notes

  1. Machine learning approaches for advanced detection of rare genetic disorders in whole-genome sequencing
    • Authors: Alzahrani, A.A., Alharithi, F.S.
    • Journal: Alexandria Engineering Journal
    • Year: 2024
    • Volume: 106, pp. 582–593
  2. IoT-enabled healthcare systems using blockchain-dependent adaptable services
    • Authors: Arul, R., Alroobaea, R., Tariq, U., Alharithi, F.S., Shoaib, U.
    • Journal: Personal and Ubiquitous Computing
    • Year: 2024
    • Volume: 28(1), pp. 43–57
    • Citations: 13
  3. A comprehensive cost performance analysis for a QoS-based scheme in network mobility (NEMO)
    • Authors: Hussein, L.F., Abass, I.A.M., Aissa, A.B., Alzahrani, A.A., Alharithi, F.S.
    • Journal: Alexandria Engineering Journal
    • Year: 2023
    • Volume: 76, pp. 349–360
    • Citations: 1
  4. Performance Analysis of Machine Learning Approaches in Automatic Classification of Arabic Language
    • Authors: Alharithi, F.S.
    • Journal: Information Sciences Letters
    • Year: 2023
    • Volume: 12(3), pp. 1563–1578
    • Citations: 1
  5. A blockchain-based hybrid platform for multimedia data processing in IoT-Healthcare
    • Authors: Taloba, A.I., Elhadad, A., Rayan, A., Alharithi, F.S., Park, C.
    • Journal: Alexandria Engineering Journal
    • Year: 2023
    • Volume: 65, pp. 263–274
    • Citations: 74
  6. Optimal Sizing and Deployment of Renewable Energy Generators in Practical Transmission Network Using Grid-Oriented Multiobjective Harmony Search Algorithm for Loss Reduction and Voltage Profile Improvements
    • Authors: Kumar, P., Swarnkar, N.K., Mahela, O.P., Mazon, J.L.V., Alharithi, F.S.
    • Journal: International Transactions on Electrical Energy Systems
    • Year: 2023
    • Volume: 2023, 6315918
    • Citations: 1
  7. Energy-Aware Live VM Migration Using Ballooning in Cloud Data Center
    • Authors: Gupta, N., Gupta, K., Qahtani, A.M., Singh, A., Goyal, N.
    • Journal: Electronics (Switzerland)
    • Year: 2022
    • Volume: 11(23), 3932
    • Citations: 4
  8. NLP-Based Application for Analyzing Private and Public Banks Stocks Reaction to News Events in the Indian Stock Exchange
    • Authors: Dogra, V., Alharithi, F.S., Álvarez, R.M., Singh, A., Qahtani, A.M.
    • Journal: Systems
    • Year: 2022
    • Volume: 10(6), 233
    • Citations: 7
  9. Deep learned BLSTM for online handwriting modeling simulating the Beta-Elliptic approach
    • Authors: Hamdi, Y., Boubaker, H., Rabhi, B., Dhahri, H., Alimi, A.M.
    • Journal: Engineering Science and Technology, an International Journal
    • Year: 2022
    • Volume: 35, 101215
    • Citations: 6
  10. A software for thorax images analysis based on deep learning
    • Authors: Almulihi, A.H., Alharithi, F.S., Mechti, S., Alroobaea, R., Rubaiee, S.
    • Book Chapter: Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention
    • Year: 2022
    • Pages: 1166–1178

 

Mijanur Rahaman | Machin Learning | Excellence in Research

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Mr. Mijanur Rahaman | Machin Learning | Excellence in Research

Assistant Professor at Bangladesh University of Business and Technology (BUBT), Bangladesh.

Mr. Mijanur Rahaman is an accomplished professional with a rich background in academia, research, and teaching. With extensive experience in computer science and engineering, he has excelled in various roles, including Assistant Professor and Lecturer at Bangladesh University of Business & Technology (BUBT). His research interests span diverse areas such as peer-to-peer payment systems, job skill requirements during the COVID-19 pandemic, and web programming curriculum reform. Mr. Rahaman’s contributions to scholarly literature include several published articles in prestigious journals and conferences. Beyond academia, he has actively engaged in software development, database administration, and website design, demonstrating his versatility and technical prowess. His commitment to education, coupled with strong research and technical skills, positions him as a valuable asset in the field of computer science.

Professional Profiles:

Education

Mr. Mijanur Rahaman holds a Bachelor of Science in Engineering (B.Sc. Engg.) in Computer Science & Engineering (CSE) from Bangladesh University of Business & Technology (BUBT). He completed his higher secondary education (Higher Secondary School Certificate – HSC) in Science from Lakshmipur Govt. College and his secondary education (Secondary School Certificate – SSC) in Science from Rakhalia High School, both in Bangladesh. Additionally, he is currently pursuing a Master of Science (MSc) in Computer Science (MScCS) from the American International University-Bangladesh (AIUB).

Professional Experience

Mr. Mijanur Rahaman has extensive professional experience in the field of education and technology. He has served as an Assistant Professor of Computer Science and Engineering (CSE) at Bangladesh University of Business & Technology (BUBT) since February 2016. Prior to this, he worked as a Lecturer in CSE at BUBT from October 2011 to January 2015, and as a Teaching Assistant (TA) in CSE from March 2011 to September 2011. Additionally, he worked as a Part-time Lecturer at Dhaka Edinburgh International College from August 2010 to October 2010. In these roles, he has been actively involved in teaching, curriculum development, and student mentorship, demonstrating his commitment to academic excellence and professional development.

Research Interest

Mr. Mijanur Rahaman’s research interests primarily revolve around areas such as applied research methodology, digitalization, software development, job skill analysis, quantum computing, cloud computing, and web programming. He has contributed to various publications covering topics such as near field peer-to-peer payment systems, IT-software job skill requirements during the COVID-19 pandemic, optimal job allocation algorithms, state-of-the-art reformation of web programming course curriculums, and quantum computing as a service (Qcaas). His diverse research interests reflect his dedication to exploring cutting-edge technologies and their applications in solving real-world problems.

Teaching Experience

Mr. Mijanur Rahaman has extensive teaching experience spanning over a decade. His teaching journey started as a Teaching Assistant (TA) in the Department of Computer Science and Engineering (CSE) at Bangladesh University of Business & Technology (BUBT) in March 2011. From there, he progressed to the role of Lecturer in CSE, where he continued to impart knowledge and motivate students until January 2015. Subsequently, he transitioned to the position of Assistant Professor of CSE at BUBT, where he has been serving since February 2016. Throughout his tenure, Mr. Rahaman has demonstrated a commitment to challenging and inspiring students through in-depth lectures, discussions, and hands-on learning experiences. Additionally, he has actively contributed to curriculum development and research activities, enriching the academic environment of his institution.

Award and Honors

Mr. Mijanur Rahaman has received numerous awards and honors throughout his career, recognizing his significant contributions to academia and programming contests. Notably, he excelled as a contestant in prestigious competitions like the ACM-ICPC Asia Regional Dhaka Site in 2010, where his team achieved the 13th place, and the 2008 Asia Dhaka Contest. His achievements also include receiving an Honorable Mention at the AB Bank-IUT 2nd National ICT Fest 2009. Beyond his individual accomplishments, Mr. Rahaman has demonstrated leadership as a coach for programming contest teams and as Chief Judge at the BUBT Intra-university Programming Contest 2015. Moreover, he has been invited to high-profile events such as the ICPC World Final 2021 and the ACM-ICPC Asia Dhaka Regional Contest, where he served in key roles. His active involvement in academic and extracurricular activities further underscores his commitment to fostering learning and innovation within the community.

Research Skills

Mr. Mijanur Rahaman possesses advanced research skills honed through years of academic and professional experience. His expertise encompasses various methodologies, including quantitative and qualitative research methods, literature reviews, experimental design, and data analysis techniques. He is proficient in utilizing statistical software such as SPSS, R, and Minitab for data analysis and interpretation. Moreover, Mr. Rahaman demonstrates strong critical thinking abilities, enabling him to formulate research questions, develop hypotheses, and design rigorous research studies. His keen attention to detail ensures the accuracy and reliability of research findings, while his effective communication skills enable him to disseminate research results through scholarly publications and presentations. Additionally, he stays abreast of emerging trends and best practices in his field, continually refining his research skills to contribute meaningfully to the advancement of knowledge in computer science and related disciplines.

Publications

  1. Utilizing EfficientNet for sheep breed identification in low-resolution images
    • Authors: Himel, G.M.S.; Islam, M.M.; Rahaman, M.
    • Year: 2024
    • Citations: 0
    • Type: Article
  2. Vision Intelligence for Smart Sheep Farming: Applying Ensemble Learning to Detect Sheep Breeds
    • Authors: Himel, G.M.S.; Islam, M.M.; Rahaman, M.
    • Year: 2024
    • Citations: 1
    • Type: Article
  3. An Empirical Analysis of IT-Software Job Skill Requirements During COVID-19 Pandemic Period in Bangladesh
    • Authors: Rahaman, M.; Islam, M.M.; Rahman, M.S.
    • Year: 2023
    • Citations: 0
    • Type: Conference Paper
  4. Knowledge, attitude, and practice of a local community towards the prevention and control of rabies in Gaibandha, Bangladesh
    • Authors: Rahaman, M.M.; Siddiqi, U.R.; Sabuj, A.A.M.; Ghosh, S.; Uddin, N.
    • Year: 2020
    • Citations: 7
    • Type: Article
  5. State-of-the-art reformation of web programming course curriculum in digital Bangladesh
    • Authors: Kar, S.; Islam, M.M.; Rahaman, M.
    • Year: 2020
    • Citations: 3
    • Type: Article

Serhat Kilicarslan | Neural Networks Award | Best Researcher Award

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Assoc Prof Dr. Serhat Kilicarslan | Neural Networks Award | Best Researcher Award

Software Engineer at Bandırma Onyedi Eylül University Faculty of Engineering and Natural Sciences, Turkey

Assoc. Prof. Dr. Serhat Kılıçarslan is a highly skilled and accomplished professional in the field of computer science and engineering. With a strong background in research, teaching, and practical applications, Dr. Kılıçarslan has made significant contributions to the field. His research expertise includes computer networks, Wireless Sensor Networks (WSNs), Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML). He is proficient in programming languages such as C, C++, Java, Python, and MATLAB, and has a deep understanding of networking concepts, protocols, and technologies. Dr. Kılıçarslan has published extensively in reputable journals and conferences, showcasing his analytical and problem-solving abilities. Overall, Dr. Kılıçarslan’s expertise and skills have positioned him as a valuable asset in advancing the field of computer science and engineering.

Professional Profiles:

Education:

Assoc. Prof. Dr. Serhat KILIÇARSLAN has a strong academic background in computer engineering, mechatronics engineering, and technical education. He completed his Bachelor’s degree in Computer Engineering at Kocaeli University in June 2017. Following this, he pursued a Master’s degree in Mechatronics Engineering at Gazi Osmanpaşa University, graduating in September 2014. For his Master’s thesis, he developed programming software for microcontroller-based PLCs under the guidance of Assoc. Prof. Dr. Gökhan GELEN. Dr. KILIÇARSLAN continued his academic journey by completing his Ph.D. in Computer Engineering at Erciyes University in September 2021. His doctoral thesis focused on the development of non-linear activation functions for deep learning methods, under the supervision of Assoc. Prof. Dr. Mete ÇELİK.

Experience:

Assoc. Prof. Dr. Serhat KILIÇARSLAN currently serves as a faculty member at Bandırma Onyedi Eylül University, Faculty of Engineering and Natural Sciences, Department of Software Engineering. He joined the university in 2022, where he contributes to the field of software engineering through research, teaching, and academic leadership. Before joining Bandırma Onyedi Eylül University, Dr. KILIÇARSLAN served as a lecturer at Gaziosmanpaşa University. He was involved in the Department of Informatics, where he also held the position of Department Chair. Additionally, he served as a lecturer at Gaziosmanpaşa University, Pazar Vocational School, Department of Computer Technologies, specializing in Computer Programming. Dr. KILIÇARSLAN’s experience in these roles has equipped him with valuable insights and expertise in the field of software engineering and computer programming.

Research Interest:

Assoc. Prof. Dr. Serhat Kılıçarslan has a diverse research background focusing on various aspects of computer science and engineering. His research interests span several key areas, including Wireless Sensor Networks (WSNs), Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), Software-Defined Networking (SDN), Cloud Computing, Cyber-Physical Systems (CPS), Security, Privacy, and Big Data Analytics. In the realm of WSNs, Dr. Kılıçarslan explores the design, implementation, and optimization of WSNs for applications such as environmental monitoring, healthcare, and industrial automation. In the field of IoT, he delves into the architectures, protocols, and security mechanisms of IoT systems, aiming to enhance their efficiency, reliability, and security.

Skills:

Assoc. Prof. Dr. Serhat Kılıçarslan possesses a diverse set of skills in the field of computer science and engineering, honed through his research, teaching, and professional experiences. Some of his key skills include research skills, where he has a strong track record of publication in reputable journals and conferences. He is adept at formulating research questions, designing experiments, analyzing data, and drawing meaningful conclusions. Dr. Kılıçarslan is also proficient in programming languages such as C, C++, Java, Python, and MATLAB, which he applies in developing software solutions for various research projects. With a focus on computer networks, Dr. Kılıçarslan has expertise in networking concepts, protocols, and technologies, including TCP/IP, routing, switching, and network security. He is experienced in designing, implementing, and optimizing Wireless Sensor Networks (WSNs) and IoT systems for diverse applications, leveraging his knowledge of sensor technologies, communication protocols, and data processing techniques. Dr. Kılıçarslan applies Artificial Intelligence (AI) and Machine Learning (ML) techniques, such as neural networks, deep learning, and reinforcement learning, to solve complex problems in computer networks and related areas. He also has expertise in Software-Defined Networking (SDN), cloud computing, Cyber-Physical Systems (CPS), security, privacy, and Big Data Analytics. Overall, Dr. Kılıçarslan’s skills are integral to his contributions in advancing the field of computer science and engineering, with a focus on enhancing the efficiency, reliability, and security of modern computing systems and networks.

Publications:
  1. Classification and diagnosis of cervical cancer with stacked autoencoder and softmax classification
    • Authors: K Adem, S Kılıçarslan, O Cömert
    • Year: 2019
    • Citations: 162
  2. Diagnosis and Classification of Cancer Using Hybrid Model Based on ReliefF and Convolutional Neural Network
    • Authors: S Kiliçarslan, K Adem, M Celik
    • Year: 2020
    • Citations: 82
  3. Hybrid models based on genetic algorithm and deep learning algorithms for nutritional Anemia disease classification
    • Authors: S Kiliçarslan, M Celik, S Sahin
    • Year: 2021
    • Citations: 67
  4. RSigELU: A nonlinear activation function for deep neural networks
    • Authors: S Kiliçarslan, M Celik
    • Year: 2021
    • Citations: 63
  5. DIVORCE PREDICTION USING CORRELATION BASED FEATURE SELECTION AND ARTIFICIAL NEURAL NETWORKS
    • Authors: MK Yöntem, K Adem, T İlhan, S Kılıçarslan
    • Year: 2019
    • Citations: 57
  6. An overview of the activation functions used in deep learning algorithms
    • Authors: S KILIÇARSLAN, A Kemal, M Çelik
    • Year: 2021
    • Citations: 24
  7. Detection and Classification of Pneumonia Using Novel Superior Exponential (SupEx) Activation Function in Convolutional Neural Networks
    • Authors: S Kiliçarslan, Cİ Közkurt, S Baş, A Elen
    • Year: 2023
    • Citations: 21
  8. Performance analysis of optimization algorithms on stacked autoencoder
    • Authors: A Kemal, S Kilicarslan
    • Year: 2019
    • Citations: 19
  9. COVID-19 Diagnosis Prediction in Emergency Care Patients using Convolutional Neural Network
    • Authors: A Kemal, S KILIÇARSLAN
    • Year: 2021
    • Citations: 18
  10. Deep learning-based approaches for robust classification of cervical cancer
    • Authors: I Pacal, S Kılıcarslan
    • Year: 2023
    • Citations: 13